ECEDHA-C 2020

ECEDHA-C Workshop

AI, Machine Learning and Data-Driven Decision Making: Modern sensing and communication infrastructure has revolutionized the collection, transmission, storage, access, and utilization of data. Artificial intelligence, machine learning and data science are emerging fields where powerful tools are being developed to understand and exploit the information embedded in the big data that arrive with greater variety, increasing volumes, and ever-higher velocity. One of the fundamental challenges is to move AI, machine learning and data science techniques beyond pattern recognition and their incorporation into real-time decision making to address data-driven control and optimization problems of dynamical engineering systems ranging from medical devices, to energy systems, and to transportation network. This workshop aims at bringing together top experts from relevant fields, exploring research and educational opportunities for ECE departments, and developing a common understanding on technical challenges, research trends, and workforce development needs.

Engineering Quantum Devices and Systems:It is clear that while foundational advances in quantum are constantly emerging, the time has come to transition quantum from a basic science (deeply rooted in physics) to an engineering discipline (deeply rooted in ECE departments). As a result of rapid advances in quantum computing, communications, and sensing, these technologies are approaching readiness for deployment. Quantum computing is anticipated to enable calculations that are simply not possible on classical computers, while the deployment of quantum communications would lead to transformative improvements in cybersecurity, and advances in quantum sensors promise devices with record sensitivity. Further, as these technology segments grow, there will be a critical need for talent with relevant expertise. This workshop will bring together experts in these topics to discuss opportunities in research and education for ECE Departments. The goal of these discussions will be to develop an understanding of the technical challenges, research trends, and workforce development needs.

Note: The ECEDHA-C workshop is included in the Full Conference Registration Price. Please email Claire Seifert at cseifert@ecedha.org if you plan on participating so we can accommodate for your participation.

If you only plan on attending this workshop, registration is required at the $495 rate. Travel grants are available for qualifying participants attending only this workshop. Please see below for grant application instructions.

Grant Application Process

Participants are asked to submit the following materials toClaire Seifert, cseifert@ecedha.org, by the extended deadline Friday, February 28, 2020:

The candidate's CV or short bio
A paragraph statement by the candidate with a description of why they would like to participate in this workshop, how it fits with their personal goals, and how it will help advance their departmental goals.

All nominations will be reviewed by the ECEDHA-C committee. Accepted individuals will receive a professional development award in the form of: 1.) travel expenses reimbursement up to$600, 2.) two nights of lodging at group rate, and 3.) complimentary registration to the ECEDHA-C workshops.

REGISTER TODAY!

ECEDHA-C Workshop Chairs

George Pappas
Professor and Chair
University of Pennsylvania

Daniel Stancil
Alcoa Distinguished Professor and Head
North Carolina State University

