showcasing projects in the Clinic program. · showcasing projects in the Clinic program. Mission Statement: Harvey Mudd College seeks to educate engineers, scientists, and mathematicians

Projects Day is dedicated to Jack Alford and Mack Gilkeson

for their foresight and wisdom in the creation of the

Harvey Mudd College Clinic Program

Acknowledgments:

To all of the many Alumni and Parents who assist in the recruitment, formulation and conduct of Clinic

projects year to year, and to the Clinic Advisory Com-mittee who provide valuable industry perspective and advice. Your continued support is greatly appreciated.

& To all Harvey Mudd College

Faculty & Staff involved in the preparation of Projects Day

Harvey Mudd’s annual celebration of student achievement includes

Presentation Days (April 30 & May 2, 2018), showcasing senior thesis research and

class projects, as well as Projects Day (May 1, 2018),

showcasing projects in the Clinic program.

Mission Statement:

Harvey Mudd College seeks to educate engineers, scientists, and mathematicians well versed in all of

these areas and in the humanities and the social sciences so that they may assume leadership in their

fields with a clear understanding of the impact of their work on society.

48th Annual Projects Day

The Biology, Computer Science, Engineering, Global, Mathematics, and Physics Clinics of

Harvey Mudd College are pleased to present the work of our students.

Zach Dodds, Director Computer Science Clinic

Kash Gokli, Director

Engineering Clinic

Qimin Yang, Associate Director Engineering Clinic

Susan Martonosi, Director

Global Clinic

Weiqing Gu, Director Mathematics Clinic

Peter Saeta, Director

Physics Clinic

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Harvey Mudd College PROJECTS DAY

May 1, 2018

Program 10:30 a.m Registration and Poster Viewing Platt Campus Center 1:00 p.m. General Session Shanahan Center 1430 Welcome - Maria Klawe, President Remarks - Kash Gokli, Director, Engineering Clinic Milestone Awards - Lisa Sullivan, Dean of the Faculty Recipients: City of Hope Dart NeuroScience, LLC Niagara Bottling, LLC Proofpoint, Inc. 1:30 - 3:00 p.m. Project Presentations See Schedule 3:00 - 3:30 p.m. Break Shanahan Center: 1st Floor North Terrace & Thomas Garrett Plaza 3:30 - 5:00 p.m. Project Presentations See Schedule 5:15 - 6:00 p.m. Poster Reception Platt Campus Center Guests, Faculty, and Students

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Notes:

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Schedule of Presentations Time Location

1:30 2:00 2:30 3:30 4:00 4:30 SHAN

Project

Building Codes: SHAN = Shanahan Center for Teaching and Learning Note: The “B” in room numbers indicates “Basement Level.”

BIOLOGY/COMPUTER SCIENCE/ MATHEMATICS CLINIC Dart NeuroScience X X X 3425 Network Analysis and Methodology Development for Drug Discovery in Alzheimer’s Disease Helix OpCo, LLC X X X 3421 Integrating Genetics and Wearable Devices for Discovery COMPUTER SCIENCE CLINIC 23andMe X X X 3485 Genetic Gameplay: Showcasing 23andMe's Personal-Genetics API Accenture Labs X X X 2407 3d Model Integration for Agile Digital Product Development Amazon Music X X X B-480 Amazon Music Graph Amazon Prime Now X X X B-454 Image-Text Classification to Correct the Amazon PrimeNow Search Experience Barefoot Networks X X X 2450 Traffic Testing in Fully Programmable, 6.4Tbps Networks Consensus Corporation X X X 2407 Algorithmic Fairness: Using Machine Learning To Detect Disparate Impact In Geo-based Risk Modeling Intuitive Surgical X X X 3485 Temporal Segmentation of Surgical Suturing Lawrence Livermore National Laboratory X X X 2425 Integrating Distributed-Memory Machine Learning into Large-Scale HPC Simulations Mercedes-Benz Research & Development North America X X X 2450 Augmented and Mixed Reality for the Driver NASA AMES Research Center X X X 3425 Minimizing Communication in Uncertain Multi-Agent Schedules New Relic Inc. X X X 2461 Opening the Web Analytics Black Box with Innovations in Machine Learning, Visualization, Animation, and Big Data Pixar Animation Studios X X X B-470 Compressed Texture Access Proofpoint, Inc. X X X B-445 Detecting Phishing Using Deep Learning Networks

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Time Location

1:30 2:00 2:30 3:30 4:00 4:30 SHAN

Rapid7, Inc. X X X 2461 Securing Today’s Software-Development Pipelines Steelcase, Inc. X X X B-470 Wood Veneer Classification and Cataloguing, Mobile Webroot, Inc. X X X 3421 Machine Learning on DNS Data to Discover Security Threats

ENGINEERING CLINIC AT&T X X X 3461 High Dynamic Range Video Quality Analyzer ATI Metals X X X 3461 Scanning and Image Processing in a 3D Envelope BD Biosciences X X X 3465 Microfluidic Chip Quality Control System Improvement Ceremod X X X 2421 Spot Cooling in the Human Body City of Hope X X X 3481 Raman Spectrometry and Laser Ablation as a Minimally Invasive, Molecularly Guided Therapy for Cancer City of Hope X X X 3481 Redesigning Wireless Cameras and Smoke Evacuators for Laparoscopic Surgery Doosan Bobcat X X X 2454 Autonomous Attachment Coupling Eaton Corporation X X X 2454 Improved Electrically Operated Ground and Test Device (GTD) FarmX X X X 2421 Improving Agricultural Water Efficiency Georg Fischer Signet X X X 2475 Wireless Power and Communication for pH Sensor Networks GKN Aerospace X X X 2475 Optical Distortion Mapping System Development HP, Inc. X X X 2440 Study of Carbon Black Dispersion in Polyurethane: Impact on Mechanical and Electrical Properties HP, Inc. X X X 2440 SERS Based Cancer Detection Lawrence Livermore National Laboratory X X X 2425 Data Fusion for Ubiquitous Nuclear Threat Detection Meggitt Control Systems X X X B-480 Aerospace Wear Coatings Millennium Space Systems X X X 1480 Iodine Propellant Feed System Moog, Inc. X X X 3465 Harmonic Gear System Replacement in Space Application Actuator Niagara Bottling, Inc. X X X B-442 Bottling Line Speed Up Project Project Corsica X X X B-454 Pouch for Li Ion Battery

Project

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Time Location

1:30 2:00 2:30 3:30 4:00 4:30 SHAN

Systron Donner Inertial X X X 2460 Embedded Neural Network for Improved Inertial Sensor Calibration and Error Compensation Algorithm Techmation X X X 2460 Project Beluga: Perception System and State Estimation in GPS -Denied Environment Toyota X X X B-450 Development of Energy Recovery Technology for Class 8 Fuel Cell Truck WET X X X 1480 PHOSFORS (TM) Development

ENGINEERING/MATHEMATICS Niagara Bottling, LLC X X X B-442 Transportation Optimization

ENGINEERING/PHYSICS CLINIC Claremont Locally Grown Power X X X B-460 Investigating Hot Spots in Photovoltaic Panels through IdealPV's Patented Controller Sandia National Laboratories X X X B-460 Measuring the Permittivity of Ferroelectric Nanoparticles in an Epoxy Composite

GLOBAL CLINIC Kounkuey Design Initiative X X X B-450 Green Infrastructure Solutions for Urban Flooding in Kibera, Nairobi, Kenya

MATHEMATICS CLINIC EDR, Inc. X X X 2465 Address Detection in Sanborn Maps with Image Processing and OCR Intel Sports X X X B-445 Creating a 3D Sound System for Paired Volumetric Video Microsoft Bing X X X 2465 Correlation and Root Cause Detection in Bing Livesite Metrics

Project

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Key to Poster Session Layout

1. 23andMe, Inc. 2. Accenture Labs 3. Amazon Music 4. Amazon Prime Now 5. AT&T 6. ATI Metals 7. Barefoot Networks 8. BD Biosciences 9. Ceremod, Inc. 10. City of Hope - Raman 11. City of Hope - Wireless 12. Claremont Locally Grown Power 13. Consensus Corporation 14. Dart Neuroscience 15. Doosan Bobcat 16. Eaton Corporation 17. EDR 18. FarmX 19. Georg Fischer Signet 20. GKN Aerospace 21. Helix OpCo, LLC 22. Hewlett Packard - CB Dispersion 23. Hewlett Packard - SERS 24. Intel Corporation 25. Intuitive Surgical, Inc. 26. Kounkuey Design Initiative 27. Lawrence Livermore National Laboratory - CS 28. Lawrence Livermore National Laboratory - ENG 29. Meggitt Control Systems 30. Mercedes-Benz Research & Development 31. Microsoft Bing 32. Millennium Space Systems 33. Moog, Inc. 34. NASA AMES Research Center 35. New Relic, Inc. 36. Niagara Bottling - ENG 37. Niagara Bottling - ENG/MATH 38. Pixar Animation Studios 39. Project Corsica 40. Proofpoint, Inc. 41. Rapid7, Inc. 42. Sandia National Laboratories 43. Steelcase, Inc. 44. Systron Donner Inertial 45. Techmation 46. Toyota 47. Webroot, Inc. 48. WET

CLINIC ADVISORY COMMITTEE OF HARVEY MUDD COLLEGE

Industry Members: Tessa Adair ’14, Laserfiche

Paul Anderson, The Aerospace Corporation

Michael Bell, Beckman Coulter, Inc.

Joseph Betser, The Aerospace Corporation

Daniel A. Borton ’90, Amgen Inc.

Bob Butterfield, BD

Carl Carrera ’75/76, The Boeing Company

Frances Ferris ’80, The Boeing Company

Aaron Gable ’12, Google, Inc.

Sharon Kwan ’98, Thermo Fisher Scientific

David Lesyna, Optivus Proton Therapy, Inc.

John Livingston, Tandem Diabetes Care

Hal Lonas, Webroot, Inc.

Craig Snow, Raytheon Missile Systems

College Members: Maria Klawe, President

Dan Macaluso, V ice President, College Advancement

Lisa Sullivan, V ice President, Dean of the Faculty

Andrew Dorantes, VP for Administration & Finance/Treasurer

Scott Martin, Assistant VP for Business Affairs & Assistant Treasurer

Colleen Coxe, Director, Corporate Relations

Zach Dodds, Director, Computer Science Clinic

Kash Gokli, Director, Engineering Clinic

Qimin Yang, Associate Director, Engineering Clinic

Susan Martonosi, Director, Global Clinic

Weiqing Gu, Director, Mathematics Clinic

Peter Saeta, Director, Physics Clinic

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“(F)” Fall Semester “(S)” Spring Semester

“(TL)” Indicates Team Leader “(PM)” Indicates Project Manager

GLOBAL CLINIC

Kounkuey Design Initiative Green Infrastructure Solutions for Urban Flooding in Kibera, Nairobi, Kenya Liaisons: Chelina Odbert, Joe Mulligan, Vera Bukachi Advisor: Ziyad Duron Students: Isabel King (TL-F), Camille Croll (TL-S), Manu Kondapi, Andrea Vasquez (F), Eric Contee II (F), Eliana Goehring (S) Kibera is a large informal settlement in Nairobi, Kenya where annual flash flooding causes signifi-cant health, economic, and structural problems in the community. Current drainage infrastructure consists of informal channels that are not designed to handle the volume of water that falls during large rain events. The objective of this project is to work with the community to develop practical design improvements for the existing drainage channels that can be implemented in Kibera, to improve quality of life for residents.

