Seminars: Spring 2018

Date      Speaker From Title
Feb 1 Leandros Tassiulas Yale University Optimizing The Network Edge For Flexible Service Provisioning
Feb 13 Zhao Yuan NYU Shanghai Presents Engineering Models, Algorithms and Applications of Convex Optimal Power Flow
Feb 15 Maggie Cheng NJIT Data Analytics Approach for Topology Change Detection and Identification in Power Systems
Feb 20 Yann LeCun Facebook AI Research & New York University Obstacles to Progress in Deep Learning and AI
Mar 19 Yoshua Bengio University of Montreal, Canada ECE Seminar Series on Modern Artificial Intelligence
Mar 22 Mehmet Toy Verizon Highly Available Cloud Services Architecture
Mar 29 Sibin Mohan University of Illinois at Urbana-Champaign Using Time as a Security Measure in Cyber-Physical Systems
Mar 30 Mei Chen State University of New York TBD
April 5 Stefano Soatto UCLA & AWS ECE Seminar Series on Modern Artificial Intelligence
April 6 Alberto Lamadrid Lehigh University Stochastic-Robust and Robust Programs for the Ramp-Constrained Economic Dispatch Problem with Uncertain Renewable Energy
April 12 Nambi Seshadri Past, Present and Future of Wireless Communications
May 4 Vladimir Vapnik Columbia University & Facebook AI Research ECE Seminar Series on Modern Artificial Intelligence

 

Optimizing The Network Edge For Flexible Service Provisioning

Speaker: Leandros Tassiulas, Yale University
Time: 11:00 am - 12:00 pm Feb 1, 2018
Location: 2 MetroTech Center, 10th floor, Room 10.099, Brooklyn, NY

Abstract: The virtualization of network resources provides unique flexibility in service provisioning in most levels of the network stack. Softwarization of the network control and operation (SDN) is a key enabler of that development. Starting from the network core, SDN is a dominant trend in the evolution of network architectures with increased emphasis recently on the network edge. I will present some recent results in this area starting with a study on migration from legacy networking to SDN enabled network modules. The trade-off between the benefits of SDN upgrades and the cost of deployment is addressed and captured by an appropriate sub-modular function that allows to optimize the penetration pace of the technology. Validation on some real world network topologies and traffic matrices will be presented as well. Then we move our attention to the network periphery. A wireless multi-hop extension at the network edge is considered and the problem of enabling SDN is addressed via replication of SDN controllers. The delay constraints of the controlled data-path elements is appropriately modeled and the problem of locating the controllers is addressed via optimization and a proof-of concept implementation. An alternate approach is considered then for the wireless network where we assume coexistence of SDN enabled components with network islands operating under distributed adhoc routing protocols. The trade-off of the coexistence is studied and the impact of SDN penetration is evaluated. Some paradigms of collaborative network services are presented finally as they are enabled by the above architectural evolution.

About the Speaker: Leandros Tassiulas is the John C. Malone Professor of Electrical Engineering at Yale University. His research interests are in the field of computer and communication networks with emphasis on fundamental mathematical models and algorithms of complex networks, architectures and protocols of wireless systems, sensor networks, novel internet architectures and experimental platforms for network research. His most notable contributions include the max-weight scheduling algorithm and the back-pressure network control policy, opportunistic scheduling in wireless, the maximum lifetime approach for wireless network energy management, and the consideration of joint access control and antenna transmission management in multiple antenna wireless systems. Dr. Tassiulas is a Fellow of IEEE (2007). His research has been recognized by several awards including the IEEE Koji Kobayashi computer and communications award (2016), the inaugural INFOCOM 2007 Achievement Award "for fundamental contributions to resource allocation in communication networks," several best paper awards including the INFOCOM 1994, 2017 and Mobihoc 2016, a National Science Foundation (NSF) Research Initiation Award (1992), an NSF CAREER Award (1995), an Office of Naval Research Young Investigator Award (1997) and a Bodossaki Foundation award (1999). He holds a Ph.D. in Electrical Engineering from the University of Maryland, College Park (1991). He has held faculty positions at Polytechnic University, New York, University of Maryland, College Park, University of Ioannina and University of Thessaly, Greece.

