Category Archives: Uncategorized

ECE Seminar Series: Quantum Dot Channel FETs and Nonvolatile Memories: Fabrication and Modeling

ECE title

ECE Seminar Series Fall 2017

Wednesday November 15th 2:30pm-3:30 PM, GENT 103

Quantum Dot Channel FETs and Nonvolatile Memories: Fabrication and Modeling

Dr. Jun Kondo

Abstract: This talk presents modeling and fabrication of quantum dot channel field effect transistors (QDC-FETs) using cladded Ge quantum dots on poly-Si thin films grown on silicon-on-insulator (SOI) substrtes. HfAlO2 high-k dielectric layers are used for the gate dielectric. QDC-FETs exhibit multi-state I-V characteristics which enable two-bit processing, and reduce FET count and power dissipation, and are expected to make a significant impact on the digital circuit design. Quntum dot channel FETs are also configured as floating gate quatnum dot nonvolatile memories (QDC-QDNVMs). In NVMs, we use floating gate comprising of GeOx-Ge quantum dots. QD nonvolatile memories (QD-NVMs) are fabricated on polysilicon thin films usingn SOI substrates. HfAlO2 high-k insulator laeyrs are used for both tunnel gate oxide as well as conhtrol gate dielectric. QDC-NVMs provide not only significantly higher ID current flow, but also significantly higher threshold voltage shifts which improve the threshold voltage variation, and show the potential for fabricating multi-bit nonvolatile memories.

ECE Seminar Series: Energy Harvesting (EH) Opportunities in 5G

ECE title

ECE Seminar Series Fall 2017

Monday October 16th 11:00am-12:00 PM, ITE 401

Energy Harvesting (EH) Opportunities in 5G

Brian Zahnstecher

PowerRox

Abstract: We have all seen plenty of the marketing hype for what will eventually become 5G in the ~2020 production deployment timeframe. At PowerRox, we have spent the last year trying to shed light on the most critical aspects of the network (from architecture to utilization), which are the paradigm shifts in power electronics and power utilization required to enable 5G. Now, we can investigate further into one of the most interesting, yet highly underappreciated, opportunities in 5G power…energy harvesting (EH). Everyone likes the thought of free, ambient energy, but most think this technology neither produces a usable amount of power nor has a production ecosystem mature enough for a telecom deployment. This talk will not only help to dispel these perceptions, but also help open the eyes of attendees to applications that they might not have otherwise thought were possible and/or applicable to telco applications (with a special focus on 5G).

Energy harvesting (EH) presents a host of interesting and useful applications that can be utilized today as well as provides a roadmap for enhancing/increasing application use cases moving forward. From mW to MW, there are scalable EH technologies to take advantage of nearly every energy source physics affords us (i.e. – kinetic, thermal, RF, photovoltaic, piezoelectric, vibrational, etc.). The major shift from macro towers to heterogeneous networks (HetNets) of many small cells makes 5G an ideal candidate for EH applications. Battery mitigation is a key goal of EH technology initially by supplementing battery power to extend battery life and eventually disposing of them altogether. Even security at many network points from the base station to the grid-level can benefit from EH by achieving grid independence and/or inhibiting undesired network penetration.

This talk will provide attendees with a wealth of knowledge and thought-provoking insight on how EH can be applied to 5G and creative applications beyond. First, we will provide a quick overview of EH sources/technologies, and review the transducers, power management ICs (PMICs)/topologies, energy storage, and test/measurement solutions that make up the production ecosystem. Then, we will deepdive on the implementation of these constituents into practical power electronics solutions and see how we can scale (even μW) to more usable power levels. Finally, we will close with a number of quick case studies on how to apply EH to 5G (and related) applications at all levels of the network from data center to edge. Additionally, we will look at some more unique applications (i.e. – Security) within 5G that EH is a key enabler for.


Short Bio
: Brian Zahnstecher is a Sr. Member of the IEEE, Chair of the IEEE SF Bay Area Power Electronics Society (PELS), and the Principal of PowerRox, where he focuses on power design, integration, system applications, OEM market penetration, and private seminars for power electronics. He has successfully handled assignments in system design/architecting, AC/DC front-end power, EMC/EMI design/debug, embedded solutions, processor power, and digital power solutions for a variety of clients. He previously held positions in power electronics with industry leaders Emerson Network Power, Cisco, and Hewlett-Packard, where he advised on best practices, oversaw product development, managed international teams, created/enhanced optimal workflows and test procedures, and designed and optimized voltage regulators. He has been a regular contributor to the industry as an invited speaker, author, workshop participant, session host, roundtable moderator, and volunteer. He has over 13 years of industry experience and holds Master of Engineering and Bachelor of Science degrees from Worcester Polytechnic Institute.

PowerRox is a firm dedicated to solving power problems for those seeking to establish or enhance their position in the enterprise and consumer power electronics marketplace. We specialize in improving efficiency, increasing reliability, achieving cost reduction through hands-on support and training/seminars/workshops. We can solve problems in power supply design, power system development, system debug and test, cost/performance analysis, marketing, and re-design. We are committed to meeting all deadlines, performing on-budget, debugging/testing solutions to required levels, and doing the highest quality work possible.

ECE Seminar Series: Resiliency and Security of the Future Power Grid

ECE title

ECE Seminar Series Fall 2017

(co-sponsor with Eversource Energy Center)

Monday October 16th 1:00-2:00 PM, LH 201

Resiliency and Security of the Future Power Grid

Chen-Ching Liu

Boeing Distinguished Professor
Director, Energy Systems and Innovation Center (ESIC)
School of Electrical Engineering & Computer Science
Washington State University

Abstract: The development of smart grid in the U.S. over the last decade significantly enhanced data acquisition capabilities on the transmission system. For the distribution network, numerous remote control devices and voltage/var control systems have been installed and millions of smart meters are now operational on the customer side. Although the level of automation has been improved, there are great challenges in the grid’s ability to withstand extreme events such as catastrophic hurricanes and earthquakes. Resiliency of the future grid can be achieved by enabling flexible reconfiguration with distributed resources, e.g., microgrid, distributed generations, as well as renewable and storage devices. Advanced and distributed operation and control will be critical for the vision. Fast increasing connectivity of the devices and systems on the power grid also led to a serious concern over the security of the complex cyber-physical system. Progress has been made in developing new technologies for cyber security of the power grid, including monitoring, vulnerability assessment, intrusion detection, and mitigation


Short Bio
: Chen-Ching Liu is Boeing Distinguished Professor at Washington State University (WSU), Pullman, WA. At WSU, Professor Liu served as Director of the Energy Systems Innovation Center. During 1983-2005, he was a Professor of Electrical Engineering at University of Washington, Seattle. Dr. Liu was Palmer Chair Professor at Iowa State University from 2006 to 2008. From 2008-2011, he served as Acting/Deputy Principal of the College of Engineering, Mathematical and Physical Sciences at University College Dublin, Ireland. Professor Liu received an IEEE Third Millennium Medal in 2000 and the Power and Energy Society Outstanding Power Engineering Educator Award in 2004. In 2013, Dr. Liu received a Doctor Honoris Causa from Polytechnic University of Bucharest, Romania. Chen-Ching chaired the IEEE Power and Energy Society Fellow Committee, Technical Committee on Power System Analysis, Computing and Economics, and Outstanding Power Engineering Educator Award Committee. He served on the U.S. National Academies Board on Global Science and Technology. Professor Liu is a Fellow of the IEEE and Member of the Washington State Academy of Sciences.

ECE Seminar Series: A New Look at Optimal Control of Wireless Networks

ECE title

ECE Seminar Series Fall 2017

Friday October 13th 2:30-3:30 PM, ITE 119

A New Look at Optimal Control of Wireless Networks

Eytan Modiano

Laboratory for Information and Decision Systems
Massachusetts Institute of Technology

Abstract: We address the problem of throughput-optimal packet dissemination in wireless networks with an arbitrary mix of unicast, broadcast, multicast and anycast traffic. We start with a review of the seminal work of Tassiulas and Ephremides on optimal scheduling and routing of unicast traffic, i.e., the famous backpressure algorithm. The backpressure algorithm maximizes network throughput, but suffers from high implementation complexity, and poor delay performance due to packets looping inside the network. Moreover, backpressure routing is limited to unicast traffic, and cannot be used for broadcast or multicast traffic. We will describe a new online dynamic policy, called Universal Max-Weight (UMW), which solves the above network flow problems simultaneously and efficiently. To the best of our knowledge, UMW is the first throughput-optimal algorithm for solving the generalized network-flow problem. When specialized to the unicast setting, the UMW policy yields a throughput-optimal, loop-free, routing and link-scheduling policy. Extensive simulation results show that the proposed UMW policy incurs substantially smaller delays as compared to backpressure.


Short Bio
: Eytan Modiano received his B.S. degree in Electrical Engineering and Computer Science from the University of Connecticut at Storrs in 1986 and his M.S. and PhD degrees, both in Electrical Engineering, from the University of Maryland, College Park, MD, in 1989 and 1992 respectively. He was a Naval Research Laboratory Fellow between 1987 and 1992 and a National Research Council Post Doctoral Fellow during 1992-1993. Between 1993 and 1999 he was with MIT Lincoln Laboratory. Since 1999 he has been on the faculty at MIT, where he is a Professor and Associate Department Head in the Department of Aeronautics and Astronautics, and Associate Director of the Laboratory for Information and Decision Systems (LIDS). His research is on communication networks and protocols with emphasis on satellite, wireless, and optical networks. He is the co-recipient of the MobiHoc 2016 best paper award, the Wiopt 2013 best paper award, and the Sigmetrics 2006 Best paper award. He is the Editor-in-Chief for IEEE/ACM Transactions on Networking, and served as Associate Editor for IEEE Transactions on Information Theory and IEEE/ACM Transactions on Networking. He was the Technical Program co-chair for IEEE Wiopt 2006, IEEE Infocom 2007, ACM MobiHoc 2007, and DRCN 2015. He is a Fellow of the IEEE and an Associate Fellow of the AIAA, and served on the IEEE Fellows committee.

ECE Seminar Series: Building-to-Grid Control Framework for Grid Services

ECE title

ECE Seminar Series Fall 2017

Wednesday September 27th 2:30-3:30 PM, KNS 103

Building-to-Grid Control Framework for Grid Services

Sumit Paudyal

Michigan Technological University

Abstract: With the implementation of Smart Grid technologies, such as sensors, smart meters, smart appliances, more than one-fourth of the US total electricity demand could be dispatchable. Coordinated demand dispatch of customers’ loads provides benefits to the customers and the grid both. A complete demand dispatch solution that benefits the customers and the grid involves a large scale optimization problem with underlying complex transmission and distribution grid models. A centralized approach to solve this problem is computationally involving in a practical sized grid with the consideration of comprehensive customer load models and the grid models that include discrete control variables. A practical way to solve this problem is to use hierarchical and distributed computing approaches, where information exchange occurs between the different levels in the hierarchy. This talk presents hierarchical framework to i) optimally dispatch electric vehicle (EV) loads and ii) optimally dispatch commercial building loads in building-to-grid (B2G) interaction. The case studies demonstrate the benefits of optimal demand dispatch of EV and building loads to the customers and grid operations.


Short Bio
: Sumit Paudyal received B.E. in Electrical Engineering from Tribhuvan University in Nepal, in 2003; Msc. degree in Electrical Engineering from the University of Saskatchewan, Saskatoon, Canada, in 2008; and a Ph.D. in Electrical Engineering from the University of Waterloo, Ontario, Canada, in 2012. Currently, Dr. Paudyal is an Assistant Professor at Michigan Technological University. His research expertise includes Smart Distribution Grid Operations, Optimization Techniques in Power Systems, Power System Protection, and Power System Real-time Hardware Simulations.