MATHEMATICS CLINIC EDR Address Detection in Sanborn Maps with Image Processing and OCR Liaisons: Zachary Fisk, Paul Schiffer, Richard White Advisor: Rachel Levy Students: Daniel Zhang, Jeff Carney, Mehdi Drissi, Jordan Haack Our task is to automatically detect and read the handwritten addresses from EDR’s collection of 1.2 million Sanborn maps. Sanborn maps are de-tailed city maps produced regularly between 1880 and 2006. We use various image processing tech-niques to first find the street segments, and then detect the handwritten street names and house numbers. We then run these images through our OCR model, which reliably parses connected characters that are rotated or skewed.

Intel Sports Creating a 3D Sound System for Paired Volumetric Video Liaisons: Cody Gabriel, Peter Sankhagowit, Steven Xing Advisor: Weiqing Gu Students: Daniel Johnson (PM), Daniel Gorelik, Ross Mawhorter, Kyle Suver Intel's TrueView technology can reconstruct three-dimensional video at any location in a stadium using multiple video recordings. However, this system does not extend to audio. This project involves developing an approach to reconstruct game audio at any location based on microphone recordings, to combine with the existing volumet-ric video system. After exploring existing algo-rithms for sound source separation and localiza-tion, we are developing a prototype system called auVVio that extends these techniques to interac-tively reconstruct game sounds in 3D.

Microsoft Bing Correlation and Root Cause Detection in Bing Livesite Metrics Liaisons: Debashish Ghosal, Gautam Dewan Advisor: Talithia Williams Students: Grant Belsterling, Preethi Seshadri, Zhaocheng Yi (PM) Bing is the second most popular search engine in the United States. Bing’s Livesite Engineering team collects system performance metrics to detect incidents (outages, etc.) that negatively impact the end user experience. These incidents result in a loss of ads revenue and users. Identifying root cause of such incidents requires sifting through a lot of metrics and narrowing down the root cause to one or more key metrics. Our clinic team is working to streamline and automate this process by leveraging statistical models and methods.

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Personalized Projects Day Schedule

Please fill in the empty slots below with the presentations you would like to attend.

Time Event Location

10:30 a.m. Registration and Poster Viewing Platt

Campus Center

1:00 p.m. General Session Shanahan Center

1430

1:30 p.m.

2:00 p.m.

2:30 p.m.

3:00 p.m. - 3:30 p.m.

Break Shanahan Center

Thomas Garrett Plaza

3:30 p.m.

4:00 p.m.

4:30 p.m.

5:15 p.m. - 6:00 p.m.

Poster Reception Platt

Campus Center

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WET PHOSFORS (TM) Development Liaisons: Scott Winslow, Helen Park, Markos Okihisa Advisor: Matthew Spencer Students: Elijah Carbonaro, Kimberly Joly (TL-F), Hamza Khan (TL-S), Trevor Fung (S), Gabriel Quiroz (S), Shiv Seetharaman (S), Lydia Sylla (F), Felipe Borja (F) The WET Clinic team built a fleet of small aquatic robots to perform light shows. The choreography of these shows uses a computer vision system to precisely localize the pods and a multilink Blue-tooth low energy system to communicate with the pods. The fleet of pods uses multi-robot trajectory planning algorithms to move in a choreographed sequence.

ENGINEERING/MATHEMATICS CLINIC Niagara Bottling Transportation Optimization Liaison: Sun Kwok Advisor: Arthur Benjamin Students: Cade Hulse (PM), Anji Malpani, Shreyas Kadaba, Porter Adams , Ryan Haughton (S), Laurel Schy (F) This project has aimed to uncover inefficiencies at Niagara Bottling by taking a more holistic ap-proach to the problem of optimizing transportation processes across Niagara's facilities. The Harvey Mudd team has investigated potential cost-reduction measures through the application of operations research and statistical methods. The end goal of this project has been to optimize total supply chain costs across facilities as well as pro-vide invaluable business insights to Niagara.

ENGINEERING/PHYSICS CLINIC Claremont Locally Grown Power Investigating Hot Spots in Photovoltaic Panels through IdealPV's Patented Controller Liaisons: Kent Kernahan, Devon Hartman Advisors: Qimin Yang, Tom Donnelly (F), Peter Saeta (S), Dick Haskell (Emeritus-S) Students: Jonathan Kupfer (TL-F), Florence Walsh (TL-S), Dallon Asnes, William Lamb, Quentin Barth (F) Claremont Locally Grown Power is a program of CHERP Inc., (Community Home Energy Retrofit Project), a California-based 501(c)(3) non-profit social enterprise, in an exclusive licensing agree-ment to deploy idealPV’s patented solar technolo-gy. The clinic team is assisting CLGP in their goal of outfitting lower-to-middle income households with cheaper, safer, and more efficient solar panels by providing third-party verification and testing of the underlying idealPV technology through lab research, physics-based mathematical modeling, and prototype comparison field studies.

Sandia National Laboratories Measuring the Permittivity of Ferroelectric Nanoparticles in an Epoxy Composite Liaison: Dr. Todd Monson Advisors: Albert Dato, Peter Saeta Students: Andrew Bishop (TL-S), Richard Liu (TL-F), Alejandro Baptista, Lupe MacIntosh, Charles Dawson (F), Benjamin Lehman (S) Barium titanate (BTO) is a ferroelectric material commonly used in capacitors because of its high bulk dielectric constant, which may be even higher in nanoparticle form. We are determining the die-lectric constant of BTO nanoparticles as a function of particle size by measuring composites of BTO nanoparticles in epoxy. We’re using ball-milling alongside surfactants to reduce nanoparticle ag-glomeration, examining particle geometry using scanning electron microscopy, and using finite element analysis to extract the dielectric constant of the nanoparticles.


“(TL)” Indicates Team Leader “(PM)” Indicates Project Manaz- 19

Project Corsica Pouch for Li Ion Battery Liaisons: Brian Strom, Rossella Giardi Advisor: Albert Dato Students: Charles Van Eijk (TL-S), Michaela Yaman (TL-F), Sean Nguyen, Bryce Murley, Bohan Gao (S), Jakim Johnson (F) Batteries for consumer electronic devices typically consist of a stack of anode and cathode sheets separated by thin membranes, wrapped in a flexi-ble pouch. The standard battery pouch is a lami-nate consisting of metal and plastic layers. Failure in the pouch material can lead to swelling or dan-gerous chemical reactions within the battery. The goal of the Project Corsica clinic project is to design an alternative battery pouch material that improves the safety and reliability of the batteries.

Systron Donner Intertial Embedded Neural Network for Improved Inertial Sensor Calibration and Error Compensation Algorithm Liaisons: Bonnie Gordon ’11, Tony Rios, Emmanuel Quevy Advisor: Tony Bright Students: Nicholas Sakowski (TL-S), Christopher Kotcherha (TL-F), Austin Shin, Eyassu Shimelis, Aaron Lutzger (S) The Systron Donner Inertial (SDI) clinic team has been tasked with designing, writing, and judging the performance of an improved gyroscope bias compensation algorithm. The goal of the project is to reduce rate error by a factor of 10. This goal will be reached with the assistance of statistical analysis and an embedded neural network which will allow the team to explore new causes in gyro-scope bias.

Techmation Project Beluga: Perception System and State Estimation in GPS -Denied Environment Liaisons: Jerry Hsiung ’16, Benjamin Chasnov ’16, Cyrus Huang ’16, Vaibhav Viswanathan ’17 Advisor: Anthony Bright Students: Zayra Lobo (TL-S), Nancy Wei (TL-F), Austin Chun, Dominic Frempong, Evan Chapman (S), John Lee (S) The Techmation Clinic team selected and imple-mented an acoustic beacon and hydrophones to augment an IMU in an Autonomous Underwater Vehicle (AUV). The team then used these sensors for state estimation of the AUV in a GPS-denied environment. A major part of this process was also the development of an Extended Kalman Filter, a state estimation algorithm for sensor integration, and a localization algorithm for the acoustic sys-tem.

Toyota Motor Corporation Development of Energy Recovery Technology for Class 8 Fuel Cell Truck Liaisons: Justin Ward, Tak Yokoo, Advisor: Okitsugu Furuya Students: Duncan Crowley (TL-F), Sean Mahre (TL-S), Mina Berglund, Rilke Griffin, Kim Tran The Toyota clinic project aims to investigate alter-native methods of storing and utilizing energy recovered in the regenerative braking process of Toyota’s hydrogen fuel cell drayage truck. This involves researching and ideating various energy storage solutions and quantifying the amount of energy that can be recovered along several dray-age routes from the Port of Los Angeles to Long Beach.

BIOLOGY/ COMPUTER SCIENCE/MATHEMATICS CLINIC Dart NeuroScience, LLC Network Analysis and Methodology Development for Drug Discovery in Alzheimer’s Disease Liaisons: Philip Cheung ‘96, Qingying Meng, Douglas Fenger Advisor: Eliot Bush Students: Annalise Schweickart, Chloe Chan, Sasha Friedrich, Brendan Murran

The goal of this project, sponsored by Dart Neuro-Science, is to generate potential drug targets relat-ing to memory and neural plasticity, focusing specifically on Alzheimer’s disease. We have developed a novel methodology built on existing network analysis algorithms to identify key genes implicated in Alzheimer’s Disease. This methodol-ogy can be used to identify potential drug targets for Alzheimer’s, and in the future might also be used towards drug discovery for other diseases.

Helix OpCo, LLC Integrating Genetics and Wearable Devices for Discovery Liaisons: Nicole Washington ’99, Anupreet Walia, Scott Burke ’91 Advisor: Lisa Kaczmarczyk Students: Jasmin Rizko (PM-S), Moira Dillon (PM-F), Mahlet Melaku, Crystal Xiang

Helix is a private software platform company for personalized genomic products. The goal of our Clinic project was to integrate sequencing results from Helix and activity tracking via Fitbit, and develop a proof-of-concept to monitor these data in research studies. We built a participant monitor-ing dashboard and conducted IRB-approved hu-man subject studies to demonstrate the dash-board’s capabilities while examining traits related to fitness and sleep.

COMPUTER SCIENCE CLINIC

23andMe Genetic Gameplay: Showcasing 23andMe's Personal-Genetics API Liaison: Arnold De Leon '90 Advisor: Julie Medero Students: Teal Stannard (PM), Giovani Barrios-Arciga, Elise Cassella, Jacob Rosalsky

23andMe is a bioinformatics company whose mission is to help people access, understand, and benefit from the human genome. 23andMe analyz-es DNA to identify specific variations, or alleles, in order to determine ancestry and wellness traits. 23andMe makes much of this information availa-ble to third party developers through a public API. The goal of this project is to create an application which will help encourage other developers to use the public API. Therefore, the application should serve as an example of how to correctly access the public API and securely handle a user’s genetic information. Additionally, we aim to engage users while their data is being analyzed.

Accenture Labs 3D Model Integration for Agile Digital Product Development Liaisons: Robert Dooley, Alex Kass Advisor: Ran Libeskind-Hadas Students: Emily Dorsey (PM), Wenbo (Tracy) Cao, Holly Mitchell, Shailee Samar, Abigail Schantz

3D asset management can pose a significant prob-lem for Augmented and Virtual Reality (AR/VR) applications. The Harvey Mudd Clinic Team is working with Accenture Labs to make AR/VR content management easier by providing a straightforward workflow allowing users to alter their content from within existing tools. The team’s Unity plugin allows inexperienced users to understand the tradeoffs between the visual quality of their assets and app performance, and then manage that tradeoff by customizing their asset’s polygon counts.

