Below is the IEMS Fall 2009 seminar series schedule, with a general area/topic of the talk. Please mark your calendar accordingly. All talks are from 4:00 to 5:00 in Tech Room M228.
Talk information and video presentations will be posted as soon as the content is made available.
For more information on the seminar series, please contact Benjamin Armbruster (armbruster@northwestern.edu).
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- Tuesday, September 22rd, 2009 - Network and Combinatorial Optimization; Operations Research; Logistics
James Orlin, Massachusetts Institute of Technology - Title: A Faster and Simpler Algorithm for Computing Market Equilibrium
Abstract: Devanur, Papadimitriou, Saberi, and Vazirani recently published the first polynomial time algorithm for computing an equilibrium for the linear utilities case of the market model defined by Fisher. Here we provide a much faster and simpler algorithm. In addition, we provide the first strongly polynomial time algorithm for computing the equilibrium. (This latter algorithm is not as simple.) We describe our algorithms from an economic perspective in a way that is accessible to a general audience. This work is joint with Mehdi Ghiyasvand.
Bio: James Orlin specializes in network and combinatorial optimization. He has helped develop improved solution methodologies in airline scheduling, railroad scheduling, logistics, network design, telecommunications, inventory control, and marketing. Together with MIT Sloan colleague Thomas L. Magnanti and Ravindra K. Ahuja, he has written the award-winning text Network Flows: Theory, Algorithms, and Applications (Prentice Hall, 1993). To see video of this presentation, please click here. - Tuesday, September 29th, 2009 - Computational Epidemiology, Computational Economics
Madhav Marathe, Virginia Bioinformatics Institute - Title: Epidemics in Co-evolving Networks: The Role of Individual behaviors and Public Policies
Abstract: Complex Networks are pervasive in our society. Realistic biological, information, social and technical networks share a number of unique features that distinguish them from physical networks. Examples of such features include: irregularity, time-varying structure, heterogeneity among individual components and selfish/cooperative game-like behavior by individual components. Furthermore, the network structure, the dynamical process on the network and the behavior of constituent agents co-evolve over time. The size and heterogeneity of these networks, their co-evolving nature and the technical difficulties in applying dimension reduction techniques commonly used to analyze physical systems makes reasoning, prediction and controlling of these networks even more challenging. Recent quantitative changes in high performance and wireless computing capability have created new opportunities for collecting, integrating, analyzing and accessing information related to such large complex networks. The advances in network and information science that build on this new capability provide entirely new ways for reasoning and controlling these networks. Together, they enhance our ability to formulate, analyze and realize novel public policies pertaining to these complex networks. The talk will focus on elements of network and information science requires to support policy informatics as it pertains to epidemic processes in co-evolving social and wireless networks. Understanding these epidemiological processes is of immense societal importance. Additionally they serve as excellent "model organisms" for developing a theory of co-evolving complex networks. Perhaps more intriguing, recent advances in wireless communications provide compelling reasons for studying these networks together. I will discuss this possibility in my concluding remarks.
Bio: Madhav Marathe is a professor of Computer Science and deputy director of the Network Dynamics and Simulation Science Laboratory. He obtained his Bachelor of Technology degree in 1989 in Computer Science and Engineering from the Indian Institute of Technology, Madras, and his Ph.D. in 1994 in Computer Science from the University of Albany. Before coming to Virginia Tech in 2005, he worked in the Basic and Applied Simulation Science group (CCS-5) in the Computer and Computational Sciences division at Los Alamos National Laboratory where he was team leader in a theory-based, advanced simulation program to represent, design, and analyze extremely large socio-technical and critical infrastructure systems. He has publishsed more than 150 research articles in peer reviewed journals, conference proceedings, and books, and has over eight years of experience in project leadership and technology development, specializing in population dynamics, telecommunication systems, epidemiology, design and architecture of the data grid, design and analysis of algorithms for data manipulation, design of services-oriented architectures, and socio-technical systems.
- Tuesday, October 6th, 2009 - Computer Science
Michael Friedlander, University of British Columbia - Title: Algorithms for Large-scale Sparse Reconstruction
Abstract: Many signal-processing applications seek to approximate a signal as superposition of only a few elementary atoms drawn from a large collection. This is known as sparse reconstruction. The theory of compressed sensing allows us to pose sparse reconstruction problems as structured convex optimization problems. I will discuss the role of duality in revealing some unexpected and useful properties of these problems, and will show how they lead to practical, large-scale algorithms. I will also describe some applications of the resulting algorithms.
Bio: Michael Friedlander received his PhD in Operations Research from Stanford University in 2002, and his BA in Physics from Cornell University in 1993. His research is primarily in large-scale constrained optimization. From 2002-2004 he was the Wilkinson Fellow in Scientific Computing at Argonne National Laboratory. He is currently Associate Professor of Computer Science at the University of British Columbia, where he has been since 2004.