ECE Seminar Series: Seeing invisible biological cells – New horizons in cancer diagnosis and IVF

ECE title

ECE Seminar Series Fall 2016

Friday October 21st 1:30-2:30 PM, ITEB 125

Seeing invisible biological cells – New horizons in cancer diagnosis and IVF

Prof. Natan T. Shaked

Tel Aviv University, Israel

Abstract: One of the major challenges in the field of optical imaging of live cells is to achieve label-free but still fully quantitative measurements, which afford high-resolution morphological mapping at the single cell level. In particular, developing efficient, non-subjective, quantitative optical imaging technologies for single-cell imaging with clinical value is a challenging task. Live biological cells are three-dimensional (3D) dynamic microscopic objects that constantly adjust their sizes, shapes and other biophysical features. Visualizing cellular phenomena requires microscopic techniques that can achieve high data acquisition rates, while retaining both resolution and contrast to observe fine cellular features. However, cells in vitro are mostly-transparent 3D objects with absorbance and reflection characteristics that are very similar to their surroundings, and thus conventional intensity-based light microscopy approaches lack the required sensitivity. Exogenous labelling agents such as fluorescent dyes can be used to improve contrast. However, fluorescent agents tend to photo-bleach, reducing the available imaging time. Other concerns include cytotoxicity and the possibility that the exogenous agents will influence cellular behavior. Still, the widely used methods for detection and diagnosis of medical conditions in the cellular level cancer are based on indirect and subjective histological and cytological examination of tissues or samples from bodily fluids. Alternatively, if the sample has to stay alive, such as in sperm selection for in-vitro fertilization, the cells cannot be well visualized. In this lecture, I will review our latest advances in developing new imaging modalities to achieve affordable label-free but still fully quantitative measurements, which offer high-resolution 3D morphological and mechanical mapping of dynamic cells. These approaches are expected to pave the way to new clinical diagnosis and monitoring tools in the single-cell level. I will review two specific applications with a great clinical value: cancer monitoring and sperm selection in in vitro fertilization (IVF).


Short Bio
: Prof. Natan T. Shaked is an Associate Professor in the Department of Biomedical Engineering at Tel Aviv University, Israel. Till April 2011, Prof. Shaked was a Visiting Assistant Professor in the Department of Biomedical Engineering at Duke University, Durham, North Carolina, USA. In the last 4 year, Prof. Shaked raised more 4 million dollar for research. Prof. Shaked is the coauthor of more than 50 refereed journal papers and 80 conference papers, and several book chapters, patents, and an edited book.

ECE Seminar Series: Maximizing Efficiency for Simulation-based or Sample-based Optimization

ECE title

ECE Seminar Series Fall 2016

Friday November 11th 3-4 PM, ITEB 336

Maximizing Efficiency for Simulation-based or Sample-based Optimization

Chun-Hung Chen

George Mason University

Abstract: Simulation and optimization are two popular engineering design tools. Optimization intends to choose the best element from some set of available alternatives. Stochastic simulation is a powerful modeling and software tool for analyzing modern complex systems that arise in manufacturing, power grids, transportation, healthcare, finance, defense, and many other fields. Detailed dynamics of complex, stochastic systems can be modeled in simulation. This capability complements the inherent limitation of traditional optimization, so the combining use of simulation and optimization is growing in popularity. This seminar discusses how we can integrate these two popular tools together and what computational issues we have to face in this integration. We will give an overview of some existing approaches, including gradient-based and model-based approaches. We will also present our developments based on a new technique called Optimal Computing Budget Allocation, initially developed by the speaker. Our goal is to maximize the efficiency of finding a good decision via optimal control of simulation replications and optimal sampling in design space.