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“(TL)” Indicates Team Leader “(PM)” Indicates Project Manager 18

Amazon Music Amazon Music Graph Liaisons: Dr. Fabian Moerchen, Dr. Gert Lanckriet Advisor: Robert Keller Students: Dan Diemer, Rebekah Justice, Renata Paramastri, Amelia Sheppard (PM), Cha Suaysom

Our project focuses on creating an enhanced infra-structure to enable Amazon's intelligent personal assistant, Alexa, to respond to a broader and deep-er range of queries about music. To this end, we developed an ontology (graphical knowledge structure) for recorded music and prototyped a database-backed, text-based web interface based on the ontology, which demonstrates responses to sample queries. Amazon Prime Now Image-Text Classification to Correct the Amazon PrimeNow Search Experience Liaisons: Igor von Nyssen, Al Vethamuthu Advisor: Yekaterina Kharitonova Students: Alex Mitchell, (PM-S), Zhepei Wang (PM-F), Kofi Sekyi-Appiah, Tina Zhu

Amazon Prime Now wants to automate the pro-cess of identifying products whose images do not match their associated titles on their website. Our team has designed and implemented a solution using various machine learning techniques to auto-matically identify these problematic listings.

Barefoot Networks Traffic Testing in Fully Programmable, 6.4Tbps Networks Liaisons: Remy Chang, Vladimir Gurevich Advisor: Geoff Kuenning Students: E. Taylor Yates (PM), Gus Callaway, M Sangheetha Naidu, Matthew Gee

Barefoot Networks builds high-speed programma-ble networking devices. Our team is building a configurable network traffic tester that can handle up to 6.4Tbps of traffic--enough for every student at the Claremont Colleges to simultaneously stream 200 high-definition movies. The tester will send varying traffic patterns to the device under test, which will immediately forward the packets back to the tester. The tester will analyze packet delay, sequencing, and loss, and will gather and report relevant statistics. Consensus Corporation Algorithmic Fairness: Using Machine Learning To Detect Disparate Impact In Geo-based Risk Modeling Liaisons: Harrison Lynch, Allen Tam, Jing Shen Advisor: Yi-Chieh (Jessica) Wu Students: Daniel King (PM-S), Abby Tisdale (PM-F), Tiffany Fong, Kyra Yee

Consensus Corporation makes point-of-activation software for the sale of mobile phones. This soft-ware includes a risk prediction engine, which predicts whether or not a phone plan will be deac-tivated and the sale deemed fraudulent. The Con-sensus Clinic Team’s project is twofold: (1) im-prove this risk prediction engine by incorporating new features and analyzing different machine learning models and (2) detect unintended bias in the risk prediction engine.

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Meggitt Control Systems Aerospace Wear Coatings Liaisons: Leo Leyanna, Mark Abrams Advisor: Gordon Krauss Students: Kristin Lie (TL-S), Jacob Knego (TL-F), Briana Liu (S), William Teav (S), Alex Ravnik (F), Zach Goland (F), Fernando Fernandez (F) Meggitt Control Systems is an aerospace company that produces a variety of products for extreme environments. The Meggitt clinic team was tasked with researching, testing and characterizing low-cost, environmentally friendly surface treatments to reduce wear on a butterfly bleed-air valve. These valves are used in aircraft engines and must withstand high temperatures while experiencing as little wear as possible over 50,000 cycles.

Millennium Space Systems Iodine Propellant Feed System Liaison: Jason Murray Advisor: Mary Cardenas Students: Richard Ni (TL-F), Alex Echeverria (TL-S), Christopher Strong (F), Marianna Sbordone (F), Kaitlyn Eng (S), Maggie Gelber (S) The team designed and built an iodine feed system which stores solid iodine for a minimum of five years, and sublimates solid iodine to deliver gase-ous iodine at a rate of at least 3 mg/s within 10 minutes in a zero gravity setting. The team validat-ed this proof of concept design through rigorous thermal and structural modeling, in addition to testing the proof of concept for corrosion, leak resistance, flow control, thermal management, and propellant management.

Moog, Inc. Harmonic Gear System Replacement in Space Application Actuator Liaisons: Jason Ro ’99, Armand Asadurian Advisor: Philip D. Cha Students: Luis Viorney (TL-S), Angelica Virrueta (TL-F), Giulia Castleberg (F), Alex Nunes (F), Derrick Chun (S), Jacob Garcia (S), Nate Smith (S) Strain wave gear reduction technology has domi-nated the aerospace rotary transmission industry for half a century due to its simplicity, efficiency, and accuracy. Moog, Inc. has sponsored a Harvey Mudd Clinic team to develop an alternative for use in the sponsor’s satellite actuators. The team’s solution relies on hypocycloidal geometry to achieve a high reduction ratio, zero backlash, and superior performance.

Niagara Bottling Bottling Line Speed Up Project Liaisons: Damon Choate, Ian Song ’17, Alexander Mouschovias Advisor: Ziyad Duron Students: Jose Godinez (TL-S), Ryan Gibbs (TL-F), Arthur Reyes, Priscilla Chu (F), Deji Andrew (F), Rikki Walters (Soph.-S) This project focuses on the P6 gallon bottle blow-molding machine at Niagara’s Corporate plant and finding physical limitations to speed increase. The team is characterizing the dynamics of the ma-chine and finding resonant frequencies at which the machine vibrates due to its operation. By find-ing what is most likely to break first due to vibra-tion, and then strengthening it, the team can safely increase the speed of operation.

GKN Aerospace Optical Distortion Mapping System Development Liaisons: Brooke Haueisen, Philip Sturman Advisor: Kash Gokli Students: Wenkai Qin, Sr. (TL-F), Josephine Wong, Sr. (TL-S), Enoch Yeo, Robert Gonzalez (S), Sydney Cozier, (F), Roger Hooper (F) The GKN Aerospace Clinic Team is designing, implementing, and testing a new software system to locate and quantify optical distortions in cockpit windows, fighter jet canopies, and other aircraft transparencies. The software uses modern comput-er vision and data analysis tools to improve upon the industry standard for optical distortion map-ping. GKN Aerospace will use our solution to prevent expensive damage on aircraft canopies and achieve higher product quality.

HP, Inc. SERS Based Cancer Detection Liaisons: Anita Rogacs, Jason Aronoff, Caitlin Dejong, Brian Keefe, Raghuvir Sengupta, Yiming Zuo Advisor: Liz Orwin Students: Michelle Lanternman (TL-F), James Palmer (TL-S), Zunyan Wang, Willis Sanchez-DuPont (S), Missy Spangler (S), Ronak Bhatia (F) Nisha Maheshwari (F) The goal of this project is to explore the predictive diagnostic value of the complex spectra generated by metabolites adsorbed onto the HP Surface Emission Raman Spectroscopy substrates from cancerous and healthy cervical tissue in lab. The project has two primary components. The labora-tory component entails cell culturing and prepara-tion of the samples for data collection. Then when the data is collected, machine learning algorithms will be used to distinguish healthy from cancerous cell by the SERS spectra.

HP, Inc. Study of Carbon Black Dispersion in Polyurethane: Impact on Mechanical and Electrical Properties Liaisons: Bin Huang, Guang Jin Li Advisor: Nancy Lape Students: Sarah Silcox (TL-S), Jacey Coniff (TL-F), Jordan Howard-Jennings (S), Kaitlyn Loop (S), Aliki Sarantopoulos (S), Lisa Mattson (F), Curtis Shin (F), Meily Wu Fung (F) The HP CB Clinic Team studied polyurethane (PU)-carbon black (CB) composites as new elasto-mer materials for Binary Ink Developers (BIDs) on HP Indigo printing presses. The investigation focused on how CB dispersion and loading affect the mechanical and electrical properties of the composites to meet HP’s product functionality and reliability requirements. Techniques such as ten-sile/tear, voltage-current sweeping, and SEM im-aging analysis were used for material characteriza-tion.

Lawrence Livermore National Laboratory Data Fusion for Ubiquitous Nuclear Threat Detection Liaisons: Simon Labov, Brandon Seilhan Advisor: David Harris Students: Sarah Wang (TL-F), Yashas Hegde (TL-S), Emily Lane, Arch Robison, Jordan Abrahams (S) As part of the nuclear terrorism prevention effort at Lawrence Livermore National Laboratory (LLNL), the LLNL Clinic Team is challenged with testing and improving the performance of a “smart” network of pocket-size radiation sensors. This will be done by 1) using non-threat radiation to monitor the calibration of the sensors, 2) config-uring sensors to work together to improve detec-tion sensitivity and confidence, and 3) integrating location information of known radiation sources to reduce false alarm rates. LLNL is operated under Contract DE-AC52-07NA27344.

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Intuitive Surgical Temporal Segmentation of Surgical Suturing Liaisons: Anthony Jarc, Liheng Guo Advisor: Colleen Lewis Students: Juliet Forman, Varsha Kishore (PM), Jane Wu, Hyobin You, Angela Zhao

Intuitive Surgical specializes in minimally inva-sive robot-assisted surgery and they developed the da Vinci surgical system. The objective of our project is to analyze the motion of surgical instru-ments controlled by surgeons and video recording of surgeries by developing computational models that automatically recognize suturing activities during robot-assisted surgery. Our approach com-prises machine learning and neural network archi-tectures. These computational models could then be used to generate advanced analytics such as surgeon performance reports.

Lawrence Livermore National Laboratory Integrating Distributed-Memory Machine Learning into Large-Scale HPC Simulations Liaisons: Cyrus Harrison, Ming Jiang, Brian Gallagher, Matt Larsen Advisor: Christopher Stone Students: Amy Huang (PM), Evan Chrisinger, Jeb Bearer, Katelyn Barnes

Supercomputers provide the computing power for complex physics simulations, but these simula-tions require frequent manual adjustments to pre-vent run-time failures. Machine learning is a po-tential solution for automating this process. The LLNL clinic team is developing a machine learn-ing model appropriate for supercomputers that can learn from the output of physics simulations as they run in real time.

Mercedes-Benz Research & Development North America Augmented and Mixed Reality for the Driver Liaisons: Mark Poguntke, Kavita Saney, Jeff Bertalotto Advisor: Geoff Kuenning Students: Aman Raghuvanshi (PM-S), Julio Medina (PM-F), Drew Summy, Meredith Simpson

The objective of this project is to explore the pos-sibility of using augmented reality (AR) while driving a car. This entails comparing various AR headsets such as the Microsoft Hololens and the Meta 2, and building a functioning prototype that addresses a moving car use-case. The headset comparison involves testing devices in a stationary and moving vehicle, and understanding their re-spective development experiences. Our prototype application attempts to help drivers park more safely and precisely, and serves as a starting point for the Mercedes-Benz team for an extendable AR headset prototyping framework.

NASA AMES Research Center Minimizing Communication in Uncertain Multi-Agent Schedules Liaison: Dr. Jeremy Frank Advisor: Jim Boerkoel Students: Grace Diehl (PM), David Chu, Marina Knittel, Judy Lin, William Lloyd

Our project aims to provide NASA with new scheduling protocols for multi-agent systems (e.g., a robot team). In such systems, scheduling disturb-ances (due to environmental factors or equipment malfunction) may necessitate rescheduling. How-ever, communicating new schedules to all agents can be resource intensive. Reducing rescheduling can improve the performance of multi-agent sys-tems when communication resources are limited. Our team has designed three algorithms to mini-mize rescheduling, trading communication for schedule quality. Further, we developed infrastruc-ture for testing such algorithms.

New Relic, Inc. Opening the Web Analytics Black Box with Innovations in Machine Learning, Visualization, Animation, and Big Data Liaisons: Bill Kayser, Merlyn Albery-Speyer Advisor: Melissa O’Neill Students: Pratyush Kapur (PM-S), Lee Norgaard (PM-F), Alexandre Trudeau, Edward Carroll

Have you ever wondered how your website is performing? Wouldn’t it be convenient to know if your website is going to experience problems before they happen? The New Relic Clinic Team is exploring new ways to visualize website analyt-ics data, communicate application health, and predict spikes in errors. Using animation, machine learning, and deep learning, the New Relic Clinic Team is developing innovative and unique solu-tions for New Relic’s customers.

Pixar Animation Studios Compressed Texture Access Liaisons: Stephen Friedman ‘03, Wayne Wooten Advisor: Z Sweedyk Students: Doren Lan (PM), Kevin Shimba Bengtsson, Sally Cheng, Nick Gott, Cam Zhou

Pixar Animation Studios’ RenderMan is software used to render all Pixar films and is widely used in the visual effects industry. With RenderMan, Pix-ar's continued aim is to speed up rendering, partic-ularly for textures, which provide fine detail on 3D shapes. The goal of this project is to improve on rendering speed and reduce memory usage by providing higher compression rates for textures on disk and in cache. The clinic team researched data compression algorithms, implemented a promising approach, and evaluated the results.

Proofpoint, Inc. Detecting Phishing Using Deep Learning Networks Liaisons: Thomas Lynam, Mike Morris '97 Advisor: Zach Dodds Students: Daniel Sonner (PM), Nic Trieu, Srinidhi Srinivasan, Amberlee Baugus, Montana Roberts

Proofpoint is a leader at identifying online threats. This project seeks to more accurately classify phishing webpages based on their look, i.e., their visual rendering within a browser. The team de-signed, piloted, and tested software tools to sup-port this investigation, culminating in a machine-learning pipeline that estimates the probability that a page is phishing based on its screen capture.

Rapid7, Inc. Securing Today’s Software-Development Pipelines Liaisons: Corinne Druhan ‘14, James Green, Bryan Trujillo ‘15 Advisor: Elizabeth Sweedyk Students: Zhenghan Zhang, Spencer Michaels, Eric Nguyen, Sarah Sedky

Our project aims to expand the capabilities of Rapid7's security assessment platform by integrat-ing the company’s newly-developed container assessment service into popular continuous inte-gration tools, namely Jenkins, Bamboo, and Teamcity. Anyone developing a container with these tools can add our plugin to the build pipeline to check for vulnerabilities during each build. The plugin generates a detailed assessment report, and the user can configure rules to pass or fail the build depending on various criteria present in the assessment results.

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Doosan Bobcat Autonomous Attachment Coupling Liaisons: John Pfaff, Jonathan Roehrl Advisor: Christopher Clark Students: Aman Fatehpuria (TL-S), Jessica Lupanow (TL-F), Gabriel Rubin, Darien Joso (F), Kayla Yamada (F), David Olumese (S), Jingnan Shi (S) The Doosan Bobcat clinic team will develop a proof of concept for autonomously driving a com-pact track loader to connect to a bucket attach-ment. Assumed starting conditions include flat, level ground and close alignment of the attach-ment and loader. Sensors, such as LiDAR sensors, will be used to determine the position of the vehi-cle with respect to the bucket. This position will be fed into the control system, which will send de-sired commands to the tracks on the loader.

Eaton Corporation Improved Electrically Operated Ground and Test Device (GTD) Liaisons: Logan Weigle, Koustubh Ashtekar, Brad Leccia, Tyler Holp Advisor: Patrick Little Students: Lupe Carlos (TL-S), Thomas Morgan-Witts (TL-F), Kathryn Belling (F), Morgan Blevins (F), Bella Puentes (S), Matthew Huerta (S), Christopher McElroy (S) Eaton Corp manufactures high voltage circuit breakers and related electrical safety devices. Ground and Test Devices (GTD) are used to ground the line or load side of the power bus bars for maintenance activities. The Eaton Clinic Team has been enlisted to improve design flaws in a GTD that was pulled from the market when updat-ed standards from the Institute of Electrical and Electronics Engineers (IEEE) were released.

FarmX Improving Agricultural Water Efficiency Liaison: Bill Jennings Advisor: David Money Harris Students: Kamau Waller (TL-S), Tess Despres (TL-F), Hill Balliet, Bailey Meyer, Geneva Ecola (S), Sitoë Thiam (F) FarmX, a San Francisco startup, aims to save up to 2% of California’s water by providing precision irrigation management. The HMC FarmX clinic team improved two sensor systems: a weather station, which measures the farm’s local water cycle, and a dendrometer, which monitors tree health. These sensor systems will help FarmX provide better irrigation recommendations and alert farmers when their crops are in danger.

Georg Fischer Signet Wireless Power and Communication for pH Sensor Networks Liaisons: Chuck Gerner, Steve Wells, Ph.D., Kamran Afshari Advisors: Ruye Wang (S), Brian Bryce (F) Students: Isabel Martos-Repath (TL-S), Christine Goins (TL-F), Lauren Hu, David Kwan, Benjamin Iten (S), Kai Kaneshina (F) Georg Fischer Signet is an engineering firm that produces flow and analytical technology. The 2017-2018 Georg Fischer Signet Clinic Team aims to design, build, and test a corrosion-proof method of internally processing and communicating pH and temperature measurements to a remote data collection network. To avoid corrosion, the project implements wireless power through inductive coupling and wireless communication through Bluetooth Low Energy. A LoRa network architec-ture is used to receive data from multiple units.


Steelcase, Inc. Wood Veneer Classification and Cataloguing, Mobile Liaisons: Ed Vander Bilt, Mark Schild, Allen Sietsema Advisor: Katherine Breeden Students: Brenda Castro (PM), Dalton Varney, Jessica Wang, Samantha Andow

Steelcase is looking to ensure color consistency before large purchase orders for their wood veneer furniture. In order to reduce waste due to veneer color issues, our clinic team is developing a porta-ble veneer classification device that can verify veneer colors objectively in uncertain lighting conditions. The prototype is a mobile lightbox with an intuitive graphical user interface and a computer vision classification system.

Webroot, Inc. Machine Learning on DNS Data to Discover Security Threats Liaisons: Dave Krich, Kiran Kumar, Hal Lonas, Trung Tran, Cathy Yang Advisor: Lisa Kaczmarczyk Students: Julia McCarthy (PM), Anthony Romm, Reiko Tojo, Danny Wang

In this project, the goals were to aggregate DNS-level data, apply machine learning approaches to identify command and control (C&C) botnets through automated analysis of live traffic patterns, and construct a website for dynamic visualization of threats. Visualizations help the user pinpoint where botnet attacks are coming from, identify geographic hotspots for botnet activity, and find out who is at risk for infection.

ENGINEERING CLINIC

AT&T High Dynamic Range Video Quality Analyzer Liaisons: Dr. Peshala Pahalawatta, Douglas Hu ’14, Shamik Maitra ’02 Advisor: Timothy J. Tsai Students: Justin Lauw (TL-S), Owen Morrison (TL-F), Ankoor Apte (S), Nick Draper (S), Tianyi Ma (S), Bradley Phelps (F), Hanna Ching (F), Marisol Guzman (F)

Design and prototype of High Dynamic Range/Wide Color Gamut (HDR/WCG) video analyzer tool that automates the process of detecting four artifacts: contouring, incorrect color space, clip-ping and noise artifacts in video content which may arise during poor conversion from legacy Standard Dynamic Range (SDR) content. Project involves designing artifact detection algorithms to detect the four artifacts in HDR videos and pack-aging the algorithms into an intuitive Graphical User Interface (GUI) for users to adjust algorithm parameters and view results.

ATI Metals Scanning and Image Processing in a 3D Envelope Liaisons: Noah Philips, Ph.D ’03, Gordon Alanko, Ph.D., Gordon Dobbie, Joe Kelly Advisor: Timothy J. Tsai Students: Patrick Scalise (TL-S), Rob Simsiman (TL-F), Peyton Holm, Zach Shattler, Rachel Perley (S), Chance Bisquera (F)

ATI Metals manufactures high performance metal products for the nuclear energy, chemical pro-cessing, and aerospace industries. ATI’s customers require parts fabricated to precise dimensions. The ATI clinic team has integrated computer vision techniques and laser rangefinders into an automat-ed measurement system that generates a 3D model of metal components post-process on the hot roll-ing mill. This system will streamline ATI’s pro-duction by detecting out-of-spec parts earlier in the process, and assist process engineers in im-proving product consistency.

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BD Biosciences Microfluidic Chip Quality Control System Improvement Liaisons: Atul Madhusudan, Alireza Salmanzadeh, Ph.D., Ruth Sung ’17 Advisor: Leah Mendelson Students: Ramita Kondepudi (TL-F), Marissa Lee (TL-S), Jesus Villegas, Sati Smyth (F), Valerie Kwee (S), Russell Salazar (S)

The 2017-18 BD Biosciences Clinic Team im-proved a quality control (QC) system for an acous-tic microfluidic chip. This chip separates white blood cells, which are of primary interest for the detection of autoimmune disorders, from the rest of blood. The QC system acquires images of flow through the chip and reports the accuracy of blood separation through image processing techniques. The team improved mechanical design and image processing components of this system to reduce manufacturing cost and processing time. Ceremod, Inc. Spot Cooling in the Human Body Liaisons: Dr. Kim Burchiel, Dr. Chris Madden, Dr. Shaun Morrison Advisor: Erik Spjut Students: Aurora Leeson (TL-S), Jasmine Yang (TL-F), Kyla Scott, Brenden Brown (S), Scott Montague (S), Jesus Solano (F), Angela Sun (F)

Ceremod, Inc. is a startup founded at Oregon Health & Science University to foster innovation in medical technology. The Ceremod, Inc. clinic team has modeled and designed a flexible, bio-compatible subsystem to cool a small target region in the human body.The modeling results are being used in feasibility and design studies of the experi-mental and production devices.

City of Hope Raman Spectrometry and Laser Ablation as a Minimally Invasive, Molecularly Guided Therapy for Cancer Liaisons: Dr. Yuman Fong, Dr. Veronica Jones, Dr. Lily Lai, Dr. Dan Schmolze Advisors: Phil Cha, Michael Storrie-Lombardi Students: Ragini Kothari (TL-S), Viviana Bermúdez Reyes (TL-F), Jenny Smith, Youkang Shon, Dominique Mena

The 2017-18 COH-Raman team aimed to reduce the collection time for Raman spectra of breast tissue to 1-3 seconds. This spectral database was analyzed using machine learning algorithms to display the probability of breast cancer. The spec-tral analysis is driven by understanding the bio-chemical markers that are evident in each unique Raman spectrum. The team also investigated Sur-face Enhanced Raman Spectroscopy (SERS) to enhance the Raman spectra. Additionally, the team worked on combining Raman diagnostics with laser ablation treatment. City of Hope Redesigning Wireless Cameras and Smoke Evacuators for Laparoscopic Surgery Liaisons: Dr. Kurt Melstrom, Dr. Yanghee Woo, Dr. Mustafa Raoof, Dr. Yuman Fong Advisor: Angie Lee Students: Lam Huynh (TL-F), Lillian Liang (TL-S), Marisa de Souza (F), Casey Gardner (F), Sabrina Chang (S), Ice Limchantra (S), Elizabeth Poss (S)

The City of Hope Wireless Clinic team is design-ing low-cost and wireless laparoscopic cameras and smoke evacuators. In laparoscopic surgery, smoke is a byproduct that must be evacuated be-cause it impedes visibility and is potentially haz-ardous, ultimately prolonging surgery. In addition to designing the systems to be wireless, the team is incorporating re-circulation of insufflated air into the smoke evacuation system and first-person view (FPV) VR technology into the camera system. With their designs, the team aims to improve visu-alization of the abdominal cavity during laparo-scopic surgery and increase access to laparoscopic surgical tools.

