Grand Challenges (I) Spying on Cells

--Mechanisms of interacting molecular functions leading to new engineering designs of sensing events -- Nano sensors for detecting molecular event in situ in living cells --Algorithms for massive parallel data analysis

-- Engineering structures monitoring, smart materials, faster computing, improved agricultural and industrial biological species

Forward engineering & design of biological components & systems --Two way interfaces of living tissue-machine & programmed tissue generation/repair lead to integration of biological & engineered parts for construction of programmed living systems --New, superior chemicals, materials, systems, and computational approaches developed thru integration of biological & engineering paradigms integration

Grand Challenges (II) Complex engineering systems enabled by biologically-inspired principles --How bio- systems acquire rich sensory info about their environment and to integrate it

with actuator output to achieve their living goals ---Design of bio-inspired sensing/actuation systems that are adaptive, efficient, robust,

sustainable, multi-functional, scalable and applicable ---Realization of revolutionary hybrid engineering devices

Complexity to Simplicity: Sensor informatics guided by life --How living organisms sense and integrate environmental cues for concerted outcome --Emulate bio info processing for new design paradigms in monitoring, info fusion,

communication and computing --Vast increment of spatial & temporal fidelity --Hierarchical decision making in sensor rich environment --Revolutionize abilities for assessing and controlling of complex systems

Multi-scale Biodigital Hybrid Computing --Computing paradigm for information exchange between biological and electronic

systems --Assembling complex biomolecular networked systems --Impacts: in vivo computing for nano-medicine, new cooperative parallel computing

models, biodigital computers, nanoscale assembly of circuits

Sensor Informatics Guided by LifeObjective

• Understand how living organisms sense & integrate environmental cues for a concerted outcome.

• Emulate biological information processing for new design paradigms in monitoring, communication, computing and information fusion.

• Vastly increase spatial and temporal fidelity with which we instrument and analyze the physical world.

• Develop transformative strategies for hierarchical decision making in sensor rich environments.

• Revolutionize abilities for assessing and controlling complex systems.

Technical Challenges• Real-time monitoring and actuation of cellular signal

transduction processes and communication proceses amongst organisms.

• Data mining in massively parallel biological systems.• Understanding biological systems algorithmic

techniques for rapidly and robustly handling rich, noisy data, anomaly detection, adaptation and resilience.

• Statistical/stochastic modeling of biological information detection, processing and actuation methods.

• Adapting relevant decision/control/coordination algorithms, in-network data aggregation and fault-tolerance schemes and sensor-actuator and visualization systems to complex engineered systems.

Impact & Payoffs• Revolutionary understanding of biological

mechanisms of communication and information fusion. at cellular and complex-system level.

• Introduction of new concepts for high performance sensors that transduce, process, filter and amplify signals and enable faster computing and decision making.

• New paradigms for sensor array design, prioriti-zation of information to collect and process, and for decision making and control methods.

• Scalable methods for data discovery and analysis, and decision making in sensor rich environments.

Spying on cells: Understanding cell mechanisms and creating new paradigms for characterizing and modeling complex systems

Technical Challenges Simultaneous monitoring of multiple cellular

events in real time in living cells Design and build instruments for multi-

dimensional simultaneous data gathering from within and around living cells

Develop techniques to analyze massively parallel data sets

Model multiple interacting events in heterogeneous space

Objectives Mechanisms of molecular functions in their

cellular and intercellular context Nanoscale sensors for detecting and reporting

molecular events in situ in the living cell Understanding complex heterogeneous

material structure in the context of function Algorithms for massively parallel data analysis Models of the complex and integrated

mechanisms of interacting cell functionsImpact and Payoffs

Understanding mechanisms of cell function at the molecular level and how they are integrated for cell responses

New engineering designs for sensing events in multiple time and length scales

Continuous monitoring of engineered structures to detect early critical damage

smarter materials faster computing personalized health monitoring improved agricultural and industrial

biological species

Hierarchical Organization of Biologyfor BioSensing and BioActuation

Objectives.

