ESE Colloquia & Events

Fall 2018

ESE colloquia are held from 11-12:00pm in Towne 337, unless otherwise noted. For all Penn Engineering events, visit the Penn Calendar.

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Roget Howe
Tuesday, September 18th (Joint MEAM/ESE)
Sigma Aldrich Lecture (Singh and ESE Joint Seminar)
Ali Javey, University of California-Berkeley
Professor, Electrical Engineering and Computer Sciences
"2D Semiconductor Electronics: Advances, Challenges, and Opportunities"
2:00pm, Singh Center Glandt Forum
Read the Abstract and Bio

Abstract:Two-dimensional (2-D) semiconductors exhibit excellent device characteristics, as well as novel optical, electrical, and optoelectronic characteristics. In this talk, I will present our recent advancements in defect passivation, contact engineering, surface charge transfer doping, ultrashort transistors, and heterostructure devices of layered chalcogenides. We have develope da defect passivation technique that allows for observation of near-unity quantum yield in monolayer semiconductors. The work presents the viability of monolayers for efficient light emitting devices. Forming Ohmic contacts for both electrons and holes is necessary in order to exploit the performance limits of enabled devices while shedding light on the intrinsic properties of a material system. In this regard, we have developed different strategies, including the use of surface charge transfer doping at the contacts to thin down the Schottky barriers, thereby, enabling efficient injection of electrons or holes. We have been able to show high performance n- and p-FETs with various 2D materials, including the demonstration of a FET with 1nm physical gate length exhibiting near ideal switching characteristics. Additionally, I will discuss the use of layered chalcogenides for various heterostructure device applications, exploiting charge transfer at the van der Waals heterointerfaces.

Bio: Ali Javey received a Ph.D. degree in chemistry from Stanford University in 2005, and was a Junior Fellow of the Harvard Society of Fellows from 2005 to 2006. He then joined the faculty of the University of California at Berkeley where he is currently a professor of Electrical Engineering and Computer Sciences. He is also a faculty scientist at the Lawrence Berkeley National Laboratory where he serves as the program leader of Electronic Materials (E-Mat). He is the co-director of Berkeley Sensor and Actuator Center (BSAC), and Bay Area PV Consortium (BAPVC). He is an associate editor of ACS Nano. Javey's research interests encompass the fields of chemistry, materials science, and electrical engineering. His work focuses on the integration of nanoscale electronic materials for various technological applications, including low power electronics, flexible circuits and sensors, and energy generation and harvesting. He is the recipient of MRS Outstanding Young Investigator Award (2015), Nano Letters Young Investigator Lectureship (2014); UC Berkeley Electrical Engineering Outstanding Teaching Award (2012); APEC Science Prize for Innovation, Research and Education (2011); Netexplorateur of the Year Award (2011); IEEE Nanotechnology Early Career Award (2010); Alfred P. Sloan Fellow (2010); Mohr Davidow Ventures Innovators Award (2010); National Academy of Sciences Award for Initiatives in Research (2009); Technology Review TR35 (2009); SF Early CAREER Award (2008); U.S. Frontiers of Engineering by National Academy of Engineering (2008); and Peter Verhofstadt Fellowship from the Semiconductor Research Corporation (2003).

Tuesday, October 2nd
Jeremy N. Munday, University of Maryland
Associate Professor, Electrical and Computer Engineering, and
The Institute for Research in Electronics and Applied Physics
"Taming Photons: From Nanoscale Devices to Space Propulsion"

Read the Abstract and Bio

Abstract: Photons are remarkable bundles of energy that can be used to perform a variety of tasks. In this talk, I will present our latest research describing how we control photons to create novel devices ranging from near-IR Si detectors and solar energy harvesters to space propulsion technologies based on photon pressure (light sails) and devices that exploit the quantum nature of the vacuum. In the first part of my talk, I will discuss the concept of hot carriers (i.e. charge carriers with excess kinetic energy) and how they can be used to make near-IR imaging detectors. Next, I will demonstrate the concept of electrically controlled optical components and show how we use these devices to create self-powered smart windows for building integration, attitude control devices for light sails, and as a way to modify the optoelectronic response of a semiconductor. Finally, when no photons are present, quantum fluctuations of electromagnetic fields still exist. In the last part of the talk, I will discuss how we can control these fluctuations (sometimes called virtual photons) to create forces and torques on nanoscale objects, exploiting this effect (i.e. the Casimir effect) for fundamental science and technological applications.