Short Bio
: Chun-Hung Chen received his Ph.D. degree from Harvard University in 1994. He is currently a Professor at George Mason University. Dr. Chen was an Assistant Professor at the University of Pennsylvania before joining GMU. He was also affiliated with National Taiwan University (Electrical Eng. and Industrial Eng.) from 2008-14. Sponsored by NSF, NIH, DOE, NASA, FAA, Missile Defense Agency, and Air Force in US, he has worked on the development of very efficient methodology for simulation-based decision making and its applications. Dr. Chen received several awards such as “National Thousand Talents Award” from China and Eliahu I. Jury Award from Harvard University. He has served as a Department Editor for IIE Transactions, Department Editor for Asia-Pacific Journal of Operational Research, Associate Editor for IEEE Transactions on Automation Science and Engineering, Associate Editor for IEEE Transactions on Automatic Control, Area Editor for Journal of Simulation Modeling Practice and Theory, Advisory Editor for International Journal of Simulation and Process Modeling, and Advisory Editor for Journal of Traffic and Transportation Engineering. Dr. Chen is the author of two books, including a best seller: “Stochastic Simulation Optimization: An Optimal Computing Budget Allocation”. He is an IEEE Fellow.

ECE Seminar Series: A Decade of Compressive Sensing-application in optical sensing and imaging, achievements and challenges

ECE title

ECE Seminar Series Fall 2016

Wednesday October 19th 3-4 PM, ITEB 336

A Decade of Compressive Sensing-application in optical sensing and imaging, achievements and challenges

Adrian Stern

Ben Gurion University of Negev, Israel

Abstract: The theory of compressive sensing (CS) has attracted great attention since it was published a decade ago. CS has found natural applications in imaging and optical sensing sciences, yielding a great number of publications. From a decade perspective, I will present an overview of the main achievements in optical CS engineering and discuss remaining challenges. I will survey the main applications and present representative examples form our and other’s group results. I will highlight the benefits gained from the CS application in optics, present the main implementation challenges of the mathematical CS theory in optical engineering. Finally, future directions will be discussed.

 

adrian-sternShort Bio: Adrian Stern received his B.Sc., M. Sc. (cum laude) and PhD degrees from Ben-Gurion University of the Negev, Israel, in 1988, 1997 and 2003 respectively, all in Electrical and Computer Engineering. Currently he is an Associate Professor at Electro-Optical Engineering department at Ben-Gurion University in Israel where he serves as department head. During the years 2002-2004 he was a postdoctoral fellow at University of Connecticut. During 2007-2008 he served as senior research and algorithm specialist for GE Molecular Imaging, Israel. In 2014-2015, during his sabbatical leave, he was a visitor scholar and professor at Massachusetts Institute of Technology (MIT). His current research interests include computational imaging and sensing, 3D imaging, compressed imaging, phase-space optics, bio-medical imaging. Dr. Stern has published over 150 technical articles in leading peer reviewed journals and conference proceeding, more than quarter of them being invited papers. Dr. Stern is a Fellow of SPIE, member of IEEE, OSA. He served as editor for Optics Express journal. He is the editor of the first book to be published on optical compressive sensing.

ECE Seminar Series: Large-Area High-Efficiency Solid-State Thermal Neutron Detector

ECE title

ECE Seminar Series Spring 2016

Thursday May 5th 1-2 PM, ITEB 336

Large-Area High-Efficiency Solid-State Thermal Neutron Detector

Rajendra Dahal

Electrical, Computer, and Systems Engineering

Rensselaer Polytechnic Institute, Troy, New York

Abstract: The development of high-efficiency large-area solid-state neutron detectors is urgent for a wide range of civilian and defense applications; such as monitoring of “dirty bombs”, border patrol, medical and industrial imaging. The applications of present neutron detector systems are limited by cost, size, weight, and power requirements. An efficient self-powered, or low-power, solid-state neutron detector using mature silicon technology would provide significant benefits in terms of cost and volume. Also, it would allow wafer-level integration with readout electronics. This talk presents current research advances on fabrication and characterization of a large area solid-state thermal-neutron detector module with detection efficiency exceeding 30%. The detector utilizes three-dimensional honeycomb silicon microstructures, and a continuous p+-n junction diode filled with enriched boron (99% of 10B) as a converter material for thermal-neutron detection. The low leakage current density of the fabricated device helps to increase the detector surface area to greater than 16cm2. These results show promise in using such highly efficient large-area solid-state neutron detectors in home land security applications.

