A modern power system is composed of many individual entities collaborating with each other to operate the entire system in a secure and economic manner. These entities could have different owners and operators with their own operating rules and policies, and it makes the decision- making process in the system challenging. In this talk, a system of systems (SoS) engineering framework is presented for optimally operating the modern/future smart grids. The presented SoS framework defines each entity as an independent subsystem with its own regulations. Since the independent subsystems are working in an interconnected system, the operating condition of one might impact the operating condition of others. According to the independent subsystems’ characteristics and connection between them, an optimization problem is formulated for each independent subsystem. In order to solve the optimization problem of each subsystem and to optimally operate the entire SoS-based power system, decentralized decision-making algorithms are developed. Using these algorithms, only a limited amount of information is exchanged among different subsystems, and the operators of independent subsystems do not need to exchange all the information, which might be commercially sensitive, with each other. Furthermore, the presented decentralized optimization algorithms could obtain the optimal operating point of large- scale power systems faster than conventional centralized methods. Two examples are studied to demonstrate the effectiveness of the presented decision-making framework.

DNA methylation is an epigenetic modification of DNA in which methyl groups are added at the 5-carbon position of cytosine (5mC). Aberrant DNA methylation, which has been associated with carcinogenesis, can be assessed in various biological fluids and potentially be used as biomarkers for detection of cancer. In this talk, I will present a nanopore-based direct methylation detection assay using methyl-binding proteins (MBPs), which selectively label the methylated DNA. The nanopore-based assay using moleucular-scale pores in a variety of diameters distinguished 827 bp-long methylated DNA/MBP complexes from unmethylated DNA, selectively detects 90 bp methylated DNA/MBP over unmethylated DNA, and discriminated hypermethylated DNA/MBP and unmethylated DNA on 90 bp, 60 bp, and 30 bp DNA fragments. Furthermore, these nanopore assays can detect CpG dyads in DNA fragments and could someday profile the position of methylated CpG sites on DNA fragments. This nanopore-based methylated sensitive assay could circumvents the need of conventional methods for bisulfite conversion, fluorescent labeling, and PCR and could therefore prove very useful in studying the role of epigenetics in human disease.

Jiwook Shim is currently a research scientist, leading the solid-state nanopore group under Prof. Rashid Bashir's direction, in the Micro and Nanotechnology Laboratory at the University of Illinois at Urbana-Champaign (UIUC). He obtained M.S. in Electrical and Computer Engineering and Ph.D. in Bioengineering at University of Missouri in 2004 and 2008, respectively, and he continued working another year with his Ph.D. advisor as a postdoctoral fellow. In 2009, Dr. Shim joined Beckman Institute for advanced science and technology at UIUC as a postdoctoral research associate, and then he continued working as postdoctoral research associate at Micro and Nanotechnolgy Laboratory. His research interests include novel applications of nanotechnology for healthcare and developing a method to utilize nanotechnology for disease diagnostics tools.

The operation of modern electric power systems depends a great deal on the use of advanced sensing and measurement technologies that collect and collate synchronized data from multiple locations to monitor the health of network states for fast and accurate diagnosis of large system disruptions. Along with power grid's physical vulnerability to faults and disturbances, the inherent wide-area nature of the sensing, communication, and control systems in evolving smart grids presents several vulnerabilities in terms of possible cyberintrusions that may hinder or alter the normal operations of the entire cyber-physical grid infrastructure. For this reason, ensuring reliable event detection and maintaining system observability even under the threat of physical and cyberattacks remain a key challenge for developing a resilient power grid. Accordingly, this talk will provide distinctively new research efforts towards designing reliable and secure power grid infrastructure through versatile utilization of synchronized measurement systems. In particular, cost-effective deployment strategies for synchronized measurement devices, which allow for systemwide fault/attack localization and grid observability, will be presented with examples.

Dr.\ Mert Korkali received the B.S. degrees with a double major in electrical and electronics engineering and in industrial engineering from Bahcesehir University, Istanbul, Turkey, in 2008, and the M.S. and Ph.D. degrees in electrical engineering from Northeastern University, Boston, MA, in 2010 and 2013, respectively. From October 2013 to October 2014, he was a Postdoctoral Research Associate at the Complex Systems Center, The University of Vermont, Burlington, VT. Since November 2014, he has been a Postdoctoral Research Staff Member at the Computational Engineering Division, Lawrence Livermore National Laboratory, Livermore, CA. His research interests lie at the broad interface of power system state estimation, electromagnetic transient analysis, cyber-physical energy networks, cascading failures, and high-performance computing applications for large-scale power grids. He is a Member of the IEEE and SIAM, and regularly serves as a reviewer for several international journals.

During the last decade of the century, there has been a tremendous increase in the use of electrical and electronic system in the biomedical field for clinical study and research purpose. A biomedical instrumentation system is to measure the presence of some biophysical quantity and aid in making decision for better diagnostic and treatment outside of a centralized testing facility, including hospitals, physicians' office, emergency settings, at-home use or remote settings. Using enormous emerging technologies from nano to macro scale, a large part of the excitement behind biomedical instrumentation is in its practical for producing innovation. It seems that one of the most promising opportunities for recent rapid diagnostics is found in point-of-care applications because a number of unmet needs can be fulfilled by cutting-edge technology due to their portability, rapid processing time, and flexibility in various settings. Development of a biomedical instrumentation system encompasses capturing user requirement or market demand, putting into specification with appropriate functional definition, implementing indispensable modules toward integration. Additionally, there is a set of common regulatory requirements for approval of developed biomedical instrumentation system. I will also reflect on lessons based on personal experiences during development of biomedical instruments.

Jungyoup (Jay) Han earned his Ph.D. degree from the Department of Electrical and Computer Engineering and Computer Science at University of Cincinnati. Prior to joining to the Ph.D program at University of Cincinnati, he worked as a research engineer in satellite control and system interface at Korea Aerospace Research Institute (KARI), South Korea for five years. He is currently at Siloam Biosciences, working as a Sr. Vice President of Product Development. His specialty is biomedical instrumentation and healthcare system development & integration towards clinical diagnostics. He has been leading development of biomedical instruments on a Point-of-Care Testing (POCT) system for beta-hCG and cardiac biomarker and interfacing between research and manufacturing. He is also building up Quality Management System (QMS) pursuing ISO certificate and FDA qualified facility under QSR (Quality System Regulation) for medical instruments. He earned his official certificate of PMP (Project Management Professional) showing his fully demonstrated experience and in-depth knowledge & skills to lead/direct project teams.

There are numerous situations, especially within the Department of Defense, where smaller HPC systems are specified and deployed to handle a moderately predictable workload containing less than a dozen or so special-purpose applications. Typically, these systems are designed in a naive way using rough high-level benchmarking and intuition. In most cases, this results in a system that runs the workload inefficiently, consuming precious resources and unnecessarily increasing the operational cost of the system.

Application-specific HPC involves designing heterogeneous systems with respect to the application workload. This is accomplished through profiling of the applications against the potential hardware candidates such as general-purpose CPUs, GPUs, and FPGAs. Resulting systems can dramatically increase the workload efficiency when considering execution time, cost of operation, power, size, and weight. In this presentation, the basics of application-specific HPC from an operational standpoint are covered. Additionally, case studies that exemplify this methodology are presented, the most thorough of which deals with all-pairs shortest paths graph processing for sparse graphs. Results of this study revealed that employing a CPU/FPGA heterogeneous system rather than a conventional CPU cluster can reduce weight by 88%, power consumption by 94%, and purchase cost by 30% for the same execution wall-time requirement.

The U.S. is currently increasing the use of renewable energy to decrease the reliance on imported fossil fuels and pollution. The development of the smart grid will facilitate the integration of renewable energy sources into the power grid. However, the stochastic nature of solar and wind energy resources complicates the integration of renewable generation applications. There is no significant control over wind and solar generation. Also, wind generation is often not correlated with load and may be even discarded when abundantly available. Solar generation is not available during nighttime. This problem can be viewed and addressed from two perspectives: feeder scale and grid scale. For feeder scale, we developed a genetic algorithm-based optimization method together with a two-point estimate method to minimize the installation costs of a hybrid power system including PV, wind units and energy storage to supply the feeder load. Load shifting functions have been added to the optimization problem to increase the flexibility and decrease the cost of the hybrid power system. Later, the reliability of the system is evaluated using Monte Carlo simulation. For the grid scale problem, a stochastic optimization method based on a particle swarm optimization (PSO) is proposed to minimize the sum of operation and congestion costs over a scheduling period energy. The proposed method optimally places and adequately sizes energy storage units to enhance the efficiency of wind integration. Also, the proposed method is used to carry out a cost-benefit analysis for the IEEE 24-bus system and determine the most economical technology. Moreover, a multi-stage multi-objective transmission network expansion planning (TNEP) methodology is developed which considers the investment cost, absorption of private investment and reliability of the system as the objective functions. This facilitates the integration of large-scale wind farms within a transmission grid. A Non-dominated Sorting Genetic Algorithm (NSGA II) optimization approach is used in combination with a probabilistic optimal power flow (POPF) to determine the Pareto optimal solutions considering the power system uncertainties. Using a compromise-solution method, the best final plan is then realized based on the decision maker preferences. The proposed methodology is applied to the IEEE 24-bus Reliability Tests System (RTS) to evaluate the feasibility and practicality of the developed planning strategy.