15



Steelcase, Inc. Wood Veneer Classification and Cataloguing, Mobile Liaisons: Ed Vander Bilt, Mark Schild, Allen Sietsema Advisor: Katherine Breeden Students: Brenda Castro (PM), Dalton Varney, Jessica Wang, Samantha Andow

Steelcase is looking to ensure color consistency before large purchase orders for their wood veneer furniture. In order to reduce waste due to veneer color issues, our clinic team is developing a porta-ble veneer classification device that can verify veneer colors objectively in uncertain lighting conditions. The prototype is a mobile lightbox with an intuitive graphical user interface and a computer vision classification system.

Webroot, Inc. Machine Learning on DNS Data to Discover Security Threats Liaisons: Dave Krich, Kiran Kumar, Hal Lonas, Trung Tran, Cathy Yang Advisor: Lisa Kaczmarczyk Students: Julia McCarthy (PM), Anthony Romm, Reiko Tojo, Danny Wang

In this project, the goals were to aggregate DNS-level data, apply machine learning approaches to identify command and control (C&C) botnets through automated analysis of live traffic patterns, and construct a website for dynamic visualization of threats. Visualizations help the user pinpoint where botnet attacks are coming from, identify geographic hotspots for botnet activity, and find out who is at risk for infection.

ENGINEERING CLINIC

AT&T High Dynamic Range Video Quality Analyzer Liaisons: Dr. Peshala Pahalawatta, Douglas Hu ’14, Shamik Maitra ’02 Advisor: Timothy J. Tsai Students: Justin Lauw (TL-S), Owen Morrison (TL-F), Ankoor Apte (S), Nick Draper (S), Tianyi Ma (S), Bradley Phelps (F), Hanna Ching (F), Marisol Guzman (F)

Design and prototype of High Dynamic Range/Wide Color Gamut (HDR/WCG) video analyzer tool that automates the process of detecting four artifacts: contouring, incorrect color space, clip-ping and noise artifacts in video content which may arise during poor conversion from legacy Standard Dynamic Range (SDR) content. Project involves designing artifact detection algorithms to detect the four artifacts in HDR videos and pack-aging the algorithms into an intuitive Graphical User Interface (GUI) for users to adjust algorithm parameters and view results.

ATI Metals Scanning and Image Processing in a 3D Envelope Liaisons: Noah Philips, Ph.D ’03, Gordon Alanko, Ph.D., Gordon Dobbie, Joe Kelly Advisor: Timothy J. Tsai Students: Patrick Scalise (TL-S), Rob Simsiman (TL-F), Peyton Holm, Zach Shattler, Rachel Perley (S), Chance Bisquera (F)

ATI Metals manufactures high performance metal products for the nuclear energy, chemical pro-cessing, and aerospace industries. ATI’s customers require parts fabricated to precise dimensions. The ATI clinic team has integrated computer vision techniques and laser rangefinders into an automat-ed measurement system that generates a 3D model of metal components post-process on the hot roll-ing mill. This system will streamline ATI’s pro-duction by detecting out-of-spec parts earlier in the process, and assist process engineers in im-proving product consistency.

14



BD Biosciences Microfluidic Chip Quality Control System Improvement Liaisons: Atul Madhusudan, Alireza Salmanzadeh, Ph.D., Ruth Sung ’17 Advisor: Leah Mendelson Students: Ramita Kondepudi (TL-F), Marissa Lee (TL-S), Jesus Villegas, Sati Smyth (F), Valerie Kwee (S), Russell Salazar (S)

The 2017-18 BD Biosciences Clinic Team im-proved a quality control (QC) system for an acous-tic microfluidic chip. This chip separates white blood cells, which are of primary interest for the detection of autoimmune disorders, from the rest of blood. The QC system acquires images of flow through the chip and reports the accuracy of blood separation through image processing techniques. The team improved mechanical design and image processing components of this system to reduce manufacturing cost and processing time. Ceremod, Inc. Spot Cooling in the Human Body Liaisons: Dr. Kim Burchiel, Dr. Chris Madden, Dr. Shaun Morrison Advisor: Erik Spjut Students: Aurora Leeson (TL-S), Jasmine Yang (TL-F), Kyla Scott, Brenden Brown (S), Scott Montague (S), Jesus Solano (F), Angela Sun (F)

Ceremod, Inc. is a startup founded at Oregon Health & Science University to foster innovation in medical technology. The Ceremod, Inc. clinic team has modeled and designed a flexible, bio-compatible subsystem to cool a small target region in the human body.The modeling results are being used in feasibility and design studies of the experi-mental and production devices.

City of Hope Raman Spectrometry and Laser Ablation as a Minimally Invasive, Molecularly Guided Therapy for Cancer Liaisons: Dr. Yuman Fong, Dr. Veronica Jones, Dr. Lily Lai, Dr. Dan Schmolze Advisors: Phil Cha, Michael Storrie-Lombardi Students: Ragini Kothari (TL-S), Viviana Bermúdez Reyes (TL-F), Jenny Smith, Youkang Shon, Dominique Mena

The 2017-18 COH-Raman team aimed to reduce the collection time for Raman spectra of breast tissue to 1-3 seconds. This spectral database was analyzed using machine learning algorithms to display the probability of breast cancer. The spec-tral analysis is driven by understanding the bio-chemical markers that are evident in each unique Raman spectrum. The team also investigated Sur-face Enhanced Raman Spectroscopy (SERS) to enhance the Raman spectra. Additionally, the team worked on combining Raman diagnostics with laser ablation treatment. City of Hope Redesigning Wireless Cameras and Smoke Evacuators for Laparoscopic Surgery Liaisons: Dr. Kurt Melstrom, Dr. Yanghee Woo, Dr. Mustafa Raoof, Dr. Yuman Fong Advisor: Angie Lee Students: Lam Huynh (TL-F), Lillian Liang (TL-S), Marisa de Souza (F), Casey Gardner (F), Sabrina Chang (S), Ice Limchantra (S), Elizabeth Poss (S)

The City of Hope Wireless Clinic team is design-ing low-cost and wireless laparoscopic cameras and smoke evacuators. In laparoscopic surgery, smoke is a byproduct that must be evacuated be-cause it impedes visibility and is potentially haz-ardous, ultimately prolonging surgery. In addition to designing the systems to be wireless, the team is incorporating re-circulation of insufflated air into the smoke evacuation system and first-person view (FPV) VR technology into the camera system. With their designs, the team aims to improve visu-alization of the abdominal cavity during laparo-scopic surgery and increase access to laparoscopic surgical tools.

15



New Relic, Inc. Opening the Web Analytics Black Box with Innovations in Machine Learning, Visualization, Animation, and Big Data Liaisons: Bill Kayser, Merlyn Albery-Speyer Advisor: Melissa O’Neill Students: Pratyush Kapur (PM-S), Lee Norgaard (PM-F), Alexandre Trudeau, Edward Carroll

Have you ever wondered how your website is performing? Wouldn’t it be convenient to know if your website is going to experience problems before they happen? The New Relic Clinic Team is exploring new ways to visualize website analyt-ics data, communicate application health, and predict spikes in errors. Using animation, machine learning, and deep learning, the New Relic Clinic Team is developing innovative and unique solu-tions for New Relic’s customers.

Pixar Animation Studios Compressed Texture Access Liaisons: Stephen Friedman ‘03, Wayne Wooten Advisor: Z Sweedyk Students: Doren Lan (PM), Kevin Shimba Bengtsson, Sally Cheng, Nick Gott, Cam Zhou

Pixar Animation Studios’ RenderMan is software used to render all Pixar films and is widely used in the visual effects industry. With RenderMan, Pix-ar's continued aim is to speed up rendering, partic-ularly for textures, which provide fine detail on 3D shapes. The goal of this project is to improve on rendering speed and reduce memory usage by providing higher compression rates for textures on disk and in cache. The clinic team researched data compression algorithms, implemented a promising approach, and evaluated the results.

Proofpoint, Inc. Detecting Phishing Using Deep Learning Networks Liaisons: Thomas Lynam, Mike Morris '97 Advisor: Zach Dodds Students: Daniel Sonner (PM), Nic Trieu, Srinidhi Srinivasan, Amberlee Baugus, Montana Roberts

Proofpoint is a leader at identifying online threats. This project seeks to more accurately classify phishing webpages based on their look, i.e., their visual rendering within a browser. The team de-signed, piloted, and tested software tools to sup-port this investigation, culminating in a machine-learning pipeline that estimates the probability that a page is phishing based on its screen capture.

Rapid7, Inc. Securing Today’s Software-Development Pipelines Liaisons: Corinne Druhan ‘14, James Green, Bryan Trujillo ‘15 Advisor: Elizabeth Sweedyk Students: Zhenghan Zhang, Spencer Michaels, Eric Nguyen, Sarah Sedky

Our project aims to expand the capabilities of Rapid7's security assessment platform by integrat-ing the company’s newly-developed container assessment service into popular continuous inte-gration tools, namely Jenkins, Bamboo, and Teamcity. Anyone developing a container with these tools can add our plugin to the build pipeline to check for vulnerabilities during each build. The plugin generates a detailed assessment report, and the user can configure rules to pass or fail the build depending on various criteria present in the assessment results.

13




Doosan Bobcat Autonomous Attachment Coupling Liaisons: John Pfaff, Jonathan Roehrl Advisor: Christopher Clark Students: Aman Fatehpuria (TL-S), Jessica Lupanow (TL-F), Gabriel Rubin, Darien Joso (F), Kayla Yamada (F), David Olumese (S), Jingnan Shi (S) The Doosan Bobcat clinic team will develop a proof of concept for autonomously driving a com-pact track loader to connect to a bucket attach-ment. Assumed starting conditions include flat, level ground and close alignment of the attach-ment and loader. Sensors, such as LiDAR sensors, will be used to determine the position of the vehi-cle with respect to the bucket. This position will be fed into the control system, which will send de-sired commands to the tracks on the loader.

Eaton Corporation Improved Electrically Operated Ground and Test Device (GTD) Liaisons: Logan Weigle, Koustubh Ashtekar, Brad Leccia, Tyler Holp Advisor: Patrick Little Students: Lupe Carlos (TL-S), Thomas Morgan-Witts (TL-F), Kathryn Belling (F), Morgan Blevins (F), Bella Puentes (S), Matthew Huerta (S), Christopher McElroy (S) Eaton Corp manufactures high voltage circuit breakers and related electrical safety devices. Ground and Test Devices (GTD) are used to ground the line or load side of the power bus bars for maintenance activities. The Eaton Clinic Team has been enlisted to improve design flaws in a GTD that was pulled from the market when updat-ed standards from the Institute of Electrical and Electronics Engineers (IEEE) were released.

FarmX Improving Agricultural Water Efficiency Liaison: Bill Jennings Advisor: David Money Harris Students: Kamau Waller (TL-S), Tess Despres (TL-F), Hill Balliet, Bailey Meyer, Geneva Ecola (S), Sitoë Thiam (F) FarmX, a San Francisco startup, aims to save up to 2% of California’s water by providing precision irrigation management. The HMC FarmX clinic team improved two sensor systems: a weather station, which measures the farm’s local water cycle, and a dendrometer, which monitors tree health. These sensor systems will help FarmX provide better irrigation recommendations and alert farmers when their crops are in danger.