Models, Algorithms and Applications of Convex Optimal Power Flow

Speaker: Zhao Yuan, NYU Shanghai Presents Engineering
Time: 3:00 pm - 5:00 pm Feb 13, 2018
Location: 2 MetroTech Center, 10th floor, Room 10.099, Brooklyn, NY

Abstract: Optimal power flow (OPF) is the fundamental mathematical model to optimize the operation of power system. We propose second-order cone programming (SOCP) convex OPF models which are reformulated from the original nonconvex OPF model. The advantage of convex OPF over nonconvex OPF in terms of global optimality over local optimality is obvious. We then propose a modified Benders decomposition algorithm (M-BDA) to efficiently solve large-scale OPF model by decomposition and parallelization. The feasibility and optimality of the proposed M-BDA are analytically and numerically proved. Finally the applications of convex OPF in distribution locational marginal pricing, wind power integration and super grid coordinated energy dispatch are demonstrated.

About the Speaker: PhD Candidate, Erasmus Mundus Joint PhD Degree: KTH Royal Institute of Technology, Sweden Comillas Pontifical University, Spain Delft University of Technology, Netherlands.

Data Analytics Approach for Topology Change Detection and Identification in Power Systems

Speaker: Maggie Cheng, NJIT
Time: 11:00 am - 12:00 pm Feb 15, 2018
Location: 2 MetroTech Center, 10th floor, Room 10.099, Brooklyn, NY

Abstract: An undetected topology change caused by overgrown trees is the root cause for the 2003 large scale blackout. The discrepancy between the actual topology of the power grid and the graph model used in state estimation is considered a topology error. Topology error was a reason that the WLS-based state estimation failed to converge and report alarms. This presentation will cover a non-WLS approach for topology error detection, and a learning framework to further identify the line outage. Time series analysis of multi-stream PMU data is used for feature extraction, and several statistical learning algorithms are trained based on these features. The line outage identification process is not tightly coupled with power flow analysis and state estimation as these tasks require detailed and accurate information about the system matrices, but can achieve a high detection rate comparable to the previous work that involves solving power flow and state estimation equations. Both single line outage and multiple simultaneous line outages are considered.

About the Speaker: Maggie Cheng is an associate professor in the Martin Tuckman School of Management in New Jersey Institute of Technology. She received a Ph.D. degree in Computer Science from the University of Minnesota at the Twin Cities in 2003. She was a faculty member in the department of Computer Science in Missouri University of Science and Technology before she joined NJIT in 2016. Her research focuses on data analytics methodology and optimization in complex network systems, and has a wide spectrum of topics including data analytics for cyber-physical systems, intrusion and attack detection in communication networks, user cyber behavioral analysis, network tomography, fault diagnosis, system level vulnerability analysis, as well as social network analysis on link formation, information propagation, and community detection. Her research has been sponsored by National Science Foundation, Department of Energy, Department of Education, Department of Transportation, and UM-System Research Board. She served as a guest editor of the journal of Combinatorial Optimization, associate editor of Nano Communication Networks Journal, and is currently on the editorial board of the International Journal of Sensor Networks. She served as an organizer and member of technical program committees in multiple international conferences.

Obstacles to Progress in Deep Learning and AI

Speaker: Yann LeCun, Facebook AI Research & New York University
Time: 10:00 am - 11:00 am Feb 20, 2018
Location: Pfizer Auditorium, 5 MetroTech Center, Brooklyn, NY, US

Abstract: Deep learning is causing revolutions in computer perception and natural language understanding. But almost all these successes largely rely on supervised learning, where the machine is required to predict human-provided annotations. For game AI, most systems use model-free reinforcement learning, which requires too many trials to be practical in the real world. But animals and humans seem to learn vast amounts of knowledge about how the world works through mere observation and occasional actions. Good predictive world models are an essential component of intelligent behavior: with them, one can predict outcomes and plan courses of actions. One could argue that prediction is the essence of intelligence. Good predictive models may be the basis of intuition, reasoning and "common sense", allowing us to fill in missing information: predicting the future from the past and present, the past from the present, or the state of the world from noisy percepts. After a brief presentation of the state of the art in deep learning, some promising principles and methods for predictive learning will be discussed.

ECE Seminar Series on Modern Artificial Intelligence

Speaker: Yoshua Bengio, University of Montreal, Canada
Time: 10:00 am - 11:00 am Mar 19, 2018
Location: Pfizer Auditorium, 5 MetroTech Center, Brooklyn, NY, US

Abstract: The Seminar Series in Modern Artificial Intelligence begins a new tradition at New York University. The series will be held at NYU Tandon School of Engineering and is hosted by the Department of Electrical and Computer Engineering. Organized by Professor Anna Choromanska, the series aims to bring together faculty and students to discuss the most important research trends in the world of AI. The speakers include world-renowned experts whose research is making an immense impact on the development of new machine learning techniques and technologies and helping to build a better, smarter, more-connected world.