I received my MSC degree in Electrical Engineering from Sharif University of Technology, Tehran, Iran, and PhD degree from University of Nevada Reno, Nevada, USA in 2010 and 2014, respectively. Upon graduation, I served as an instructor at UNR for one semester in 2014. Currently, I am a research assistant at the Energy Management Department, NEC Labs America, Inc., Cupertino, CA. My research interests include power system operation and planning, power market, energy management, renewable energy and storage sizing, Electric vehicles, fault location and state estimation. I have been the author and co-author of 14 journal papers and 18 conference papers.

CMOS-based bioelectronics has been an invaluable instrument in biotechnology due to the need for high-throughput and high performance signal acquisition at extremely low cost. Emerging applications can be found in high-throughput gene sequencing as exemplified by the activities of leading biotechnology companies such as Oxford Nanopore Technologies and Ion Torrent at Life Technologies. In this talk, I will present the development and application of CMOS-based bioelectronics in biophysical and biomedical research. The CMOS manufacturing process is used to design and fabricate low-noise amplifier arrays and mixed-signal multiplexers. And this is followed by post- CMOS processing to monolithically integrate sensor electrodes on the surfaces of the CMOS chips. The monolithic CMOS bioelectronics eliminates a large percentage of the noise source by amplifying the signal at close proximity to the electrodes, and allows increased scalability and throughput by reducing the size of individual amplifiers. The application of monolithic CMOS bioelectronics in electrophysiology shows low noise performance—on the order of 100 fA at 2 kHz bandwidth—and accelerates the data collection from living cells by using a 320-electrode parallel recording array in a few sq mm silicon chip (25 by 40 sq micron per amplifier).

Brian Kim received his Bachelor of Science in Electrical and Computer Engineering, with summa cum laude, from Hanyang University, Seoul in 2008, and his Ph.D. in Biophysics from the School of Applied and Engineering Physics at Cornell University in 2013. His thesis work included system design of Monolithic CMOS Bioelectronics for biomedical instrumentation; he demonstrated massively parallelized signal acquisition with low noise and high sensitivity. He was a postdoctoral fellow at the University of California, Berkeley for a brief period in 2013 before he was referred to a Seattle-based biotechnology company, Stratos Genomics, where he continues to apply his expertise in CMOS circuit design for biomedical instrumentation as a Senior Electrical Engineer. He is currently involved in the development of a next-generation gene sequencing (NGS) technique.

Poisson high-dimensional data is an emerging type of data which often appears in various applications such as medical imaging, optical communications and topic modeling, etc. Being parallel to its Gaussian counterpart, the analysis and processing of this type of data call for new methods and theoretical foundations. To this end, I will introduce a framework how to effectively analyze the Poisson high-dimensional data. Specifically, several effective compressive schemes based on information-theoretic criteria and their associated theoretical properties will be introduced. Both the signal reconstruction and classification problems are discussed and several real applications of the proposed methods will be presented as well.

Liming Wang received the B.S. degree in electronic information engineering from the Huazhong University of Science and Technology, China, in 2006, the M.S. degree in mathematics and the Ph.D. degree in electrical and computer engineering from the University of Illinois at Chicago, both in 2011. Dr. Wang is currently a Postdoctoral Associate in the Department of Electrical & Computer Engineering, Duke University. From 2011 to 2012, he was a Postdoctoral Research Scientist in the Department of Electrical Engineering, Columbia University. His research interests include high-dimensional data processing, statistical signal processing, machine learning, compressive sensing and genomic signal processing.

Signal processing techniques, such as detection, estimation, and coding, have been used with great success to improve the quality of communications. With the recent rapid growth of wireless communications, the application of signal processing to the enhancement of spectral utilization is becoming increasingly important. This talk will focus on novel signal processing schemes involving identification and dynamic use of spectrum opportunities changing over time, frequency, and space. In particular, the importance of statistical signal processing for interference reduction will be emphasized and real-time DSP implementation will be presented. In the end, further extension of the work to the coexistence of future wireless systems as well as DSP applications in embedded and cyber-physical systems will be discussed.