Bio: Dr. Jeremy N. Munday is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Maryland, College Park. He received his PhD in Physics from Harvard University and was a postdoctoral scholar at Caltech prior to his appointment at Maryland. His research themes range from quantum electromechanical phenomena (such as the Casimir effect) to fundamental solar energy conversion processes with an emphasis on the optics, photonics, and thermodynamics of such systems. He is a recipient of the DARPA Young Faculty Award (2018), the NSF CAREER Award (2016), the ONR Young Investigator Program Award (2016), the OSA Adolph Lomb Medal (2015), the IEEE Photonics Society Young Investigator Award (2015), the SPIE Early Career Achievement Award (2014), and the NASA Early Career Faculty Space Technology Research Award (2012).

Tuesday, October 16th
Mahdi Soltanolkotabi, University of Southern California
Assistant Professor, Ming Hsieh Department of Electrical Engineering
"From Shallow to Deep: Rigorous Guarantees for Training Neural Networks"

Read the Abstract and Bio

Abstract: Neural network architectures (a.k.a. deep learning) have recently emerged as powerful tools for automatic knowledge extraction from data, leading to major breakthroughs in a multitude of applications. Despite their wide empirical use the mathematical success of these architectures remains a mystery. A major challenge is that training neural networks correspond to extremely high-dimensional and nonconvex optimization problems and it is not clear how to provably solve them to global optimality. While training neural networks is known to be intractable in general, simple local search heuristics are often surprisingly effective at finding global/high quality optima on real or randomly generated data. In this talk I will discuss some results explaining the success of these heuristics. First, I will discuss results characterizing the training landscape of single hidden layer networks demonstrating that when the number of hidden units are sufficiently large then the optimization landscape has favorable properties that guarantees global convergence of (stochastic) gradient descent to a model with zero training error. Second, I introduce a de-biased variant of gradient descent called Centered Gradient Descent (CGD). I will show that unlike gradient descent, CGD enjoys fast convergence guarantees for arbitrarily deep convolutional neural networks with large stride lengths.

Bio: Mahdi Soltanolkotabi is currently an assistant professor in the Ming Hsieh Department of Electrical Engineering at the University of Southern California. Prior to joining USC, he completed his PhD in electrical engineering at Stanford in 2014. He was a postdoctoral researcher in the EECS department at UC Berkeley during the 2014-2015 academic year. Mahdi is a recipient of the 2017 Google faculty research and the 2018 AFOSR young investigator awards. His research focuses on the design and mathematical understanding of computationally efficient algorithms for optimization, high dimensional statistics, artificial intelligence, machine learning, signal processing and computational imaging. A main focus of his research has been on developing and analyzing algorithms for nonconvex optimization, with provable guarantees of convergence to global optima.

Tuesday, October 30th
Hua Wang, Georgia Tech
Associate Professor, School of Electrical and Computer Engineering
"Building Heterogeneous Integrated Systems for Future Communication, Sensing, and Bioelectronics"
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Abstract: Silicon-based integrated electronics have become one of the most powerful man-made platforms for building complex systems that can detect, generate, process, and store information at an unprecedented level. Future innovations in integrated electronics rely on exploiting heterogeneity at both technology level and system level. Recent rapidly growing applications of 5G wireless, IoT, and bioelectronics are perfect examples based on cross-domain combination of communication, sensing, and computation. In this talk, I will introduce several example research projects at Georgia-Tech Electronics and Micro-Systems (GEMS) lab, which achieve technology innovations by exploring such heterogeneity.
First, I will present several mm-Wave circuits and systems for 5G massive MIMO communication and radar by fusing complex electronics with radiators and signal processing. In particular, novel “multi-feed antennas” and their co-integration with electronics can actively synthesize desired radiation responses with unprecedented “on-antenna” functionalities and reconfigurability far beyond electronics-only designs, including high-efficiency power combining, impedance scaling, Doherty or Outphasing active load modulation, and polarization full-duplex communication.
Next, I will introduce our hybrid bioelectronics and biosensors research, focusing on fusing living cells with electronics to achieve biotic/abiotic systems with novel functionalities. I will present several multi-modal CMOS cellular interfacing arrays with single-cell resolution, tissue-level field-of-view (FoV), and multi-modal sensing/actuation at the pixel-level, enabling holistic cell characterization for massively parallel new drug development, synthetic biology engineering, and cell manufacturing. The multi-modal cellular interfacing platforms generate a massive amount of real-time hyper-dimensional cellular data, and the potential use of data-driven cell classifications with machine learning will also be discussed.

