Shreya Rajpal Resume

7/25/2019 Shreya Rajpal Resume

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Shreya Rajpal

+91-9999805820 shreya.rajpal@gmail.com

Education

Bachelor of Technology  - Production and Industrial Engineering (8.225/10.0) Expected: May 2016Minor  - Computer Science (Coursework GPA - 9.235/10.0)Indian Institute of Technology, Delhi

Publications

[1] Shreya Rajpal, Karan Goel, Mausam. POMDP-Based Worker Pool Selection for Crowdsourcing.CrowdML Workshop, International Conference on Machine Learning (ICML).   Lille, France. July 2015.

Relevant Coursework

Computer Science : Introduction to Computer Science [topped among 350+ students], Data Structures,

Analysis and Design of Algorithms, Artificial Intelligence, Probabilistic Graphical ModelsElectrical Engineering : Digital Electronics (+ Lab)Industrial Engineering : Probability and Stochastic Processes, Operations Research

Research Experience

Cost-Quality-Time Optimization in Crowdsourcing [report   |  slides]with  Prof. Mausam (IIT-Delhi)   July 2015 - Present

•  Modeled the optimization of a 3-variable reward function, in a multi-agent setting using Markov Deci-sion Processes (MDPs). Agents make online decisions for task pricing, prioritization and termination.

•   Utilized a Thinned Non-Homogenous Poisson Process to model worker arrivals to the marketplace,with a Discrete Choice Model to estimate task selection.

•   Exploring the application of Decentralized Partially Observable MDPs (DEC-POMDPs) to this paradigm.

Modeling Human Perception for Discovering Consensus Rankings [report]with   Prof. Aditya Parameswaran (UIUC), Collaborator: Prof. David Forsyth (UIUC)   July 2015 - Present

•   Proved NP-Hardness for the problem of discovering multiple latent consensus rankings when humanssort a set of items, by reducing from the Minimum Clique Cover problem in graphs.

•  Conducted experiments on Amazon MTurk to study perception of depth with ambiguous visual cues,by adapting Cornell’s OpenSurfaces interface to our application, and deploying it on Amazon EC2.

•   Developing a Conditional Random Field model to classify workers based on similarity of perception.

Worker Pool Selection in Crowdsourcing [1] [paper  |  poster   |  slides]with  Prof. Mausam (IIT-Delhi)   January 2015 - May 2015

•   Developed an online task routing algorithm using Partially Observable MDPs (POMDPs), with a

novel approach that leverages an organization of workers based on their qualifications. The modelsystematically trades off push and pull crowdsourced approaches in a single, theoretical framework.

•  Experiments in simulation and on real Amazon MTurk data demonstrated improvement over baselines.•   Accepted at the International Conference on Machine Learning’s CrowdML workshop.

Teaching Experience

Artificial Intelligence, Undergraduate and Graduate-Bridge Course [website]with  Prof. Mausam (IIT-Delhi)   July 2015 - Present

•  Developed, implemented and graded 2 assignments on developing AI game bots.•  Taught 125+ students concepts in MDPs and POMDPs after creating problem sets for them.•   Undertook several one-on-one teaching sessions for a student with a hearing disability.

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Internships

Algorithm Performance Metrics for Foreign Exchange Currenciesat Deutsche Bank Center, Mumbai, India    May 2015 - July 2015

•   Developed a performance metric for High Frequency Trading algorithms and utilized this metric toanalyze the performance of frequently used algorithms and find issues with inefficient algorithms.

•  Developed a heuristic for selecting optimal HFT algorithm given trade volume, using the metric.•   Developed an efficient querying scheme using graph pruning algorithms for a massive dataset.

Outlier Detection in Large Datasetsat LIRIS Lab, University of Lyon-1, France    December 2013

•  Implemented a Principal Component Analysis based algorithm for anomaly detection, and analyzedits performance with respect to the state-of-the-art.

Projects

OCR Word Prediction using Conditional Random Fields (CRFs) [report   |  code 1   |  code 2]

•  Performed Variable Elimination on a CRF and used the Min-Fill heuristic to generate a Clique Tree.•   Implemented Sum-Product Message Passing, Gibbs Sampling and Loopy Belief Propagation to find

the Max-Marginal Assignment and also implemented their Most Probable Explanation counterparts.•   Increased model complexity by increasing CRF connectivity to compare algorithm performance.

POS and NER Tagging for Tweets using MALLET [code]

•   Engineered features to improve POS and NER tagging in a CRF model. Grouped similar soundingwords via metaphone similarity to tweets and added Twitter specific features.

•  Studied CRF performance by performing an ablation study by adding features.

Viterbi Algorithm for Genomic Sequences [code]

•  Implemented a Hidden Markov Model to identify CpG islands in Genomic Sequences. Learned modelparameters using Maximum-Likelihood estimation and used the Viterbi Algorithm for prediction.

A Review of Convolutional Codes and the Viterbi Algorithm [paper]

•  Performed a literature survey on the Viterbi Algorithm and its faster, less optimal extensions.•   Compared two popular hardware implementation of the Viterbi algorithm.

AI for Connect M-N-K

•   Created two game bots using Minimax with Alpha-Beta pruning, and Monte Carlo Tree Search.•  Enabled flexible board configuration handling for a general Connect-4 game board.

Skills

Languages:  C/C++, Python, SQL, JavascriptSoftware:  MATLAB, AutoCAD, LATEX

Development:  HTML, CSS, JQuery, Ajax

Activities

•  Institute journalist for the Board of Student Publications.•   Performed stage and street theater for inter-college events.•   Regularly act as master of ceremony for institute-wide events.