1. 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

2. 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

3. Sensor Informatics Guided by Life Objective 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.

4. 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 functions Impact 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

5. Hierarchical Organization of Biology for 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 structures analyze the principles leading to multi- functionalities design and fabricate hierarchical structured sensors

6. 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

7. 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

8. 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.