- Tuesday, October 20th, 2009 – The intersection of probability and optimization theory, and in particular in the optimization and control of large-scale stochastic systems
Ciamac Moallemi, Columbia University - Title: Approximate Dynamic Programming via a Smoothed Linear Program
Abstract: We present a novel linear program for the approximation of the dynamic programming cost-to-go function in high-dimensional stochastic control problems. LP approaches to approximate DP have typically relied on a natural`projection' of a well studied linear program for exact dynamic programming. Such programs restrict attention to approximations that are lower bounds to the optimal cost-to-go function. Our program---the `smoothed approximate linear program'---is distinct from such approaches and relaxes the restriction to lower bounding approximations in an appropriate fashion while remaining computationally tractable. Doing so appears to have several advantages: First, we demonstrate substantially superior bounds on the quality of approximation to the optimal cost-to-go function afforded by our approach. Second, experiments with our approach on a challenging problem (the game of Tetris) show that the approach outperforms the existing LP approach (which has previously been shown to be competitive with several ADPalgorithms) by an order of magnitude. This is joint work with Vijay Desai (Columbia) and Vivek Farias (MIT).
Bio: Ciamac Moallemi is an Assistant Professor at the Graduate School of Business of Columbia University, where he has been since 2007. He received SB degrees in Electrical Engineering & Computer Science and in Mathematics from the Massachusetts Institute of Technology (1996). He studied at the University of Cambridge, where he earned a Certificate of Advanced Study in Mathematics, with distinction (1997). He received a PhD in Electrical Engineering from Stanford University (2007). Prior to his doctoral studies, he developed quantitative methods in a number of entrepreneurial ventures, as a founder of a computer security software startup, in an early stage drug discovery startup, and as a partner of a fixed-income arbitrage hedge fund. He is a member of the IEEE and INFORMS. He is the recipient of a British Marshall Scholarship (1996) and a Benchmark Stanford Graduate Fellowship (2003).
- Tuesday, October 27th, 2009 - Integrated Topology Control and Routing in Wireless Sensor Network Design for Prolonged Network Lifetime
Halit Uster - Title: Integrated Topology Control and Routing in Wireless Sensor Network Design for Prolonged Network Lifetime
Abstract: A Wireless Sensor Networks (WSN) can be deployed in inhospitable environments, difficult-to-reach terrains, and wild habitats such as war zones, oceans, the poles, deserts, and rain forests to monitor and observe natural, environmental, and climate-related phenomena including temperature, pressure, humidity, vibration, light, chemical and biological agents, etc. The most distinguishing characteristic of a WSN is the fact that its sensors have finite and non-renewable energy resources. In this talk, we consider integrated topology control and routing issues in data gathering WSNs and address the problem of prolonging network lifetime until next sensor deployment. We suggest a policy to be employed in each period of a deployment cycle and computationally examine its efficiency in prolonging network lifetime against two other commonly employed approaches. We present mathematical models and a general efficient solution procedure that is applicable to all the three cases. We determine that the proposed policy has attractive properties and exhibits very good performance in extending network lifetime. For the proposed policy, we also discuss further parallelization of the solution approach along with additional cut inequalities as well as a Benders Decomposition approach. (Research supported by National Science Foundation under grant CMMI-0428831).
Bio: Halit Üster is an Associate Professor in the Department of Industrial and Systems Engineering at Texas A&M University. He holds a Ph.D. in Management Science/Systems from McMaster University, Ontario, Canada. His research interests are in the areas of logistics, design of networked systems, and applied optimization. His publications appeared in Computers and Operations Research, European Journal of Operational Research, Interfaces, IIE Transactions, Naval Research Logistics, and Transportation Science among others. He is visiting the IEMS Department at Northwestern University during 2009-2010 academic year where he has been named Eshbach Scholar in the McCormick School of Engineering & Applied Science for Fall Quarter 2009.
- Tuesday, November 3rd, 2009 – Supply Chain and Information Systems
Russell R. Barton, Penn State University - Title: A Framework for Monitoring Supply Chain Execution
Abstract: Real-time sensor data, particularly RFID and GPS data, provides new possibilities to monitor the execution of supply chain processes. This talk examines a basic framework for examining the timeliness and correctness of the movement of items and/or transactions through a sequence of supply chain events. The nature of the data poses special issues for statistical process control and process capability analysis.
Bio: Russell R. Barton is a professor in the Department of Supply Chain and Information Systems at Penn State University. He also serves at the Smeal College of Business Co-Director for a one-year Master of Manufacturing Management degree program that is jointly offered with the College of Engineering. He received a B.S. degree in Electrical Engineering from Princeton and M.S. and Ph.D. degrees in Operations Research from Cornell. Before entering academia, he spent twelve years in industry. He was program chair for the 2007 Winter Simulation Conference, and he serves on the Advisory Board for the Quality, Statistics and Reliability Section of INFORMS. His research interests include applications of statistical and simulation methods to system design and to product design, manufacturing and delivery.
- Tuesday, November 10th, 2009 – Financial Mathematics, Stochastic Control, