Seminars: Fall 2016

Date      Speaker From Title
Sep 7 Atena Darvishi New York Power Authority Monitoring of single and multiple line outages with synchrophasors in areas of the power system
Sep 15 Carlos Fernandez-Granda New York University Demixing Sines and Spikes: Spectral Super-resolution in the Presence of Outliers
Sep 16 Maria Teresa Outeiro Polytechnic Institute of Coimbra, Portugal Grid Integration of Renewable Energy Sources and the Way Portugal Deals With It
Sep 22 Antonio Miele Politecnico di Milano, Milano, Italy Lifetime Reliability Estimation and Management In Multi-core Systems
Sep 28 Roberto Padovani Qualcomm Jack Keil Wolf Lecture Series: The Road To 5G
Oct 6 Bipin Rajendran New Jersey Institute of Technology Intelligent Computing – Algorithms, Devices & Systems
Oct 13 Daoyi Dong University of New South Wales, Australia Efficient Estimation, Identification and Fault-tolerant Filtering in Quantum Systems
Oct 18 Ivana Kockar University of Strathclyde, UK Integration of DERs: New operation and planning tools and their applications
Oct 27 Danielle Bassett University of Pennsylvania Perturbation and Control of Human Brain Network Dynamics
Nov 10 Xiang Li Fudan University Towards Identifying and Predicting Spatial Epidemics of Complex Metapopulation Networks
Dec 1 Andras Gyorgy UC Berkeley From Hacking Towards Engineering Gene Circuits - an Emerging Systems Theory


Monitoring of single and multiple line outages with synchrophasors in areas of the power system

Speaker:Atena Darvishi, New York Power Authority
Time: 11:00 am - 12:00 pm Sep 7, 2016
Location: LC433, 5 MetroTech Center, Brooklyn, NY

When power grids are heavily stressed with a bulk power transfer, it is useful to have a fast indication of the increased stress when multiple line outages occur. Reducing the bulk power transfer when the outages are severe could forestall further cascading of the outages. Phasor measurement units (PMUs) are vital elements for monitoring and control of these heavily stressed power systems. This work presents a new approach to implement and utilize PMU information to monitor operational transfer capability and limits based on voltage phasor angles with respect to thermal limits of transmission lines. This work demonstrates an algorithm to obtain thresholds based on the angle and then quickly deploy PMU data to monitor stress changes due to single and multiple outages in real time to send fast notification of emergency situations. Area angle uses the topology and the synchronized measurements of angles across an area of power system to measure stress caused by outages within the area. The proposed algorithm is easy, quick and computationally suitable for real systems to capture bulk stress caused by outages and also identify local stress.

This presentation illustrates the idea of area angle in a Japanese test system and then explores the choice of the border buses. It further investigates the relation between area angle to area susceptance and supports the findings in two areas of the Western North American power system. Finally, this presentation develops a procedure to determine thresholds for the area angle that relate to the maximum power that can be transferred through the area until a line limit is reached. The algorithm determines the area angle thresholds offline and then in real time monitoring the area angle and comparing it to the thresholds after multiple outages determines the urgency (or not) of actions to reduce the bulk transfer of power through the area. The procedure also identifies exceptional cases in which separate actions to resolve local power distribution problems are needed. The findings are supported by testing on a 1553 bus reduced model of the Western interconnection power system.

About the Speaker: Atena is currently working in research and development department at New York Power Authority (NYPA). She is responsible for developing innovative techniques for enhancing NYPA/New York State generation and transmission systems. Research and development group in NYPA is collaborating with external research and development organizations, academia, vendors, and consultants to develop, implement, test, and evaluate new tools and techniques for NYPA/New York State system.

Atena received her Ph.D. degree in power system from Iowa State University in August 2015 under the supervision of Professor Ian Dobson. She is a motivated power system engineering professional with more than 6 years of research and work experience and has been involved in various research projects including wide area monitoring and control using phasor measurement units, outage detection and management using phasor measurement units, power market especially demand side management, congestion management in transmission systems, analysis of reserve effect on congestion management, day-ahead and real-time market operation (DAM & RTM).