Georg Fischer Signet Wireless Power and Communication for pH Sensor Networks Liaisons: Chuck Gerner, Steve Wells, Ph.D., Kamran Afshari Advisors: Ruye Wang (S), Brian Bryce (F) Students: Isabel Martos-Repath (TL-S), Christine Goins (TL-F), Lauren Hu, David Kwan, Benjamin Iten (S), Kai Kaneshina (F) Georg Fischer Signet is an engineering firm that produces flow and analytical technology. The 2017-2018 Georg Fischer Signet Clinic Team aims to design, build, and test a corrosion-proof method of internally processing and communicating pH and temperature measurements to a remote data collection network. To avoid corrosion, the project implements wireless power through inductive coupling and wireless communication through Bluetooth Low Energy. A LoRa network architec-ture is used to receive data from multiple units.


GKN Aerospace Optical Distortion Mapping System Development Liaisons: Brooke Haueisen, Philip Sturman Advisor: Kash Gokli Students: Wenkai Qin, Sr. (TL-F), Josephine Wong, Sr. (TL-S), Enoch Yeo, Robert Gonzalez (S), Sydney Cozier, (F), Roger Hooper (F) The GKN Aerospace Clinic Team is designing, implementing, and testing a new software system to locate and quantify optical distortions in cockpit windows, fighter jet canopies, and other aircraft transparencies. The software uses modern comput-er vision and data analysis tools to improve upon the industry standard for optical distortion map-ping. GKN Aerospace will use our solution to prevent expensive damage on aircraft canopies and achieve higher product quality.

HP, Inc. SERS Based Cancer Detection Liaisons: Anita Rogacs, Jason Aronoff, Caitlin Dejong, Brian Keefe, Raghuvir Sengupta, Yiming Zuo Advisor: Liz Orwin Students: Michelle Lanternman (TL-F), James Palmer (TL-S), Zunyan Wang, Willis Sanchez-DuPont (S), Missy Spangler (S), Ronak Bhatia (F) Nisha Maheshwari (F) The goal of this project is to explore the predictive diagnostic value of the complex spectra generated by metabolites adsorbed onto the HP Surface Emission Raman Spectroscopy substrates from cancerous and healthy cervical tissue in lab. The project has two primary components. The labora-tory component entails cell culturing and prepara-tion of the samples for data collection. Then when the data is collected, machine learning algorithms will be used to distinguish healthy from cancerous cell by the SERS spectra.

HP, Inc. Study of Carbon Black Dispersion in Polyurethane: Impact on Mechanical and Electrical Properties Liaisons: Bin Huang, Guang Jin Li Advisor: Nancy Lape Students: Sarah Silcox (TL-S), Jacey Coniff (TL-F), Jordan Howard-Jennings (S), Kaitlyn Loop (S), Aliki Sarantopoulos (S), Lisa Mattson (F), Curtis Shin (F), Meily Wu Fung (F) The HP CB Clinic Team studied polyurethane (PU)-carbon black (CB) composites as new elasto-mer materials for Binary Ink Developers (BIDs) on HP Indigo printing presses. The investigation focused on how CB dispersion and loading affect the mechanical and electrical properties of the composites to meet HP’s product functionality and reliability requirements. Techniques such as ten-sile/tear, voltage-current sweeping, and SEM im-aging analysis were used for material characteriza-tion.

Lawrence Livermore National Laboratory Data Fusion for Ubiquitous Nuclear Threat Detection Liaisons: Simon Labov, Brandon Seilhan Advisor: David Harris Students: Sarah Wang (TL-F), Yashas Hegde (TL-S), Emily Lane, Arch Robison, Jordan Abrahams (S) As part of the nuclear terrorism prevention effort at Lawrence Livermore National Laboratory (LLNL), the LLNL Clinic Team is challenged with testing and improving the performance of a “smart” network of pocket-size radiation sensors. This will be done by 1) using non-threat radiation to monitor the calibration of the sensors, 2) config-uring sensors to work together to improve detec-tion sensitivity and confidence, and 3) integrating location information of known radiation sources to reduce false alarm rates. LLNL is operated under Contract DE-AC52-07NA27344.

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Intuitive Surgical Temporal Segmentation of Surgical Suturing Liaisons: Anthony Jarc, Liheng Guo Advisor: Colleen Lewis Students: Juliet Forman, Varsha Kishore (PM), Jane Wu, Hyobin You, Angela Zhao

Intuitive Surgical specializes in minimally inva-sive robot-assisted surgery and they developed the da Vinci surgical system. The objective of our project is to analyze the motion of surgical instru-ments controlled by surgeons and video recording of surgeries by developing computational models that automatically recognize suturing activities during robot-assisted surgery. Our approach com-prises machine learning and neural network archi-tectures. These computational models could then be used to generate advanced analytics such as surgeon performance reports.

Lawrence Livermore National Laboratory Integrating Distributed-Memory Machine Learning into Large-Scale HPC Simulations Liaisons: Cyrus Harrison, Ming Jiang, Brian Gallagher, Matt Larsen Advisor: Christopher Stone Students: Amy Huang (PM), Evan Chrisinger, Jeb Bearer, Katelyn Barnes

Supercomputers provide the computing power for complex physics simulations, but these simula-tions require frequent manual adjustments to pre-vent run-time failures. Machine learning is a po-tential solution for automating this process. The LLNL clinic team is developing a machine learn-ing model appropriate for supercomputers that can learn from the output of physics simulations as they run in real time.

Mercedes-Benz Research & Development North America Augmented and Mixed Reality for the Driver Liaisons: Mark Poguntke, Kavita Saney, Jeff Bertalotto Advisor: Geoff Kuenning Students: Aman Raghuvanshi (PM-S), Julio Medina (PM-F), Drew Summy, Meredith Simpson

The objective of this project is to explore the pos-sibility of using augmented reality (AR) while driving a car. This entails comparing various AR headsets such as the Microsoft Hololens and the Meta 2, and building a functioning prototype that addresses a moving car use-case. The headset comparison involves testing devices in a stationary and moving vehicle, and understanding their re-spective development experiences. Our prototype application attempts to help drivers park more safely and precisely, and serves as a starting point for the Mercedes-Benz team for an extendable AR headset prototyping framework.

NASA AMES Research Center Minimizing Communication in Uncertain Multi-Agent Schedules Liaison: Dr. Jeremy Frank Advisor: Jim Boerkoel Students: Grace Diehl (PM), David Chu, Marina Knittel, Judy Lin, William Lloyd

Our project aims to provide NASA with new scheduling protocols for multi-agent systems (e.g., a robot team). In such systems, scheduling disturb-ances (due to environmental factors or equipment malfunction) may necessitate rescheduling. How-ever, communicating new schedules to all agents can be resource intensive. Reducing rescheduling can improve the performance of multi-agent sys-tems when communication resources are limited. Our team has designed three algorithms to mini-mize rescheduling, trading communication for schedule quality. Further, we developed infrastruc-ture for testing such algorithms.



Amazon Music Amazon Music Graph Liaisons: Dr. Fabian Moerchen, Dr. Gert Lanckriet Advisor: Robert Keller Students: Dan Diemer, Rebekah Justice, Renata Paramastri, Amelia Sheppard (PM), Cha Suaysom

Our project focuses on creating an enhanced infra-structure to enable Amazon's intelligent personal assistant, Alexa, to respond to a broader and deep-er range of queries about music. To this end, we developed an ontology (graphical knowledge structure) for recorded music and prototyped a database-backed, text-based web interface based on the ontology, which demonstrates responses to sample queries. Amazon Prime Now Image-Text Classification to Correct the Amazon PrimeNow Search Experience Liaisons: Igor von Nyssen, Al Vethamuthu Advisor: Yekaterina Kharitonova Students: Alex Mitchell, (PM-S), Zhepei Wang (PM-F), Kofi Sekyi-Appiah, Tina Zhu

Amazon Prime Now wants to automate the pro-cess of identifying products whose images do not match their associated titles on their website. Our team has designed and implemented a solution using various machine learning techniques to auto-matically identify these problematic listings.

Barefoot Networks Traffic Testing in Fully Programmable, 6.4Tbps Networks Liaisons: Remy Chang, Vladimir Gurevich Advisor: Geoff Kuenning Students: E. Taylor Yates (PM), Gus Callaway, M Sangheetha Naidu, Matthew Gee

Barefoot Networks builds high-speed programma-ble networking devices. Our team is building a configurable network traffic tester that can handle up to 6.4Tbps of traffic--enough for every student at the Claremont Colleges to simultaneously stream 200 high-definition movies. The tester will send varying traffic patterns to the device under test, which will immediately forward the packets back to the tester. The tester will analyze packet delay, sequencing, and loss, and will gather and report relevant statistics. Consensus Corporation Algorithmic Fairness: Using Machine Learning To Detect Disparate Impact In Geo-based Risk Modeling Liaisons: Harrison Lynch, Allen Tam, Jing Shen Advisor: Yi-Chieh (Jessica) Wu Students: Daniel King (PM-S), Abby Tisdale (PM-F), Tiffany Fong, Kyra Yee

Consensus Corporation makes point-of-activation software for the sale of mobile phones. This soft-ware includes a risk prediction engine, which predicts whether or not a phone plan will be deac-tivated and the sale deemed fraudulent. The Con-sensus Clinic Team’s project is twofold: (1) im-prove this risk prediction engine by incorporating new features and analyzing different machine learning models and (2) detect unintended bias in the risk prediction engine.

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Meggitt Control Systems Aerospace Wear Coatings Liaisons: Leo Leyanna, Mark Abrams Advisor: Gordon Krauss Students: Kristin Lie (TL-S), Jacob Knego (TL-F), Briana Liu (S), William Teav (S), Alex Ravnik (F), Zach Goland (F), Fernando Fernandez (F) Meggitt Control Systems is an aerospace company that produces a variety of products for extreme environments. The Meggitt clinic team was tasked with researching, testing and characterizing low-cost, environmentally friendly surface treatments to reduce wear on a butterfly bleed-air valve. These valves are used in aircraft engines and must withstand high temperatures while experiencing as little wear as possible over 50,000 cycles.

Millennium Space Systems Iodine Propellant Feed System Liaison: Jason Murray Advisor: Mary Cardenas Students: Richard Ni (TL-F), Alex Echeverria (TL-S), Christopher Strong (F), Marianna Sbordone (F), Kaitlyn Eng (S), Maggie Gelber (S) The team designed and built an iodine feed system which stores solid iodine for a minimum of five years, and sublimates solid iodine to deliver gase-ous iodine at a rate of at least 3 mg/s within 10 minutes in a zero gravity setting. The team validat-ed this proof of concept design through rigorous thermal and structural modeling, in addition to testing the proof of concept for corrosion, leak resistance, flow control, thermal management, and propellant management.

Moog, Inc. Harmonic Gear System Replacement in Space Application Actuator Liaisons: Jason Ro ’99, Armand Asadurian Advisor: Philip D. Cha Students: Luis Viorney (TL-S), Angelica Virrueta (TL-F), Giulia Castleberg (F), Alex Nunes (F), Derrick Chun (S), Jacob Garcia (S), Nate Smith (S) Strain wave gear reduction technology has domi-nated the aerospace rotary transmission industry for half a century due to its simplicity, efficiency, and accuracy. Moog, Inc. has sponsored a Harvey Mudd Clinic team to develop an alternative for use in the sponsor’s satellite actuators. The team’s solution relies on hypocycloidal geometry to achieve a high reduction ratio, zero backlash, and superior performance.