• Understand the principles governing the growth of hierarchical versatile functional biological structures

• utilize the biological principles in biosensing and bioactuation applications

Transformative Nature. • drastic shift in design and fabrication of sensors and actuators ― new concepts and new paradigms.• potential for a completely new tool box to study the complex nature of biological materials, particularly their irregular, highly compliant, and hierarchical nature.

Impacts. • Deeper understanding of the complex nature of biological systems• potential to analyze and fabricate much more complex, integrated, multifunctional sensing and actuating systems• platforms for synergistic

Interdisciplinary Nature. characterize the hierarchical structuresanalyze the principles leading to multi- functionalitiesdesign and fabricate hierarchical structured sensors

Objective• Understand the fundamental principles by which

biological systems acquire rich and varied sensory information about their environments, and how they integrate this information with versatile actuator output to achieve their goals while minimizing energy, materials, and computation requirements.

• Exploit this understanding to enable the conceptualization, design and development of biologically-inspired sensing/actuation systems that are transformative in their functionality, applicability, efficiency, robustness, sustainability, and scalability.

Technical Challenges• Understand how, what, and why living organisms

sense, and also how they use this rich and complex information to achieve their goals.

• Understand complex materials and their shapes and surfaces in the context of the system in which they function.

• Develop new techniques for modeling massively parallel systems.

• Develop new algorithmic techniques for rapidly and robustly handling rich but noisy data.

• Develop novel sensors, actuators, materials and structures, and facilitate the design process leading to their integration into functioning devices.

Impact & Payoffs• Fundamental advancements in integrated

sensing and actuation, mathematical modeling of complex systems, and biological understanding of organism function.

• Enable the realization of revolutionary, hybrid engineering devices.

• Drive technological and economical development, and address pressing societal needs in health, environment, security, etc

• Break down traditional boundaries between disciplines, and stimulate new educational and research frontiers.

Grand Challenge Complex Engineering Systems Enabled by Biologically-Inspired

Universally-Applicable Organizational Principles

Forward Engineering and Design of Biological Components and Systems

Impact

Vision

Technical Approach

Objective:• Construct programmed living systems by synthesis and

systems-level integration of biological and engineered parts that do sensing, actuation, and computation

• Build hybrid mechano/electronic/living systems that perform desired output / function

• Integrate engineering and biological paradigms to develop new chemicals, materials, systems, and computational approaches superior to current technologies

Impact:• Increased capacity to manipulate and program biological

systems will address major societal challenges (environment, energy, sustainability, health and medicine)

• Development of engineering frameworks (CAD for biology, new programming languages) and general tool sets for building complex biological systems with reliable and robust behavior

• Integrated educational programs that address broader issues such as risks and ethics

Technical Approach:• Design and synthesis of modular and programmable parts that

perform sensing, actuation, and computation in biological systems

• Develop complete physical models of cells and systems that include regulatory, signaling, mechanical, and biochemical properties of sensing and actuation

• Integration of biological and engineered systems to enhance understanding of biology

• Engineering frameworks for design and construction of complex biological systems

• Modeling and simulation tools that lead to new bio-programming languages

Programmed tissue generation / repair

Harvesting and storing solar energy

Sustainable / green construction materials

Vision:

Living tissue-machine two-way interfaces

Multi-scale Biodigital Hybrid Computing

Objective• Develop multi-scale biodigital hybrid

computing paradigm.• Ability to exchange information between

biological and electronic systems.• Methods for assembling complex

biomolecular computing networked systems.

Technical Problems• Digitalization of biochemical signals to interface

with electronic systems (Bio, Eng, MPS, CISE).

• Understanding biological computational processes for cooperative and hierarchical communication, computing and control (Bio, CISE).

• New programming models, languages, verification methods for biodigital computer systems (CISE, Bio).

• Error correction and robustness in hybrid biodigital computing systems (CISE, Bio, MPS).

Impact• In vivo computing for nano-mediciine.

• New models for cooperative parallel computing methods.

• Biodigital computers, integrating DNA computers, silicon computers and biological systems.

• Enable directed nanoscale assembly of circuits.