Demixing Sines and Spikes: Spectral Super-resolution in the Presence of Outliers

Speaker:Carlos Fernandez-Granda, New York University
Time: 11:00 am - 12:00 pm Sep 15, 2016
Location: 2MTC, 10th floor, Room 10.099, Brooklyn, NY

In this talk we consider the problem of super-resolving the line spectrum of a multisinusoidal signal from a finite number of samples, some of which may be completely corrupted. Measurements of this form can be modeled as an additive mixture of a sinusoidal and a sparse component. We propose to demix the two components and super-resolve the spectrum of the multisinusoidal signal by solving a convex program. Our main theoretical result is that-- up to logarithmic factors-- this approach is guaranteed to be successful with high probability for a number of spectral lines that is linear in the number of measurements, even if a constant fraction of the data are outliers. We show that the method can be implemented via semidefinite programming and explain how to adapt it in the presence of dense perturbations, as well as exploring its connection to atomic-norm denoising. In addition, we propose a fast greedy demixing method which provides good empirical results when coupled with a local nonconvex-optimization step.

About the Speaker: Carlos Fernandez-Granda received engineering degrees from Universidad Politecnica de Madrid and Ecole des Mines in Paris and an M. Sc. from Ecole Normale Superieure de Cachan. He then obtained a Ph. D. from Stanford University, where he studied the problem of super-resolving signals from blurred data using methods based on convex optimization. Before joining Courant, he spent a year at Google, where he worked on techniques to process neural data. His research focuses on developing and analyzing optimization-based methods to tackle inverse problems that arise in applications such as neuroscience, computer vision and medical imaging.

Grid Integration of Renewable Energy Sources and the Way Portugal Deals With It

Speaker:Maria Teresa Outeiro, Polytechnic Institute of Coimbra, Portugal
Time: 11:00 am - 12:00 pm Sep 16, 2016
Location: 2MTC, 10th floor, Room 10.099, Brooklyn, NY

The integration of renewable energy sources (RES) such as; Hydro power, Wind power (Onshore and Offshore), PV, Wave, Tidal and Biomass in the electric distribution and transmission networks in Portugal and the way Portugal deals with it is the main focus of the seminar. The seminar starts with an overview of the actual energy sector in Portugal, presenting the various RES, the investments that have been and are being made in the sector in order to meet the targets fixed by the European Strategy for Energy which are substantiated by the European Orientation of the "20-20-20" of Horizon 2020. Considering that the power electronics is key technology for RES grid integration, the seminar will analyze various configurations and topologies of converters that allow connecting RES to the electric grid as well as the no less important role of the Energy Storage Technologies in the process. The impacts of integrating the RES into the electric grid and the way Portugal deals with them are briefly analyzed. The seminar closes with an overview of the future directions of the energy sector in Portugal in particular with the integration of electric mobility and advancements in the smart grids. The various investments done and in progress in these areas are briefly presented.

About the Speaker: Maria Teresa Outeiro (IEEE-IES Member) received the PhD degree in Electrical and Computer Engineering with honors from the Faculty of Engineering of Porto University, Portugal in 2012. She is an Adjunct Professor at Polytechnic Institute of Coimbra, (ISEC/IPC), Portugal, and Senior Research Member of the Research Center for Systems and Technologies-SYSTEC, University of Porto, Portugal. M. T. Outeiro has co-organized and co-chaired special session “High-Performance Power Supplies” at IECON'13, special session “Power Supplies for Special Applications” at IECON'14, and special session “Resonant Power Converter Topologies, Control Techniques and Applications” at IECON'15. She presented a tutorial: “Resonant Power Converter Topologies, Control Techniques and Applications” at IECON'15. Her scientific interests include: soft-switching and resonant power converters, new topologies of power converters and control techniques, optimization, wired and wireless charging of electric vehicles. M. T. Outeiro is a member of editorial boards and technical committees of several international journals and conferences.

Lifetime Reliability Estimation and Management In Multi-core Systems

Speaker:Antonio Miele, Politecnico di Milano, Milano, Italy
Time: 11:00 am - 12:00 pm Sep 22, 2016
Location: 2MTC, 9 floor, Room 9.101, Brooklyn, NY

Nowadays, lifetime reliability has assumed a role of primary driver in the design of modern multi-core systems, due to the aggressive CMOS technology downscaling that has caused an acceleration in device aging and wear-out phenomena. At the same time, complexity of modern systems has pushed the focus of the design activities at system level. At that level, designers face with two main issues: 1) the estimation of system lifetime, and 2) the definition of reliability-aware resource management strategies.

As a matter of fact, the various design and management choices (such as mapping, scheduling, use of spare units,..) as well as the high variability of the working condition the system will face with (e.g. variably workload or premature failures of a subset of the cores) have a considerable effect on the overall system reliability. Therefore, the definition of an accurate and flexible model for the the estimation of the lifetime reliability of a multi-core system is mandatory.

At the same time, the availability of numerous, possibly heterogeneous, processing resources in multi-core systems allows one to exploit them not only to optimize performance and/or power consumption but also to prolong the system lifetime. Therefore, classical runtime resource management strategies should be enhanced in order to become reliability-aware. The overall goal is to pursue the improvement of lifetime reliability while optimizing for performance/power.

The aim of this talk is to present an overview of the research activities carried out in the last two years in the area of the estimation and the improvement of lifetime reliability in multi-core systems.

About the Speaker: Antonio Miele is an assistant professor at the Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milano, Italy. He received his Ph.D. in Information Technology in 2010 from the same institution where he worked as postdoc research assistant from 2010 to 2014. Previously, he received the M.Sc. and the B.Sc. in Computer Science Engineering from Politecnico di Milano in 2006 and 2003 respectively. In 2006 he also got the M.Sc. in Computer Science at the University of Illinois at Chicago, USA.

His main research interests are related to the definition of design and analysis methodologies for embedded systems, in particular focusing fault tolerance and reliability issues, runtime resource management in heterogeneous multi-/many-core systems and FPGA-based systems design.

Dr. Miele is co-author of more than 50 scientific publications in international conference proceedings and selected journals. Moreover, he is program co-chair of DFT 2016 and guest editor for a special issue of the IEEE Transactions on Emerging Topics in Computing in 2016 and is part of the technical program committees of various conferences (e.g. DATE, DFT, FPL, ARC, DSD).

Jack Keil Wolf Lecture Series: The Road To 5G

Speaker:Roberto Padovani, Qualcomm
Time: 11:00 am - 12:30 pm Sep 28, 2016
Location: The MakerSpace EventSpace, 6 Metrotech Center, Brooklyn, NY

The standardization efforts for next generation cellular technology or 5G is now at full throttle with early commercial deployments expected for 2020. I will present Qualcomm's view and efforts on 5G as we approach the final stretch of yet another generational cycle.

About the Speaker: Dr. Roberto Padovani is Executive Vice President and Fellow at Qualcomm Technologies, Inc. He joined Qualcomm in 1986 and served as the company's Chief Technology Officer from 2002 to 2011.

During his tenure at Qualcomm, Dr. Padovani has been involved in the research and development of digital communication systems with particular emphasis on Code Division Multiple Access (CDMA) wireless technology systems. He was involved in the initial design, development, and standardization of IS-95 CDMA systems. His research and inventions in this field have led to the worldwide standardization and commercialization of CDMA technology for second- and third-generation cellular systems. He has also led the design and development of CDMA2000 1xEV-DO, an IP-based, high-speed wide-area wireless data technology, which led to the deployment of high speed data services on third generation wireless networks across the globe.

Dr. Padovani holds more than 80 patents on wireless systems. He has published numerous technical papers in the digital communications field and was the co-recipient of the 1991 IEEE Vehicular Technology Society Best Paper Award for a fundamental paper on the capacity of CDMA cellular systems. In 2009 he received the IEEE Eric. E. Sumner Award “for pioneering innovations in wireless communications, particularly to the evolution of CDMA for wireless broadband data,” and in 2016 the IEEE Alexander Graham Bell Medal “For innovations enabling efficient, wideband, wireless access to the Internet, that is central to all third-generation cellular networks.” He was elected to the National Academy of Engineering in 2006.

Dr. Padovani received a laureate degree from the University of Padova, Italy and MS and Ph.D. degrees from the University of Massachusetts, Amherst, all in electrical and computer engineering. He is an IEEE Fellow and an Affiliate Professor in the Electrical and Computer Engineering Department at the University of California, San Diego.

Intelligent Computing – Algorithms, Devices & Systems

Speaker:Bipin Rajendran, New Jersey Institute of Technology
Time: 11:00 am - 12:00 pm Oct 6, 2016
Location: 2MTC, 10th floor, Room 10.099, Brooklyn, NY

The new iPhone processor has more than 3 billion transistors, and can perform more than 300 GFLOPS (300 billion floating point operations per second), consuming less than 10 Watts. The human brain, with more than 100 billion neurons, is estimated to be capable of performing an astounding 20 Million GFLOPS equivalent, while consuming a mere 20 Watts ! Clearly, nature’s methods and engines for information processing are far superior to the best man-made systems today.

How does computation and learning emerge in neural networks that communicate using spikes through adaptive synapses? Is it possible to build computing systems that mimic the cognitive abilities of the brain, at the size and scale of biology? These questions need to be answered to realize the long-standing goal of reverse engineering the brain and develop the next generation of information processing systems. In this talk, I will discuss some new algorithms, devices and systems that we have engineered in our laboratory, inspired by the brain.

About the Speaker: Bipin Rajendran received a B. Tech degree from I.I.T. Kharagpur, in 2000, and M.S. and Ph.D. degrees in Electrical Engineering from Stanford University, in 2003 and 2006, respectively. He was a Master Inventor and Research Staff Member at IBM T. J. Watson Research Center in New York during 2006-’12 and a faculty member in the Electrical Engineering Department at I.I.T. Bombay during 2012-’15. His research focuses on building algorithms, devices and systems for brain-inspired computing. He has authored over 60 papers in peer-reviewed journals and conferences, and has been issued 55 U.S. patents. He is currently an Associate Professor in the Department of Electrical & Computer Engineering at New Jersey Institute of Technology.

Efficient Estimation, Identification and Fault-tolerant Filtering in Quantum Systems

Speaker:Daoyi Dong, University of New South Wales, Australia
Time: Oct 13, 2016
Location: 2MTC, 10th floor, Room 10.099, Brooklyn, NY

In this talk, I will introduce several results on quantum state estimation, Hamiltonian identification and fault-tolerant quantum filtering with my collaborators. First, a simple yet efficient method of linear regression estimation (LRE) is presented for quantum state tomography. Numerical examples show that LRE is much faster than maximum-likelihood estimation for quantum state tomography. Based on LRE, we present a recursively adaptive quantum state tomography (RAQST) protocol for finite dimensional quantum systems and experimentally implement the adaptive tomography protocol on two-qubit systems. The computational capability of full quantum state tomography is pushed forward to reconstruct a 14-qubit state with a run time of only 3.35 hours using the LRE algorithm. Second, we present a two-step optimization quantum Hamiltonian identification algorithm, characterize its computational complexity and establish an error upper bound. Lastly, we analyse how to determine the fault tolerant quantum filter and fault detection equation for a class of open quantum systems coupled to a laser field that is subject to stochastic faults. In particular, we propose a quantum-classical Bayesian inference method based on the definition of a so-called quantum-classical conditional expectation.

About the Speaker: Daoyi Dong received a B.E. degree in automatic control and a Ph.D. degree in engineering from the University of Science and Technology of China, Hefei, China, in 2001 and 2006, respectively. Currently, he is a Senior Lecturer at the University of New South Wales, Canberra, Australia, and a visiting scholar at Princeton University, USA. He was with the Institute of Systems Science, Chinese Academy of Sciences and with the Institute of Cyber-Systems and Control, Zhejiang University. He had visiting positions at RIKEN, Wako-Shi, Japan and The University of Hong Kong, Hong Kong. His research interests include quantum control, multiagent systems and intelligent control. Dr. Dong is a recipient of an International Collaboration Award and an Australian Post-Doctoral Fellowship from the Australian Research Council. He is also a co-recipient of Guan Zhao-Zhi Award at The 34th Chinese Control Conference and the Best Theory Paper Award at The 11th World Congress on Intelligent Control and Automation (WCICA). He serves as an Associate Editor of IEEE Transactions on Neural Networks and Learning Systems.

Integration of DERs: New operation and planning tools and their applications

Speaker:Ivana Kockar, University of Strathclyde, UK
Time: 11:00 am - 12:00 pm Oct 18, 2016
Location: LC433, 5 MetroTech Center, Brooklyn, NY

The distribution level of a future power system network will include various types of active dynamic devices, such as distributed generators based on solar and wind, batteries, deferrable loads, curtailable loads, and electric vehicles, whose control and scheduling may amount to a very complex power management problem related not only to technical and economic aspects of system operation, but also to adjustments in human responses and participation. Therefore, integration of new technologies in power system networks brings new operational and planning challenges, which include (i) changes in nature of distribution networks that are becoming more active due to connections of Distributed Energy Resources (DERs); (ii) stochastic nature of DERs; (iii) intertemporal constraints imposed by some technologies such as storage, electric vehicles, and demand response; (iv) changes at transmission and distribution network interfaces due to DERs connections; (v) provision of ancillary services of DER connected at the distribution network to transmission and/or distribution system operators.