 

Short Bio: Dr. Rajendra Dahal is a Research Assistant Professor in the Electrical, Computer, and Systems Engineering Department here at Rensselaer. His current research interests include epitaxial growth of wide band-gap semiconductor thin films, such as 2D layered materials and nanostructures; fabrication of micro/nanostructures for efficient radiation detectors; and optoelectronic devices.

 

ECE Seminar Series: Industrial Strength Real World Multi-Sensor Data Fusion

ECE title

ECE Seminar Series Spring 2016

Monday May 2rd 1-2 PM, ITEB 336

Industrial Strength Real World Multi-Sensor Data Fusion

Frederick E. Daum

Raytheon

Abstract: We explain why multi-sensor data fusion is a difficult problem in the real world. We also describe several new algorithms that are designed to solve such problems, considering real world effects. The major real world issues for data fusion include: (1) unresolved sensor data; (2) residual sensor bias errors; (3) closely spaced multiple targets; (4) unresolved sensor data; (5) non-unity probability of detection and non-zero probability of false alarms from noise & clutter; (6) inconsistent covariance matrices; and (7) unresolved sensor data. Such problems often result in putting the wrong data into your favorite estimation algorithm (extended Kalman filter, particle filter, unscented Kalman filter, etc.). The best way to ruin the performance of a good filter is to put the wrong data into it. One of the best algorithms to mitigate such problems is called GNPL (global nearest pattern Levedahl), invented at Raytheon. This algorithm jointly estimates the residual relative sensor biases and the association of data or tracks between sensors. The key word is “jointly”. We show comparisons of GNPL vs. simpler algorithms that decouple the bias estimation and data association problems. For difficult scenarios, GNPL is superior to simpler decoupled algorithms. We also describe more advanced algorithms that promise better performance at the cost of higher real time computational complexity. Such algorithms actually model the correct relevant physics, and they also exploit recent advances in particle filters and GPUs and the theory of random sets. This talk is for normal engineers who do not have nonlinear filters for breakfast.

 

Short Bio: Fred Daum is an IEEE Fellow, a principal Fellow at Raytheon, a Distinguished Lecturer for the IEEE and a graduate of Harvard University. Fred was awarded the Tom Phillips prize for technical excellence, in recognition of his ability to make complex radar systems work in the real World. He developed, analyzed and tested the real time algorithms for essentially all the large long range phased array radars built by the USA in the last four decades, including: Cobra Dane, PAVE PAWS, Cobra Judy, BMEWS, THAAD, ROTHR, UEWR, and SBX, as well as many other systems (SPY-3 proposal, JLENS proposal, SPACE FENCE proposal, LRDR proposal, JADGE, Project Hercules, ADI concept A, C-RAM, C-MAR, AN/TPN-19, ASDE-X, DERD-MC, NATO Sea Sparrow, DLGN-38, GPS OCX and several sonar systems). These real time algorithms include: extended Kalman filters, radar waveform scheduling, Bayesian discrimination, data association, discrimination of satellites from missiles, calibration of tropospheric and ionospheric refraction, and target object mapping. Fred’s exact fixed finite dimensional nonlinear filter theory generalizes the Kalman and Beneš filters. Fred’s particle flow nonlinear filter is many orders of magnitude faster than standard particle filters for the same accuracy. He has published nearly one hundred technical papers, and he has given invited lectures at MIT, Harvard, Yale, Caltech, the Technion, Ecole Normale Superieure de Paris, Brown, Georgia Tech., Duke, Univ. of Connecticut, Univ. of Minnesota, Melbourne Univ., Univ. of Toulouse, Univ. of New South Wales, Univ. of Canterbury, Liverpool Univ., Xidian Univ., Univ. of Illinois at Chicago, Washington Univ. at St Louis, McMaster Univ., Boston Univ., Northeastern University, Huntsville, Colorado and Rutgers.