Xiangwei Zhou received his Ph.D. degree in Electrical and Computer Engineering from Georgia Institute of Technology, Atlanta, Georgia, in 2011. He received his M.S. degree in Information and Communication Engineering from Zhejiang University, Hangzhou, China and his B.S. degree in Communication Engineering from Nanjing University of Science and Technology, Nanjing, China, in 2007 and 2005, respectively. Since 2013, Dr. Zhou has been with the Department of Electrical and Computer Engineering at Southern Illinois University Carbondale as an Assistant Professor. Prior to that, he was a Senior Systems Engineer with Marvell Semiconductor, Santa Clara, California, from 2011 to 2013. Dr. Zhou's general research interests include digital signal processing, wireless communications, and cross-layer optimization. He is a recipient of the best paper award at the 2014 International Conference on Wireless Communications and Signal Processing. Dr. Zhou has served as a technical program committee member for a number of international conferences and is currently serving on the editorial board of IEEE Transactions on Wireless Communications.

Advancements in digital signal processing and communications have spearheaded developments in many disciplines such as: 1.~power transmission, through the smart grid; 2.~agriculture, through sensor networks; 3.~transportation, through connected vehicular networks; 4.~robotics, through machine-to-machine communications; and 5.~medicine, through telemedicine and molecular communications, etc. This extensive use of wireless devices will consequently result in greater demand for both bandwidth and bandwidth efficiency. The former is anticipated to be addressed via the use of the millimeter-wave band, i.e., frequencies above 30 GHz, while the latter has been subject of continuous research that has resulted in new technologies, e.g.\ reconfigurable antennas, full duplex relaying, heterogeneous networks, and massive multi-input and multi-output (MIMO) systems. In the first part of this talk, we will focus on the role of digital signal processing in advancing these technologies and enhancing bandwidth utilization and efficiency at millimeter-wave frequencies. The second part of this talk, looks beyond the traditional applications of signal processing and communications, and focuses on their role in areas such as sensor networks via energy harvesting systems, and medicine through molecular communications.

Dr. Mehrpouyan received the B.Sc. honors degree from Simon Fraser University, Burnaby, Canada in 2004 and the Ph.D. degree from Queens University, Kingston, Canada, in Electrical Engineering in 2010. From Sep. 2010 to Aug. of 2012 he was a Post-Doc at Chalmers University of Technology. During this time, he visited the University of Luxembourg. Since 2012, he has been an Assistant Professor at California State University, Bakersfield. During his tenure at CSUB, he has been able to attract external funding to his research team as a PI and Co-PI. Dr. Mehrpouyan has received many awards, e.g., Natural Sciences and Engineering Research Council (NSERC)-Fellowship, British Columbia Wireless Innovation Award, IEEE Wireless Communication Letters Exemplary Reviewer Award, and more. He is an associate editor of IEEE Communication Letters and he has also served as a TPC member for IEEE Globecom, ICC, VTC, etc. Dr. Mehrpouyan has also been involved with industry leaders such as Ericsson AB, Blackberry, Societe Europeenne des Satellites (SES) ASTRA etc. His current research interests lie in the area of applied signal processing and physical layer of wireless communication systems, including millimeter-wave systems, reconfigurable antennas, energy harvesting systems, synchronization, channel estimation, and molecular communications.

Power electronics is the application of semiconductor devices for control and conversion of electrical energy. Such power converters play a vital role in power systems and can be found in any application that needs to modify one form of electrical energy such as; renewable energy integration, power transmission and power distribution. This talk discusses future trends in power electronics in modern 21st century power systems.

Energy saving is one of the important issues in today world. It has been estimated that with the widespread use of efficient and cost-effective power electronics technology, the world could see a 35% reduction in energy consumption. To integrate and optimize the power electronic converters for specific applications is necessary to further increase efficiency and reduce volume and cost. These concepts will be discussed in detail using ongoing research projects at Rockwell Automation and Ryerson University as examples. It will focus on the structure of high power converters in industrial motor drives and renewable energy integration. The challenges will be reviewed and the new power converters that have significant potential for commercialization will be discussed.

Mehdi Narimani received his B.S. and M.S degrees from Isfahan University of Technology (IUT), Isfahan, Iran and his PhD degree from University of Western Ontario, Canada, all in electrical engineering. He is currently a Postdoctoral Research Associate at the Department of Electrical and Computer Engineering at Ryerson University and Rockwell Automation Canada. He worked as a faculty member of Isfahan University of Technology from 2002 to 2009 where he supervised/assisted several industrial projects. He is the author/co-author of more than 50 journal and conference proceeding papers, four patents, more than 40 technical reports and co-author of one book in the area of power conversion and energy systems. His current research interests include power conversion, high power, application of power electronics in power systems, and renewable energy systems.