This presentation will discuss above issues related to integration of DERs and present some of the new tools and solutions that can help system operators and planners integrate these new technologies. In particular, it will look at operational scheduling tool, with examples of its implementation coming from recent industrial/pilot projects.

About the Speaker: Ivana Kockar received her PhD degree from McGill University, Montreal, Canada. Currently, she is a Senior Lecturer within the Institute for Energy and Environment at the University of Strathclyde, Glasgow, UK. Her research is in the area of power system operation, planning and economics, including new centralised and decentralised tools for the integration of Distributed Energy Resources as well as interactions between TSOs and DSOs. Her work also includes projects funded by industry, looking into energy solution on Shetland Islands (funded by Scottish and Southern Energy Power Networks) and in Scottish Borders (funded by Scottish Power Energy Networks). Ivana is the past chair of the IEEE PES Computing and Analytical Methods Subcommittee (CAMS).

Perturbation and Control of Human Brain Network Dynamics

Speaker:Danielle S. Bassett, University of Pennsylvania
Time: 11:00 am - 12:00 pm Oct 27, 2016
Location: 2MTC, 10th floor, Room 10.099, Brooklyn, NY

The human brain is a complex organ characterized by heterogeneous patterns of interconnections. New non-invasive imaging techniques now allow for these patterns to be carefully and comprehensively mapped in individual humans, paving the way for a better understanding of how wiring supports our thought processes. While a large body of work now focuses on descriptive statistics to characterize these wiring patterns, a critical open question lies in how the organization of these networks constrains the potential repertoire of brain dynamics. In this talk, I will describe an approach for understanding how perturbations to brain dynamics propagate through complex writing patterns, driving the brain into new states of activity. Drawing on a range of disciplinary tools – from graph theory to network control theory and optimization – I will identify control points in brain networks, characterize trajectories of brain activity states following perturbation to those points, and propose a mechanism for how network control evolves in our brains as we grow from children into adults. Finally, I will describe how these computational tools and approaches can be used to better understand how the brain controls its own dynamics (and we in turn control our own behavior), but also how we can inform stimulation devices to control abnormal brain dynamics, for example in patients with severe epilepsy.

About the Speaker: Danielle S. Bassett is the Eduardo D. Glandt Faculty Fellow and Associate Professor in the Department of Bioengineering at the University of Pennsylvania. She is most well-known for her work blending neural and systems engineering to identify fundamental mechanisms of cognition and disease in human brain networks. She received a B.S. in physics from the Pennsylvania State University and a Ph.D. in physics from the University of Cambridge, UK. Following a postdoctoral position at UC Santa Barbara, she was a Junior Research Fellow at the Sage Center for the Study of the Mind. In 2012, she was named American Psychological Association's `Rising Star' and given an Alumni Achievement Award from the Schreyer Honors College at Pennsylvania State University for extraordinary achievement under the age of 35. In 2014, she was named an Alfred P Sloan Research Fellow and received the MacArthur Fellow Genius Grant. In 2015, she received the IEEE EMBS Early Academic Achievement Award, and was named an ONR Young Investigator. In 2016, she received an NSF CAREER award and was named one of Popular Science’s Brilliant 10. She is the founding director of the Penn Network Visualization Program, a combined undergraduate art internship and K-12 outreach program bridging network science and the visual arts. Her work has been supported by the National Science Foundation, the National Institutes of Health, the Army Research Office, the Army Research Laboratory, the Alfred P Sloan Foundation, the John D and Catherine T MacArthur Foundation, and the Office of Naval Research. She lives with her husband and two sons in Wallingford, Pennsylvania.

Towards Identifying and Predicting Spatial Epidemics of Complex Metapopulation Networks

Speaker:Xiang Li, Fudan University
Time: 4:30 pm - 6:00 pm Nov 10, 2016
Location: LC200J, 5 Metrotech Center, Brooklyn, NY

In the past decade, the network science community has witnessed huge advances in a wide range of domains including threshold theory, prediction and control of epidemic dynamics, etc. However, the understanding of epidemic spatial spread on metapopulation networks achieved so far have opened the door to new questions and problems, and a number of major challenges have prompted the research activity. In this paper, we review the recent advances about identifying epidemic parameters and spatial spread processes on metapopulation networks. For simplicity, a two-subpopulation system is taken as an example. Then we introduce a new identification framework as the so called invasion pathways identification algorithm to investigate the problem of identifying invasion spreading process for an epidemic on networked metapopulations. Finally, the outlook of identifying epidemic systems is given.

About the Speaker: Prof. Xiang Li received the B.S. and Ph.D. degrees in control theory and control engineering from Nankai University, Tianjin, China, in 1997 and 2002, respectively. Before joining the Electronic Engineering Department, Fudan University, as a Professor in 2008, he was with the International University Bremen and Shanghai Jiao Tong University as a Humboldt Research Fellow and an Associate Professor in 2005–2006 and 2004–2007, respectively. He served as Head of the Electronic Engineering Department at Fudan University in 2010–2015. Currently, he is the Founding Director of the Research Center of Smart Networks and Systems, School of Information Science and Engineering, Fudan University. His main research interests include theories and applications of complex networks and network science, and he has (co-)authored 4 research monographs and more than 150 peer-refereed publications in journals and conferences. He is Senior Member of the IEEE, serves and served as Associate Editor of IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS–I: REGULAR PAPERS, the IEEE Circuits and Systems Society Newsletter, Control Engineering Practice, and Guest Associate Editor of the International Journal of Bifurcations and Chaos. He received the IEEE Guillemin-Cauer Best Transactions Paper Award from the IEEE Circuits and Systems Society in 2005, the Shanghai Natural Science Award (first class) in 2008, the Shanghai Science and Technology Young Talents Award in 2010, the National Science Foundation for a Distinguished Young Scholar of China in 2014, and the National Natural Science Award (second class) in 2015, among other awards and honors.

From Hacking Towards Engineering Gene Circuits - an Emerging Systems Theory

Speaker:Andras Gyorgy, UC Berkeley
Time: 11:00 am - 12:00 pm Dec 1, 2016
Location: 2MTC, 10th floor, Room 10.099, Brooklyn, NY

Despite the fact that anyone can easily design, synthesize and insert custom DNA sequences into a variety of organisms at low cost, we are unable to engineer synthetic devices realizing complex functions. To deliver on the promise of genetic engineering, we must overcome our inability of predicting how interconnected pieces at the cellular level interact once functioning together. This predictive ability is still largely missing because synthetic gene circuits display context-dependent behavior. In this talk, I address two sources of context-dependence: competition for shared cellular resources and loading of signaling molecules. Combining experiments in E. coli with modeling and theoretical analysis (e.g., model reduction, singular perturbation, contraction theory, optimization, monotone systems theory), I characterize how synthetic gene circuits behave once interconnected based on their properties in isolation, both in vitro and in vivo. These results can be interpreted by considering concepts from economics (price and utility) and electrical networks theory (Thevenin’s theorem), and they move us closer to the rational design of large-scale complex biocircuits, with applications to, e.g., personal therapeutics, material design, and agriculture.

About the Speaker: Andras Gyorgy is a postdoctoral researcher at UC Berkeley after finishing his PhD at MIT in 2016. Prior to this, he earned his MS in Biomedical Engineering in 2011 and his MS in Electrical Engineering in 2009, both at the Budapest Institute of Technology and Economics in Hungary.

By characterizing how the interconnection structure and the dynamics of individual components lead to global behavior over multiple scales of spatiotemporal resolution, his research program contributes to the design, analysis, and control of networked dynamical systems, with particular focus on living systems. His research makes headway in the rational design of synthetic gene circuits enabling the predictive, dynamic, and reliable control of biological systems. Additionally, his hybrid experimental and computational build-to-learn approach elucidates the design principles underlying natural systems, with an emphasis on the role of feedback and dynamics. Therefore, his research lies at the interface of control theory and dynamics with quantitative, synthetic and systems biology. The overarching theme of his work is distilling the humbling complexity of biology into simple-to-use computational tools to reveal predictable structure in high dimensional data in systems and synthetic biology by combining experiments with an abstract systems-level approach.