ECEDHA-C Workshop Schedule of Events

Friday, March 20

7:30 am - 5:00 pm	Registration
8:00 am - 9:00 am	Spotlight Keynote Breakfast
9:00 am - 9:30 am	ECEDHA-C Workshops Opening Session
9:30 am - 10:45 am	Data Science Plenary Session Data Science Plenary Session Panelists: Vijay Kumar Nemirovsky Family Dean University of Pennsylvania VIJAY KUMAR is the Nemirovsky Family Dean of Penn Engineering with appointments in the Departments of Mechanical Engineering and Applied Mechanics, Computer and Information Science, and Electrical and Systems Engineering at the University of Pennsylvania. He received his Bachelors of Technology from the Indian Institute of Technology, Kanpur and his Ph.D. from The Ohio State University in 1987. He has been on the Faculty in the Department of Mechanical Engineering at the University of Pennsylvania since1987. In addition to holding many administrative positions at Penn, Kumar has served as the assistant director of robotics and cyber physical systems at the White House Office of Science and Technology Policy (2012 – 2013). His lab has founded many startups in robotics, and he is the founder of Exyn Technologies. He is a Fellow of the American Society of Mechanical Engineers (ASME) and the Institute of Electrical and Electronic Engineers (IEEE). He was elected to the National Academy of Engineering in 2013 and the American Philosophical Society in 2018. Shankar Sastry Thomas Siebel Professor of Computer Science Director of the Blum Center for Developing Economies University of California, Berkeley S. Shankar Sastry is the Thomas Siebel Professor of Computer Science and the director of the Blum Center for Developing Economies. He has faculty appointments in the departments of Electrical Engineering and Computer Sciences, Bioengineering and Mechanical Engineering. From 2007-2018 he was the Dean and Roy W. Carlson Professor of Engineering. From 2004 to 2007 he was the Director of CITRIS (Center for Information Technology in the Interests of Society) an interdisciplinary center spanning UC Berkeley, Davis, Merced and Santa Cruz. He has served as Chairman, Department of Electrical Engineering and Computer Sciences, University of California, Berkeley from January 2001 through June 2004. From 1999-Feb 2001, he was the Director of the Information Technology Office at the Defense Advanced Research Projects Agency (DARPA).
10:45 am - 11:15 am	Networking Break
11:15 am - 12:30 pm	Quantum Engineering Plenary Session Quantum Engineering Plenary Session Speakers: William Oliver Associate Professor Massachusetts Institute of Technology William D. Oliver is jointly appointed Associate Professor of Electrical Engineering and Computer Science, Professor of the Practice of Physics, and Lincoln Laboratory Fellow, all at the Massachusetts Institute of Technology. He serves as the Director of the Center for Quantum Engineering and as Associate Director of the Research Laboratory of Electronics. Will’s research interests include the materials growth, fabrication, design, and measurement of superconducting qubits, as well as the development of cryogenic packaging and control electronics. Will is a Fellow of the American Physical Society, Senior Member of the IEEE, serves on the US Committee for Superconducting Electronics, and is an IEEE Applied Superconductivity Conference (ASC) Board Member. He received his PhD in Electrical Engineering from the Stanford University in 2003. Erik DeBenedictis Principal Zettaflips, LLC IEEE Rebooting Computing and Quantum Initiative Co-Lead Erik DeBenedictis, Ph. D. Caltech, 1983, Computer Science has worked in HPC architecture his entire career and advanced classical and quantum computing since 2003. Erik worked at Bell Labs, Ansoft (now Ansys), nCUBE, started a company called NetAlive, Inc., worked at Sandia Labs, and is now the principal of Zettaflops, LLC. Erik is a co-lead of IEEE’s Rebooting Computing and Quantum Initiatives and is the Editor in Chief of IEEE Transactions on Quantum Engineering.
12:30 am - 2:00 pm	Lunch and iREDEFINE Poster Session
2:00 pm - 3:15 pm	Breakout Sessions Data Science Research Data Science Research *Speakers:* Yogesh Rathi Harvard University Yogesh Rathi received his Ph.D. in Electrical and Computer Engineering in 2006 from Georgia Institute of Technology, Atlanta. His research interests lie in developing smart imaging techniques to understand brain structure and function. He has developed several compressed sensing algorithms for fast imaging of diffusion MRI — a technology that is now being used to obtain advanced MRI scans of children with ADHD (Attention-deficit Hyperactivity Disorder). His current research focus is on 1). Ultra-high resolution diffusion imaging combining acquisition and reconstruction, 2). estimating tissue microstructure from biophysical and stochastic models of diffusion, and 3). time-series analysis for understanding functional connectivity using fMRI, EEG or MEG data. His clinical research focus includes using and developing sophisticated tractography algorithms for precise targeting of deep-brain stimulation (DBS) and transcranial magnetic stimulation (TMS) in obsessive compulsive disorder (OCD), Parkinson’s and major depressive disorder (MDD). His broad research focus is in the areas of signal and image-processing, statistics, control theory, machine learning, computer vision and related applications to solve inverse problems in medical imaging. Justin Romberg Professor and Associate Chair Georgia Institute of Technology Dr. Justin Romberg is the Schlumberger Professor and the Associate Chair for Research in the School of Electrical and Computer Engineering and the Director of the Machine Learning PhD program at at Georgia Tech. Dr. Romberg received his Ph.D. in 2004 from Rice University. He was a postdoc in Applied and Computational Mathematics at Caltech, and then joined the Georgia Tech faculty in Fall 2006. He is currently on the editorial board for the SIAM Journal on the Mathematics of Data Science, and is a Fellow of the IEEE. His research interests lie on the intersection of signal processing, machine learning, optimization, and applied probability. Sertac Karaman Associate Professor Massachusetts Institute of Technology Sertac Karaman is an Associate Professor at the Massachusetts Institute of Technology. His research interests lie in the broad areas of robotics and control theory. In particular, he studies the foundations and applications of high-performance safety-critical cyber-physical systems. The application areas of his research include driverless cars, unmanned aerial vehicles, distributed aerial surveillance systems, air traffic control, certification and verification of control systems software, and many others. Alex Dimakis Associate Professor University of Texas, Austin Alex Dimakis is an Associate Professor at the Electrical and Computer Engineering department at UT Austin. He received his Ph.D. in 2008 in EECS from UC Berkeley and a Diploma from NTU Athens in 2003. He received several awards including the James Massey award, NSF Career, a Google faculty award and the Eli Jury dissertation award. His research interests include information theory and machine learning. Quantum Engineering Research Quantum Engineering Research *Panelists:* Pat Grumann IBM Ron Walsworth Founding Director Quantum Technology Center Professor University of Maryland Ronald Walsworth is the Founding Director of the Quantum Technology Center and the Minta Martin Professor of Electrical and Computer Engineering, and of Physics, at The University of Maryland. He leads an interdisciplinary research group with a focus on developing precision measurement tools and then applying them to problems in both the physical and life sciences. Two start-up companies have spun out of his lab to date: Quantum Diamond Technologies, Inc. (QDTI) and Hyperfine Research. John Martinis Quantum Computation University of California, Santa Barbara John Martinis attended U.C. Berkeley from 1976 to 1987. His PhD thesis was a pioneering demonstration of quantum-bit states in superconductors. After postdoctoral research at CEA in France, he joined NIST Boulder where he developed electron counting devices and x-ray microcalorimeters. In 2004 he moved to U.C. Santa Barbara where he continued work on quantum computation. In 2014 he was awarded the London Prize for low-temperature physics research. In 2014 he joined the Google quantum-AI team to build a useful quantum computer. Catherine McGeoch D-Wave Catherine McGeoch received her doctorate in Computer Science from Carnegie Mellon University and taught at Amherst College for 30 years. In 2014 she traded academia for industry and joined the technical staff of D-Wave Systems. Her research focus is on empirical performance evaluation of algorithms, especially algorithms for NP-hard problems, and more recently on performance evaluation of quantum algorithms and computing systems.
3:15 pm - 3:45 pm	Networking Break
3:45 pm - 5:00 pm	Breakout Sessions Data Science Education Data Science Education *Organizers:* Asu Ozdaglar Massachusetts Institute of Technology Asu Ozdaglar received the B.S. degree from the Middle East Technical University in 1996, and the S.M. and the Ph.D. degrees from the Massachusetts Institute of Technology, in 1998 and 2003, respectively. She is the Distinguished Professor of Engineering in the Electrical Engineering and Computer Science (EECS) Department at the Massachusetts Institute of Technology. She is also the department head of EECS. Her research expertise includes optimization theory, distributed optimization and control, and network analysis. Raj Nadakuditi Associate Professor University of Michigan Raj Rao Nadakuditi is an Associate Professor in the Department of EECS at the University of Michigan. He received his PhD from MIT and the Woods Hole Oceanographic Institution. His research in machine learning, data science and statistical signal processing focuses on the limits on when algorithms start to work or breakdown due to low signal-to-noise-ratio or too little data. He loves to teach courses on data science and computational machine learning to a diverse audience of students. Genevera Allen Associate Professor, Electrical and Computer Engineering Associate Professor, Statistics Associate Professor, Computer Science Rice University Genevera Allen is an Associate Professor of Electrical and Computer Engineering, Statistics and Computer Science at Rice University and an investigator at the Jan and Dan Duncan Neurological Research Institute at Texas Children's Hospital and Baylor College of Medicine. She is also the Founder and Faculty Director of the Rice Center for Transforming Data to Knowledge, informally called the Rice D2K Lab. Dr. Allen's research focuses on developing statistical machine learning tools to help scientists make reproducible data-driven discoveries. Her work lies in the areas of interpretable machine learning, optimization, data integration, modern multivariate analysis, and graphical models with applications in neuroscience and bioinformatics. Dr. Allen is the recipient of several honors including a National Science Foundation Career award, the George R. Brown School of Engineering's Research and Teaching Excellence Award at Rice University, and in 2014, she was named to the "Forbes '30 under 30': Science and Healthcare" list. Dr. Allen received her PhD in statistics from Stanford University (2010), under the mentorship of Prof. Robert Tibshirani, and her bachelors, also in statistics, from Rice University (2006). Quantum Engineering Education Quantum Engineering Education *Organizers and Panelists:* Celia Merzbacher Associate Director Quantum Economic Development Consortium SRI International Dr. Celia Merzbacher is the Associate Director of the Quantum Economic Development Consortium (QED-C), a consortium established by the 2018 National Quantum Initiative Act that aims to enable and strengthen the U.S. commercial quantum industry. QED-C is supported by the National Institute of Standards and Technology (NIST) and more than 70 industry members and is managed by SRI International. Prem Kumar Professor Northwestern University Prem Kumar is Professor in the ECE Department at Northwestern University. His current research focus is on quantum communications and networking. He has served as a Program Manager at DARPA, where he awarded PM of the Year in 2015 and Secretary of Defense Medal for Outstanding Public Service in 2016. He co-authored the National Academies report: “Optics and Photonics: Essential Technologies for Our Nation,” which spawned the National Photonics Initiative (NPI). Currently, he serves on the NPI Steering Committee, lending his expertise to issues pertaining to the National Quantum Initiative. Dr. Kumar is a Fellow of the OSA, APS, IEEE, IoP (U.K.), AAAS, and SPIE. He has been a Distinguished Lecturer for the IEEE Photonics Society. Ken Brown Duke University Kenneth Brown is an Associate Professor in the Department of Electrical and Computer Engineering at Duke University. He is the Director of the NSF STAQ project which is a multi-institute effort working to build a programmable ion trap quantum computer. He is a Fellow of the APS and former Chair of the Topical Group in Quantum Information of the APS.
5:00 pm - 5:30 pm	ECEDHA-C Roundtable: Closing Session

ECEDHA-C 2020

ECEDHA-C Workshop

ECEDHA-C Workshop Chairs

ECEDHA-C Workshop Schedule of Events

Friday, March 20

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