Using Time as a Security Measure in Cyber-Physical Systems

Speaker: Sibin Mohan, University of Illinois at Urbana-Champaign
Time: 11:00 am - 12:00 pm Mar 29, 2018
Location: 2 MetroTech Center, 10th floor, Room 10.099, Brooklyn, NY

Abstract: Applications in the cyber-physical systems (CPS) domain are increasingly using commodity-off-the-shelf (COTS) components and are being interconnected for efficiency, better monitoring, and improved functionality. Traditionally, such systems were immune to software security attacks, but the increase in COTS components and interconnectivity are opening up new attack surfaces. Recent events, such as the Stuxnet incident, have shown the serious damage that can result from successful attacks. This can be particularly destructive for systems that have safety-critical constraints (e.g. avionics, automobiles, UAVs, power grids, etc.). In this talk, I intend to demonstrate how timing information can be crucial in the security of CPS especially when such systems have real-time properties.

In the first piece of work, I will demonstrate how timing information can be used to attack such systems – to leak critical information (e.g. the precise schedule and timing properties of tasks). In the second part of the talk, I will demonstrate multiple techniques that can deter attackers, both from the aforementioned attacks and also zero-day attacks that modify behavioral properties of such systems. I will also touch upon other timing-based defensive mechanisms that improve the overall security of safety-critical cyber-physical systems – both at design time, as well as retroactively (for legacy systems).

About the Speaker: Sibin Mohan is a Research Assistant Professor in both, the Dept. of Computer Science as well as the Information Trust Institute (ITI) at the University of Illinois. He completed his Ph.D. and M.S. in Computer Science from North Carolina State University in 2008 and 2004 respectively. His undergraduate degree was in Computer Science and Engineering from Bangalore University, India in 2001.

Sibin’s research interests are in the area of systems and security. His current research efforts include the integration of security in real-time embedded systems, intrusion detection in cyber-physical systems with real-time properties, secure cloud computing and the use of software defined networking (SDN) in safety-critical systems. In the past, he has done extensive work on the analysis of real-time and embedded systems and the development of system composition and safety techniques for avionics and medical devices.

He was previously a postdoctoral scholar in the Computer Science department at UIUC. In the past, he has also worked in Hewlett Packard’s India Software Operations.

ECE Seminar Series on Modern Artificial Intelligence

Speaker: Stefano Soatto
Time: 10:00 am - 11:00 am Apr 5, 2018
Location: Pfizer Auditorium, 5 MetroTech Center, Brooklyn, NY, US

Abstract: The Seminar Series in Modern Artificial Intelligence begins a new tradition at New York University. The series will be held at NYU Tandon School of Engineering and is hosted by the Department of Electrical and Computer Engineering. Organized by Professor Anna Choromanska, the series aims to bring together faculty and students to discuss the most important research trends in the world of AI. The speakers include world-renowned experts whose research is making an immense impact on the development of new machine learning techniques and technologies and helping to build a better, smarter, more-connected world.

ECE Seminar Series on Modern Artificial Intelligence

Speaker:Vladimir Vapnik
Time: 10:00 am - 11:00 am May 4, 2018
Location: Pfizer Auditorium, 5 MetroTech Center, Brooklyn, NY, US

Abstract:The Seminar Series in Modern Artificial Intelligence begins a new tradition at New York University. The series will be held at NYU Tandon School of Engineering and is hosted by the Department of Electrical and Computer Engineering. Organized by Professor Anna Choromanska, the series aims to bring together faculty and students to discuss the most important research trends in the world of AI. The speakers include world-renowned experts whose research is making an immense impact on the development of new machine learning techniques and technologies and helping to build a better, smarter, more-connected world.

Highly Available Cloud Services Architecture

Speaker:Mehmet Toy, Verizon
Time: 11:00 am - 12:00 pm Mar 22, 2018
Location: 2 MetroTech Center, 10th floor, Room 10.099, Brooklyn, NY

Abstract:Cloud Services Architecture has been defined by Open Cloud Connect (OCC) standards organization which was merged with Metro Ethernet Forum (MEF) in 2016. Further work in this area has been initiated in ETSI Network Function Virtualization (NFV) and MEF.

In my talk, I will describe Cloud Services and their architecture, interfaces between a user and Cloud Service Provider, and interfaces between Cloud Service Providers. In addition, I will describe the high availability layers and fault management architecture of virtualized systems and services and relationships between failure recovery timers of the layers.

 

About the Speaker: Mehmet Toy holds Ph.D degree in Electrical and Computer Engineering from Stevens Institute of Technology, Hoboken, NJ, and M.S and B.S degrees in Electronics and Communications from Istanbul Technical University, Istanbul, Turkey.