Bio: Hua Wang is the Demetrius T. Paris associate professor at the School of Electrical and Computer Engineering (ECE) at Georgia Institute of Technology and the director of Georgia Tech Electronics and Micro-System (GEMS) lab. Prior to that, he worked at Intel Corporation and Skyworks Solutions on mm-Wave integrated circuits and RF front-end modules. He received his M.S. and Ph.D. degrees in electrical engineering from the California Institute of Technology, Pasadena, in 2007 and 2009, respectively.
Dr. Wang is interested in innovating mixed-signal, RF, and mm-Wave integrated circuits and hybrid systems for wireless communication, radar, imaging, and bioelectronics applications.
Dr. Wang received the DARPA Young Faculty Award in 2018, National Science Foundation CAREER Award in 2015, the IEEE MTT-S Outstanding Young Engineer Award in 2017, the Georgia Tech Sigma Xi Young Faculty Award in 2016, the Georgia Tech ECE Outstanding Junior Faculty Member Award in 2015, and the Lockheed Dean’s Excellence in Teaching Award in 2015. Dr. Wang is an Associate Editor of the IEEE Microwave and Wireless Components Letters (MWCL) and a Distinguished Lecturer for the IEEE Solid-State Circuit Society (SSCS). He is a Technical Program Committee (TPC) Member for IEEE ISSCC, RFIC, CICC, and BCTM conferences. He is also the Chair of the Atlanta’s IEEE CAS/SSCS joint chapter that won the IEEE SSCS Outstanding Chapter Award in 2014.

Tuesday, November 6th
Anthony Ephremides, University of Maryland
Professor, Department of Electrical and Computer Engineering and the Institute for Systems Research
"On "Age" "
Read the Abstract and Bio

Abstract: This talk will introduce and describe the new notion of Age of Information Updates. It is also referred to as Age of Information (AoI). Briefly, this notion summarizes the latency of received messages from time of generation to final reception. Examples include any monitoring system, data collection from censors, processes that evolve in time (like stock market data, object trajectories, etc.), caching systems at network edge, and many others.

The novelty of the concept consists of viewing all the causes of latency in a unified way. The “age” of information at the receiver at time t is defined as the difference between the current time t and the time u(t) which is the time of generation of the most recently received update.

The AoI is a concept, a metric and a tool. In this talk, we will review its evolution over its brief history (it was introduced in 2012) and highlight some of the progress made in its study since. We will conclude by pointing out some of the fundamental issues that arise from its study and that connect signal processing, sampling, information theory, and network control.

Bio: Anthony Ephremides holds the Cynthia Kim Professorship of Information Technology at the Electrical and Computer Engineering Department of the University of Maryland in College Park where he is a Distinguished University Professor and has a joint appointment at the Institute for Systems Research, of which he was among the founding members in 1986. He obtained his PhD in Electrical Engineering from Princeton University in 1971 and has been with the University of Maryland ever since.

He has held various visiting positions at other Institutions (including MIT, UC Berkeley, ETH Zurich, INRIA, etc), and co-founded and co-directed a NASA-funded Center on Satellite and Hybrid Communication Networks in 1991. He has been the President of Pontos, Inc, a consulting firm, since 1980 and has served as President of the IEEE Information Theory Society in 1987 and as a member of the IEEE Board of Directors in 1989 and 1990. He has been the General Chair and/or the Technical Program Chair of several technical conferences (including the IEEE Information Theory Symposium in1991, 2000, and 2011, the IEEE Conference on Decision and Control in 1986, the ACM Mobihoc in 2003, and the IEEE Infocom in 1999). He has served on the Editorial Board of numerous journals and was the Founding Director of the Fairchild Scholars and Doctoral Fellows Program,, a University-Industry Partnership from 1981 to 1985.

He has received the IEEE Donald E. Fink Prize Paper Award in 1991, the first ACM Achievement Award for Contributions to Wireless Networking in 1996, as well as the 2000 Fred W. Ellersick MILCOM Best Paper Award, the IEEE Third Millennium Medal, the 2000 Outstanding Systems Engineering Faculty Award from the Institute for Systems Research, and the Kirwan Faculty Research and Scholarship Prize from the University of Maryland in 2001, and a few other official recognitions of his work. He also received the 2006 Aaron Wyner Award for Exceptional Service and Leadership to the IEEE Information Theory Society.

He is the author of several hundred papers, conference presentations, and patents, and his research interests lie in the areas of Communication Systems and Networks and all related disciplines, such as Information Theory, Control and Optimization, Satellite Systems, Queueing Models, Signal Processing, etc. He is especially interested in Wireless Networks, Energy Efficient Systems, and the new notion of Age of Information.

Tuesday, November 13th
David Tse, Stanford University
Professor, Department of Electrical Engineering
"Deconstructing the Blockchain to Approach Physical Limits"
Read the Abstract and Bio

Abstract: The concept of a blockchain was invented in 2008 by Satoshi Nakamoto to maintain a distributed ledger for an electronic payment system, Bitcoin. Transaction throughput, confirmation latency and confirmation reliability are important performance measures of any blockchain protocol, in addition to its security. These measures are limited by two underlying physical network attributes: communication capacity and speed-of-light propagation delay. Existing systems operate far away from these physical limits. In this work we introduce Prism, a new blockchain protocol, which can achieve 1) security against up to 50% adversarial hashing power; 2) optimal throughput up to the capacity C of the network; 3) confirmation latency for honest transactions proportional to the propagation delay D, with confirmation error probability exponentially small in the bandwidth-delay product CD ; 4) eventual total ordering of all transactions. Our approach to the design of this protocol is based on deconstructing the blockchain into its basic functionalities and systematically scaling up these functionalities to approach their physical limits.

This is joint work with Vivek Bagaria, Sreeram Kannan, Giulia Fanti and Pramod Viswanath. The full paper can be found at

Bio: David Tse received the B.A.Sc. degree in systems design engineering from University of Waterloo in 1989, and the M.S. and Ph.D. degrees in electrical engineering from Massachusetts Institute of Technology in 1991 and 1994 respectively. From 1995 to 2014, he was on the faculty of the University of California at Berkeley. He is currently the Thomas Kailath and Guanghan Xu Professor at Stanford University. He received the Claude E. Shannon Award in 2017 and was elected member of the U.S. National Academy of Engineering in 2018. Previously, he received a NSF CAREER award in 1998, the Erlang Prize from the INFORMS Applied Probability Society in 2000 and the Frederick Emmons Terman Award from the American Society for Engineering Education in 2009. He is a coauthor, with Pramod Viswanath, of the text Fundamentals of Wireless Communication, which has been used in over 60 institutions around the world. He received best paper awards from IEEE Information Theory, Communications and Signal Processing societies, and is the inventor of the proportional-fair scheduling algorithm used in all third and fourth-generation cellular systems.

Tuesday, December 4th
Cris Moore, Santa Fe Institute 
Professor, Science Board  
"Black Cats in Dark Rooms: What Physics Can Tell Us About Inference"  
Read the Abstract and Bio

Abstract: There is a deep analogy between statistical inference and statistical physics. I will give a friendly introduction to both of these fields. I will then discuss phase transitions in problems like community detection in networks, where if our data is too sparse or too noisy it suddenly becomes impossible to find the underlying pattern. It turns out that there are two kinds of phase transitions: information-theoretic ones, where the data simply doesn’t tell us enough about the ground truth, and computational ones, where inference is possible but seems to take exponential time. I will also discuss optimal algorithms that succeed as well as possible up to these barriers.

Bio: Cristopher Moore received his B.A. in Physics, Mathematics, and Integrated Science from Northwestern University, and his Ph.D. in Physics from Cornell. From 2000 to 2012 he was a professor at the University of New Mexico, with joint appointments in Computer Science and Physics. Since 2012, Moore has been a resident professor at the Santa Fe Institute; he has also held visiting positions at École Normale Superieure, École Polytechnique, Université Paris 7, the Niels Bohr Institute, Northeastern University, and the University of Michigan. He has written 150 papers at the boundary between Physics and Computer Science, ranging from quantum computing, to phase transitions in NP-complete problems, to social networks and algorithms for analyzing their structure. He is an elected Fellow of the American Physical Society, the American Mathematical Society, and the American Association for the Advancement of Science. With Stephan Mertens, he is the author of The Nature of Computation from Oxford University Press.