Niagara Bottling Bottling Line Speed Up Project Liaisons: Damon Choate, Ian Song ’17, Alexander Mouschovias Advisor: Ziyad Duron Students: Jose Godinez (TL-S), Ryan Gibbs (TL-F), Arthur Reyes, Priscilla Chu (F), Deji Andrew (F), Rikki Walters (Soph.-S) This project focuses on the P6 gallon bottle blow-molding machine at Niagara’s Corporate plant and finding physical limitations to speed increase. The team is characterizing the dynamics of the ma-chine and finding resonant frequencies at which the machine vibrates due to its operation. By find-ing what is most likely to break first due to vibra-tion, and then strengthening it, the team can safely increase the speed of operation.


“(TL)” Indicates Team Leader “(PM)” Indicates Project Manaz- 19

Project Corsica Pouch for Li Ion Battery Liaisons: Brian Strom, Rossella Giardi Advisor: Albert Dato Students: Charles Van Eijk (TL-S), Michaela Yaman (TL-F), Sean Nguyen, Bryce Murley, Bohan Gao (S), Jakim Johnson (F) Batteries for consumer electronic devices typically consist of a stack of anode and cathode sheets separated by thin membranes, wrapped in a flexi-ble pouch. The standard battery pouch is a lami-nate consisting of metal and plastic layers. Failure in the pouch material can lead to swelling or dan-gerous chemical reactions within the battery. The goal of the Project Corsica clinic project is to design an alternative battery pouch material that improves the safety and reliability of the batteries.

Systron Donner Intertial Embedded Neural Network for Improved Inertial Sensor Calibration and Error Compensation Algorithm Liaisons: Bonnie Gordon ’11, Tony Rios, Emmanuel Quevy Advisor: Tony Bright Students: Nicholas Sakowski (TL-S), Christopher Kotcherha (TL-F), Austin Shin, Eyassu Shimelis, Aaron Lutzger (S) The Systron Donner Inertial (SDI) clinic team has been tasked with designing, writing, and judging the performance of an improved gyroscope bias compensation algorithm. The goal of the project is to reduce rate error by a factor of 10. This goal will be reached with the assistance of statistical analysis and an embedded neural network which will allow the team to explore new causes in gyro-scope bias.

Techmation Project Beluga: Perception System and State Estimation in GPS -Denied Environment Liaisons: Jerry Hsiung ’16, Benjamin Chasnov ’16, Cyrus Huang ’16, Vaibhav Viswanathan ’17 Advisor: Anthony Bright Students: Zayra Lobo (TL-S), Nancy Wei (TL-F), Austin Chun, Dominic Frempong, Evan Chapman (S), John Lee (S) The Techmation Clinic team selected and imple-mented an acoustic beacon and hydrophones to augment an IMU in an Autonomous Underwater Vehicle (AUV). The team then used these sensors for state estimation of the AUV in a GPS-denied environment. A major part of this process was also the development of an Extended Kalman Filter, a state estimation algorithm for sensor integration, and a localization algorithm for the acoustic sys-tem.

Toyota Motor Corporation Development of Energy Recovery Technology for Class 8 Fuel Cell Truck Liaisons: Justin Ward, Tak Yokoo, Advisor: Okitsugu Furuya Students: Duncan Crowley (TL-F), Sean Mahre (TL-S), Mina Berglund, Rilke Griffin, Kim Tran The Toyota clinic project aims to investigate alter-native methods of storing and utilizing energy recovered in the regenerative braking process of Toyota’s hydrogen fuel cell drayage truck. This involves researching and ideating various energy storage solutions and quantifying the amount of energy that can be recovered along several dray-age routes from the Port of Los Angeles to Long Beach.

BIOLOGY/ COMPUTER SCIENCE/MATHEMATICS CLINIC Dart NeuroScience, LLC Network Analysis and Methodology Development for Drug Discovery in Alzheimer’s Disease Liaisons: Philip Cheung ‘96, Qingying Meng, Douglas Fenger Advisor: Eliot Bush Students: Annalise Schweickart, Chloe Chan, Sasha Friedrich, Brendan Murran

The goal of this project, sponsored by Dart Neuro-Science, is to generate potential drug targets relat-ing to memory and neural plasticity, focusing specifically on Alzheimer’s disease. We have developed a novel methodology built on existing network analysis algorithms to identify key genes implicated in Alzheimer’s Disease. This methodol-ogy can be used to identify potential drug targets for Alzheimer’s, and in the future might also be used towards drug discovery for other diseases.

Helix OpCo, LLC Integrating Genetics and Wearable Devices for Discovery Liaisons: Nicole Washington ’99, Anupreet Walia, Scott Burke ’91 Advisor: Lisa Kaczmarczyk Students: Jasmin Rizko (PM-S), Moira Dillon (PM-F), Mahlet Melaku, Crystal Xiang

Helix is a private software platform company for personalized genomic products. The goal of our Clinic project was to integrate sequencing results from Helix and activity tracking via Fitbit, and develop a proof-of-concept to monitor these data in research studies. We built a participant monitor-ing dashboard and conducted IRB-approved hu-man subject studies to demonstrate the dash-board’s capabilities while examining traits related to fitness and sleep.

COMPUTER SCIENCE CLINIC

23andMe Genetic Gameplay: Showcasing 23andMe's Personal-Genetics API Liaison: Arnold De Leon '90 Advisor: Julie Medero Students: Teal Stannard (PM), Giovani Barrios-Arciga, Elise Cassella, Jacob Rosalsky

23andMe is a bioinformatics company whose mission is to help people access, understand, and benefit from the human genome. 23andMe analyz-es DNA to identify specific variations, or alleles, in order to determine ancestry and wellness traits. 23andMe makes much of this information availa-ble to third party developers through a public API. The goal of this project is to create an application which will help encourage other developers to use the public API. Therefore, the application should serve as an example of how to correctly access the public API and securely handle a user’s genetic information. Additionally, we aim to engage users while their data is being analyzed.

Accenture Labs 3D Model Integration for Agile Digital Product Development Liaisons: Robert Dooley, Alex Kass Advisor: Ran Libeskind-Hadas Students: Emily Dorsey (PM), Wenbo (Tracy) Cao, Holly Mitchell, Shailee Samar, Abigail Schantz

3D asset management can pose a significant prob-lem for Augmented and Virtual Reality (AR/VR) applications. The Harvey Mudd Clinic Team is working with Accenture Labs to make AR/VR content management easier by providing a straightforward workflow allowing users to alter their content from within existing tools. The team’s Unity plugin allows inexperienced users to understand the tradeoffs between the visual quality of their assets and app performance, and then manage that tradeoff by customizing their asset’s polygon counts.

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Personalized Projects Day Schedule

Please fill in the empty slots below with the presentations you would like to attend.

Time Event Location

10:30 a.m. Registration and Poster Viewing Platt

Campus Center

1:00 p.m. General Session Shanahan Center

1430

1:30 p.m.

2:00 p.m.

2:30 p.m.

3:00 p.m. - 3:30 p.m.

Break Shanahan Center

Thomas Garrett Plaza

3:30 p.m.

4:00 p.m.

4:30 p.m.

5:15 p.m. - 6:00 p.m.

Poster Reception Platt

Campus Center

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WET PHOSFORS (TM) Development Liaisons: Scott Winslow, Helen Park, Markos Okihisa Advisor: Matthew Spencer Students: Elijah Carbonaro, Kimberly Joly (TL-F), Hamza Khan (TL-S), Trevor Fung (S), Gabriel Quiroz (S), Shiv Seetharaman (S), Lydia Sylla (F), Felipe Borja (F) The WET Clinic team built a fleet of small aquatic robots to perform light shows. The choreography of these shows uses a computer vision system to precisely localize the pods and a multilink Blue-tooth low energy system to communicate with the pods. The fleet of pods uses multi-robot trajectory planning algorithms to move in a choreographed sequence.

ENGINEERING/MATHEMATICS CLINIC Niagara Bottling Transportation Optimization Liaison: Sun Kwok Advisor: Arthur Benjamin Students: Cade Hulse (PM), Anji Malpani, Shreyas Kadaba, Porter Adams , Ryan Haughton (S), Laurel Schy (F) This project has aimed to uncover inefficiencies at Niagara Bottling by taking a more holistic ap-proach to the problem of optimizing transportation processes across Niagara's facilities. The Harvey Mudd team has investigated potential cost-reduction measures through the application of operations research and statistical methods. The end goal of this project has been to optimize total supply chain costs across facilities as well as pro-vide invaluable business insights to Niagara.

ENGINEERING/PHYSICS CLINIC Claremont Locally Grown Power Investigating Hot Spots in Photovoltaic Panels through IdealPV's Patented Controller Liaisons: Kent Kernahan, Devon Hartman Advisors: Qimin Yang, Tom Donnelly (F), Peter Saeta (S), Dick Haskell (Emeritus-S) Students: Jonathan Kupfer (TL-F), Florence Walsh (TL-S), Dallon Asnes, William Lamb, Quentin Barth (F) Claremont Locally Grown Power is a program of CHERP Inc., (Community Home Energy Retrofit Project), a California-based 501(c)(3) non-profit social enterprise, in an exclusive licensing agree-ment to deploy idealPV’s patented solar technolo-gy. The clinic team is assisting CLGP in their goal of outfitting lower-to-middle income households with cheaper, safer, and more efficient solar panels by providing third-party verification and testing of the underlying idealPV technology through lab research, physics-based mathematical modeling, and prototype comparison field studies.

Sandia National Laboratories Measuring the Permittivity of Ferroelectric Nanoparticles in an Epoxy Composite Liaison: Dr. Todd Monson Advisors: Albert Dato, Peter Saeta Students: Andrew Bishop (TL-S), Richard Liu (TL-F), Alejandro Baptista, Lupe MacIntosh, Charles Dawson (F), Benjamin Lehman (S) Barium titanate (BTO) is a ferroelectric material commonly used in capacitors because of its high bulk dielectric constant, which may be even higher in nanoparticle form. We are determining the die-lectric constant of BTO nanoparticles as a function of particle size by measuring composites of BTO nanoparticles in epoxy. We’re using ball-milling alongside surfactants to reduce nanoparticle ag-glomeration, examining particle geometry using scanning electron microscopy, and using finite element analysis to extract the dielectric constant of the nanoparticles.

CLINIC ADVISORY COMMITTEE OF HARVEY MUDD COLLEGE

Industry Members: Tessa Adair ’14, Laserfiche

Paul Anderson, The Aerospace Corporation

Michael Bell, Beckman Coulter, Inc.

Joseph Betser, The Aerospace Corporation

Daniel A. Borton ’90, Amgen Inc.

Bob Butterfield, BD

Carl Carrera ’75/76, The Boeing Company

Frances Ferris ’80, The Boeing Company

Aaron Gable ’12, Google, Inc.

Sharon Kwan ’98, Thermo Fisher Scientific

David Lesyna, Optivus Proton Therapy, Inc.

John Livingston, Tandem Diabetes Care

Hal Lonas, Webroot, Inc.