He is a Distinguished Member of Technical Staff in Verizon Communications and involved in the implementation, testing and standards for SDN, NFV and Cloud Services.

Prior to this position, Dr. Toy has held senior technical and management positions in several well-known companies and startups including Comcast, Intel Corp., Verizon Wireless, Fujitsu Network Communications, AT&T Bell Labs and Lucent Technologies. He has also been a tenure-track faculty and adjunct professor in several universities including Stevens Institute of Technology, New Jersey Institute of Technology, Worchester Polytechnic Institute, and University of North Caroline at Charlotte.

Dr. Toy contributed to research, development and standardization of Cloud, Overlay, Self-Managed, SDN and Virtualized Commercial Networks and Services, Carrier Ethernet, IP Multimedia Systems (IMS), Optical, IP/MPLS, Wireless, ATM, and Signal Processing technologies. He holds a patent and has six pending patent applications. He has also published numerous articles, seven books and a video tutorial in these areas. Two of his books are being used as college text books and one of them is translated to Turkish.

Dr. Toy has served in the Open Cloud Connect Board, the IEEE Network Magazine Editorial Board, the IEEE Communications Magazine as a Guest Editor, the IEE-USA and the IEEE ComSoc in various capacities. He has received various awards from Comcast, AT&T Bell Labs and IEEE-USA for his accomplishments in these fields. He is currently a Sr. Member of IEEE and chair person of the IEEE ComSoc Cable Networks and Services sub-committee, and serves in MEF and ETSI NFV.

Stochastic-Robust and Robust Programs for the Ramp-Constrained Economic Dispatch Problem with Uncertain Renewable Energy

Speaker:Alberto J. Lamadrid, Lehigh University
Time: 11:00 am - 12:00 pm Apr 6, 2018
Location: TBD

Abstract: The inherent uncertainty of renewable energy sources (RES) makes the solution to the electricity network’s associated economical dispatch (ED) problem with network constraints challenging. In particular, the uncertainty in the power output of RES requires conventional generation units to ramp up and down more frequently to maintain the power balance and the reliability of the system. Typically, the RES power output uncertainty is modeled in ED problems by considering its potential future scenarios. However, this leads to an optimization problem that is difficult to solve for real-sized networks. Here, we present two proposals for this problem.

In the first one, we consider the uncertainty of RES and the consequent ramping of conventional generation via a robust reformulation of the problem. In particular, we show that in typical instances of the ED problem, the associated deterministic formulation of the robust problem can be solved efficiently for medium scale constrained electricity networks even when the underlying uncertainty distribution is not normal. Moreover, by comparing the proposed robust solutions to the ED problem with the typical scenario optimization approach, we show that the former solutions result on dispatch solutions that require less ramping than the later solutions, with little trade-off on the long-term expected costs of the dispatch. These results also provide insights about how RES penetration affects cost and dispatch policies in the electricity network. To illustrate our results, we present relevant numerical experiments on IEEE test networks.

In the second, We present an implementation of a two-stage security constrained unit commitment program with a recourse to dispatch the electricity system using a hybrid method to determine reserves for the System Operator (SO). This works is related to the stochastic optimization literature, with an emphasis on the economic determination and appraisal of different types of balancing reserves. The recourse decision balances the power dispatches, subject to the endogenously determined reserves. We study the implementation of the second settlement over a set of possible realized trajectories, as part of the implementation of a receding (rolling) horizon settlement.

About the Speaker: Alberto J. Lamadrid (Ph.D. Applied Economics and Management, Cornell University, 2012; M.A. Economics NYU, 2004; B.Sc. Electrical Engineering, Universidad de los Andes, Colombia, 2001) is an assistant professor with a joint appointment in the Economics Department and in the Industrial and Systems Engineering Department at the P.C. Rossin College of Engineering and Applied Science at Lehigh University. He is also a member of the Integrated Networks for Electricity Cluster at Lehigh. He has participated in NSF funded grants, as well as other awards funded by the Department of Energy, The Pennsylvania Infrastructure Technology Alliance and EPRI. His research interests are in electricity markets, power systems, and energy economics. He has worked on topics involving multi-period stochastic optimization in electrical networks, adoption of renewable energy sources and the valuation of power infrastructure assets.

Past, Present and Future of Wireless Communications

Speaker:Nambi Seshadri
Time: 11:00 am - 12:00 pm Apr 6, 2018
Location: MakerEvent Space in 6MTC, Rogers Hall