The modern electrical energy conversion systems demand low initial & maintenance cost, high efficiency, high power density, better power quality and high dynamic performance features to conserve electrical energy. These technical and operational requirements are often fulfilled majorly by: (i) semiconductor devices such as Insulated Gate Bipolar Transistor (IGBT) or Gate-Commutated Thyristor (GCT), (ii) power converter configuration with proper arrangement of semiconductor devices possibly with dc-link elements such as capacitors or inductors, and (iii) switch-mode operation through analog or digital control to turn-on and turn-off the semiconductor devices in a power converter.

This seminar provides a comprehensive review on the state-of-the-art and emerging technologies in power electronics and digital control schemes, and their applications to renewable energy (wind and photovoltaic), distributed generation, power quality, electric vehicles, and electric motor drives. The specific topics of this presentation include megawatt-level wind turbines, back-to-back connected converters and passive generator-side converters for low voltage and medium voltage operation of variable-speed wind energy conversion systems, model predictive control of wind energy systems, wind farm configurations based on HVDC technology, fault-ride through operation of wind energy systems, power converter configurations for low-, medium- and high-power photovoltaic energy systems, standalone and grid-connected distributed generation systems, power quality improvement in microgrid, high-power charging station and level III fast chargers for plug-in electric vehicles, and medium voltage motor drives.

Venkata Yaramasu received his B.Tech degree in electrical and electronics engineering from Jawaharlal Nehru Technological University, Hyderabad, India, in 2005, an M.E. degree in electrical engineering with specialization in power electronics from S. G. S. Institute of Technology and Science, Indore, India, in 2008, and Ph.D. degree in electrical engineering from Ryerson University, Toronto, Canada, in 2014. He is currently a Postdoctoral Research Fellow at the Laboratory for Electric Drive Applications and Research (LEDAR) and Center for Urban Energy (CUE), Ryerson University. His research interests include renewable energy (wind and photovoltaic), high power converters, electric vehicles, power quality, and model predictive control.

Dr. Yaramasu worked closely with Rockwell Automation, Toronto Hydro, Hydro One, Natural Sciences and Engineering Research Council of Canada (NSERC), Wind Energy Strategic Network (WESNet) and Connect Canada, and completed 8 industrial projects in Power Electronics, Electric Drives and Renewable Energy. He has published more than 30 peer-reviewed technical papers including 19 journal papers. He is currently authoring/coauthoring two books entitled “Model Predictive Control of Wind Energy Conversion Systems” and “Power Conversion and Control of Wind Energy Systems, Second Edition” for a possible publication with the Wiley-IEEE Press. He is recipient of Best Graduate Thesis Award (2014), Three Best Poster Awards (2010, 2013), Three Graduate Research Excellence Awards (2012, 2013, 2014), Three Student Research Awards (2010, 2012, 2013), Six Best Student Paper Awards (2003-2005) and Two Teaching Related Awards (2006, 2010).

In order to understand how to operate the physical dynamics of cyber physical systems (CPSs), we study the control of entropy (or equivalently uncertainty) via communications in CPSs. We consider the controller as the Maxwell's demon that decimates the system entropy. Due to the second law of thermodynamics, the system entropy cannot be spontaneously decreased. Therefore, to reduce the system entropy, the controller needs external information communicated from sensors. The following aspects of the proposed framework will be introduced: (a) For a finite state physical system in CPS, we derive upper and lower bounds for the communication requirements. The optimal designs of message mechanism and control policy are proposed. (b) For networked physical dynamics nodes (such as generators in a power grid), the entropy propagation is described using ordinary differential equations, in which the communication requirement due to quantization error is taken into account. (c) Networked CPS is condensed to the continuous space and the corresponding entropy evolution is described using partial differential equations (PDEs), for two special types of CPS dynamics. Solutions are obtained for the PDEs to characterize the propagation, decimation and generation of entropy in the field.

Husheng Li received the BS and MS degrees in electronic engineering from Tsinghua University, Beijing, China, in 1998 and 2000, respectively, and the Ph.D. degree in electrical engineering from Princeton University, Princeton, NJ, in 2005. From 2005 to 2007, he worked as a senior engineer at Qualcomm Inc., San Diego, CA. In 2007, he joined the EECS department of the University of Tennessee, Knoxville, TN, as an assistant professor. He is promoted to associate professor in 2013. His research is mainly focused on statistical signal processing, wireless communications, networking, smart grid and game theory. Dr. Li is the recipient of the Best Paper Awards of EURASIP Journal of Wireless Communications and Networks, 2005, EURASIP Journal of Advances in Signal Processing, 2015, IEEE ICC, 2011 and IEEE SmartGridComm 2012, and the Best Demo Award of IEEE Globecom, 2010.