Craig Snow, Raytheon Missile Systems

College Members: Maria Klawe, President

Dan Macaluso, V ice President, College Advancement

Lisa Sullivan, V ice President, Dean of the Faculty

Andrew Dorantes, VP for Administration & Finance/Treasurer

Scott Martin, Assistant VP for Business Affairs & Assistant Treasurer

Colleen Coxe, Director, Corporate Relations

Zach Dodds, Director, Computer Science Clinic

Kash Gokli, Director, Engineering Clinic

Qimin Yang, Associate Director, Engineering Clinic

Susan Martonosi, Director, Global Clinic

Weiqing Gu, Director, Mathematics Clinic

Peter Saeta, Director, Physics Clinic

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GLOBAL CLINIC

Kounkuey Design Initiative Green Infrastructure Solutions for Urban Flooding in Kibera, Nairobi, Kenya Liaisons: Chelina Odbert, Joe Mulligan, Vera Bukachi Advisor: Ziyad Duron Students: Isabel King (TL-F), Camille Croll (TL-S), Manu Kondapi, Andrea Vasquez (F), Eric Contee II (F), Eliana Goehring (S) Kibera is a large informal settlement in Nairobi, Kenya where annual flash flooding causes signifi-cant health, economic, and structural problems in the community. Current drainage infrastructure consists of informal channels that are not designed to handle the volume of water that falls during large rain events. The objective of this project is to work with the community to develop practical design improvements for the existing drainage channels that can be implemented in Kibera, to improve quality of life for residents.

MATHEMATICS CLINIC EDR Address Detection in Sanborn Maps with Image Processing and OCR Liaisons: Zachary Fisk, Paul Schiffer, Richard White Advisor: Rachel Levy Students: Daniel Zhang, Jeff Carney, Mehdi Drissi, Jordan Haack Our task is to automatically detect and read the handwritten addresses from EDR’s collection of 1.2 million Sanborn maps. Sanborn maps are de-tailed city maps produced regularly between 1880 and 2006. We use various image processing tech-niques to first find the street segments, and then detect the handwritten street names and house numbers. We then run these images through our OCR model, which reliably parses connected characters that are rotated or skewed.

Intel Sports Creating a 3D Sound System for Paired Volumetric Video Liaisons: Cody Gabriel, Peter Sankhagowit, Steven Xing Advisor: Weiqing Gu Students: Daniel Johnson (PM), Daniel Gorelik, Ross Mawhorter, Kyle Suver Intel's TrueView technology can reconstruct three-dimensional video at any location in a stadium using multiple video recordings. However, this system does not extend to audio. This project involves developing an approach to reconstruct game audio at any location based on microphone recordings, to combine with the existing volumet-ric video system. After exploring existing algo-rithms for sound source separation and localiza-tion, we are developing a prototype system called auVVio that extends these techniques to interac-tively reconstruct game sounds in 3D.

Microsoft Bing Correlation and Root Cause Detection in Bing Livesite Metrics Liaisons: Debashish Ghosal, Gautam Dewan Advisor: Talithia Williams Students: Grant Belsterling, Preethi Seshadri, Zhaocheng Yi (PM) Bing is the second most popular search engine in the United States. Bing’s Livesite Engineering team collects system performance metrics to detect incidents (outages, etc.) that negatively impact the end user experience. These incidents result in a loss of ads revenue and users. Identifying root cause of such incidents requires sifting through a lot of metrics and narrowing down the root cause to one or more key metrics. Our clinic team is working to streamline and automate this process by leveraging statistical models and methods.

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Key to Poster Session Layout

1. 23andMe, Inc. 2. Accenture Labs 3. Amazon Music 4. Amazon Prime Now 5. AT&T 6. ATI Metals 7. Barefoot Networks 8. BD Biosciences 9. Ceremod, Inc. 10. City of Hope - Raman 11. City of Hope - Wireless 12. Claremont Locally Grown Power 13. Consensus Corporation 14. Dart Neuroscience 15. Doosan Bobcat 16. Eaton Corporation 17. EDR 18. FarmX 19. Georg Fischer Signet 20. GKN Aerospace 21. Helix OpCo, LLC 22. Hewlett Packard - CB Dispersion 23. Hewlett Packard - SERS 24. Intel Corporation 25. Intuitive Surgical, Inc. 26. Kounkuey Design Initiative 27. Lawrence Livermore National Laboratory - CS 28. Lawrence Livermore National Laboratory - ENG 29. Meggitt Control Systems 30. Mercedes-Benz Research & Development 31. Microsoft Bing 32. Millennium Space Systems 33. Moog, Inc. 34. NASA AMES Research Center 35. New Relic, Inc. 36. Niagara Bottling - ENG 37. Niagara Bottling - ENG/MATH 38. Pixar Animation Studios 39. Project Corsica 40. Proofpoint, Inc. 41. Rapid7, Inc. 42. Sandia National Laboratories 43. Steelcase, Inc. 44. Systron Donner Inertial 45. Techmation 46. Toyota 47. Webroot, Inc. 48. WET

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Time Location

1:30 2:00 2:30 3:30 4:00 4:30 SHAN

Systron Donner Inertial X X X 2460 Embedded Neural Network for Improved Inertial Sensor Calibration and Error Compensation Algorithm Techmation X X X 2460 Project Beluga: Perception System and State Estimation in GPS -Denied Environment Toyota X X X B-450 Development of Energy Recovery Technology for Class 8 Fuel Cell Truck WET X X X 1480 PHOSFORS (TM) Development

ENGINEERING/MATHEMATICS Niagara Bottling, LLC X X X B-442 Transportation Optimization

ENGINEERING/PHYSICS CLINIC Claremont Locally Grown Power X X X B-460 Investigating Hot Spots in Photovoltaic Panels through IdealPV's Patented Controller Sandia National Laboratories X X X B-460 Measuring the Permittivity of Ferroelectric Nanoparticles in an Epoxy Composite

GLOBAL CLINIC Kounkuey Design Initiative X X X B-450 Green Infrastructure Solutions for Urban Flooding in Kibera, Nairobi, Kenya

MATHEMATICS CLINIC EDR, Inc. X X X 2465 Address Detection in Sanborn Maps with Image Processing and OCR Intel Sports X X X B-445 Creating a 3D Sound System for Paired Volumetric Video Microsoft Bing X X X 2465 Correlation and Root Cause Detection in Bing Livesite Metrics

Project

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4

Time Location

1:30 2:00 2:30 3:30 4:00 4:30 SHAN

Rapid7, Inc. X X X 2461 Securing Today’s Software-Development Pipelines Steelcase, Inc. X X X B-470 Wood Veneer Classification and Cataloguing, Mobile Webroot, Inc. X X X 3421 Machine Learning on DNS Data to Discover Security Threats

ENGINEERING CLINIC AT&T X X X 3461 High Dynamic Range Video Quality Analyzer ATI Metals X X X 3461 Scanning and Image Processing in a 3D Envelope BD Biosciences X X X 3465 Microfluidic Chip Quality Control System Improvement Ceremod X X X 2421 Spot Cooling in the Human Body City of Hope X X X 3481 Raman Spectrometry and Laser Ablation as a Minimally Invasive, Molecularly Guided Therapy for Cancer City of Hope X X X 3481 Redesigning Wireless Cameras and Smoke Evacuators for Laparoscopic Surgery Doosan Bobcat X X X 2454 Autonomous Attachment Coupling Eaton Corporation X X X 2454 Improved Electrically Operated Ground and Test Device (GTD) FarmX X X X 2421 Improving Agricultural Water Efficiency Georg Fischer Signet X X X 2475 Wireless Power and Communication for pH Sensor Networks GKN Aerospace X X X 2475 Optical Distortion Mapping System Development HP, Inc. X X X 2440 Study of Carbon Black Dispersion in Polyurethane: Impact on Mechanical and Electrical Properties HP, Inc. X X X 2440 SERS Based Cancer Detection Lawrence Livermore National Laboratory X X X 2425 Data Fusion for Ubiquitous Nuclear Threat Detection Meggitt Control Systems X X X B-480 Aerospace Wear Coatings Millennium Space Systems X X X 1480 Iodine Propellant Feed System Moog, Inc. X X X 3465 Harmonic Gear System Replacement in Space Application Actuator Niagara Bottling, Inc. X X X B-442 Bottling Line Speed Up Project Project Corsica X X X B-454 Pouch for Li Ion Battery

Project

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3

Schedule of Presentations Time Location

1:30 2:00 2:30 3:30 4:00 4:30 SHAN

Project

Building Codes: SHAN = Shanahan Center for Teaching and Learning Note: The “B” in room numbers indicates “Basement Level.”

BIOLOGY/COMPUTER SCIENCE/ MATHEMATICS CLINIC Dart NeuroScience X X X 3425 Network Analysis and Methodology Development for Drug Discovery in Alzheimer’s Disease Helix OpCo, LLC X X X 3421 Integrating Genetics and Wearable Devices for Discovery COMPUTER SCIENCE CLINIC 23andMe X X X 3485 Genetic Gameplay: Showcasing 23andMe's Personal-Genetics API Accenture Labs X X X 2407 3d Model Integration for Agile Digital Product Development Amazon Music X X X B-480 Amazon Music Graph Amazon Prime Now X X X B-454 Image-Text Classification to Correct the Amazon PrimeNow Search Experience Barefoot Networks X X X 2450 Traffic Testing in Fully Programmable, 6.4Tbps Networks Consensus Corporation X X X 2407 Algorithmic Fairness: Using Machine Learning To Detect Disparate Impact In Geo-based Risk Modeling Intuitive Surgical X X X 3485 Temporal Segmentation of Surgical Suturing Lawrence Livermore National Laboratory X X X 2425 Integrating Distributed-Memory Machine Learning into Large-Scale HPC Simulations Mercedes-Benz Research & Development North America X X X 2450 Augmented and Mixed Reality for the Driver NASA AMES Research Center X X X 3425 Minimizing Communication in Uncertain Multi-Agent Schedules New Relic Inc. X X X 2461 Opening the Web Analytics Black Box with Innovations in Machine Learning, Visualization, Animation, and Big Data Pixar Animation Studios X X X B-470 Compressed Texture Access Proofpoint, Inc. X X X B-445 Detecting Phishing Using Deep Learning Networks

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Harvey Mudd College PROJECTS DAY

May 1, 2018

Program 10:30 a.m Registration and Poster Viewing Platt Campus Center 1:00 p.m. General Session Shanahan Center 1430 Welcome - Maria Klawe, President Remarks - Kash Gokli, Director, Engineering Clinic Milestone Awards - Lisa Sullivan, Dean of the Faculty Recipients: City of Hope Dart NeuroScience, LLC Niagara Bottling, LLC Proofpoint, Inc. 1:30 - 3:00 p.m. Project Presentations See Schedule 3:00 - 3:30 p.m. Break Shanahan Center: 1st Floor North Terrace & Thomas Garrett Plaza 3:30 - 5:00 p.m. Project Presentations See Schedule 5:15 - 6:00 p.m. Poster Reception Platt Campus Center Guests, Faculty, and Students

2

Notes:

Projects Day is dedicated to Jack Alford and Mack Gilkeson

for their foresight and wisdom in the creation of the

Harvey Mudd College Clinic Program

Acknowledgments:

To all of the many Alumni and Parents who assist in the recruitment, formulation and conduct of Clinic

projects year to year, and to the Clinic Advisory Com-mittee who provide valuable industry perspective and advice. Your continued support is greatly appreciated.

& To all Harvey Mudd College

Faculty & Staff involved in the preparation of Projects Day

Harvey Mudd’s annual celebration of student achievement includes

Presentation Days (April 30 & May 2, 2018), showcasing senior thesis research and

class projects, as well as Projects Day (May 1, 2018),

showcasing projects in the Clinic program.

Mission Statement:

Harvey Mudd College seeks to educate engineers, scientists, and mathematicians well versed in all of

these areas and in the humanities and the social sciences so that they may assume leadership in their

fields with a clear understanding of the impact of their work on society.

Documents

showcasing projects in the Clinic program. · showcasing projects in the Clinic program. Mission Statement: Harvey Mudd College seeks to educate engineers, scientists, and mathematicians