Tuesday, December 11th
James Buckwalter, UC Santa Barbara
Professor, Electrical and Computer Engineering
"Demanding Dynamic Range: Linearity, Interface Tolerance, and Energy-Efficiency for RF and Millimeter-wave Integrated Circuits and Systems"
2:00pm, Towne 337
Read the Abstract

Abstract: Future wireless systems – often referred to as 5G – will feature wireless services that demand varied trade-offs between data rate, latency, coverage, and power consumption. A long-awaited migration towards millimeter-wave bands has promised high data rates and low latency due to relatively wide bandwidth (up to 2 GHz) in access and backhaul networks. However, a combination of high-order QAM, OFDM, and multiple beams will result in high peak-to-average power ratio (PAPR) signals in the transmitter. High PAPR demands a linear response and generally a reduction in the efficiency of the circuitry. I will present our recent research that has reformulated these efficiency-linearity tradeoffs in millimeter-wave transmitters to improve the dynamic range.

Full-duplex communication could improve the spectral efficiency or channel estimation in MIMO networks. However, full duplex places significant dynamic range requirements on the receiver to tolerate the strong transmitter interference. I will present a proposed multiple access technique that realizes more than 50 dB of signal rejection before the LNA to relax the potential distortion generation in the receiver and realize a full-duplex link without significant power penalties at RF bands.

Finally, I will present a vision for RF photonic receivers to support millimeter-wave MIMO. Silicon photonic devices offer a low-cost platform that might potentially support co-integration of electronic and photonic circuitry. To overcome the spur-free dynamic range issues confronting RF electro-optic conversion, we will briefly review approaches to improve the linearity of silicon photonic modulators.

Bio: James F. Buckwalter is currently a Professor of Electrical and Computer Engineering with UCSB and was the recipient of a 2004 IBM Ph.D. Fellowship, 2007 Defense Advanced Research Projects Agency (DARPA) Young Faculty Award, 2011 NSF CAREER Award, and 2015 IEEE MTT-S Young Engineer Award. He is a senior member of the IEEE and has published more than 150 conference and journal papers on research related to RF, millimeter-wave, and high-speed optoelectronic circuits and systems.

Thursday, December 13th
Saurabh Amin, MIT
Associate Professor, Civil and Environmental Engineering
"Transportation Systems Resilience: Capacity-Aware Control and Value of Information"
Read the Abstract

Abstract: Resilience of a transportation system is its ability to operate under adverse events like incidents and storms. Availability of real-time traffic data provides new opportunities for predicting travelers’ routing behavior and implementing network control operations during adverse events. In this talk, we will discuss two problems: controlling highway corridors in response to disruptions and modeling strategic route choices of travelers with heterogeneous access to incident information. Firstly, we present an approach to designing control strategies for highway corridors facing stochastic capacity disruptions such random incidents and vehicle platoons/moving bottlenecks. We exploit the properties of traffic flow dynamics under recurrent incidents to derive verifiable conditions for stability of traffic queues, and also obtain guarantees on the system throughput. Secondly, we introduce a routing game in which travelers receive asymmetric and incomplete information about uncertain network state, and make route choices based on their private beliefs about the state and other travelers’ behavior. We study the effects of information heterogeneity on travelers’ equilibrium route choices and costs. Our analysis is useful for evaluating the value of receiving state information for travelers, which can be positive, zero, or negative in equilibrium. These results demonstrate the advantages of considering network state uncertainty in both strategic and operational aspects of system resilience.

Bio: Saurabh Amin is Robert N. Noyce Career Development Associate Professor in the Department of Civil and Environmental Engineering at MIT. He is also affiliated with the Institute of Data, Systems and Society and the Operations Research Center at MIT. His research focuses on the design of network inspection and control algorithms for infrastructure systems resilience. He studies the effects of security attacks and natural events on the survivability of cyber-physical systems, and designs incentive mechanisms to reduce network risks. Dr. Amin received his Ph.D. from the University of California, Berkeley in 2011. His research is supported by NSF CPS FORCES Frontiers project, NSF CAREER award, Google Faculty Research award, DoD-Science of Security Program, and Siebel Energy Institute Grant.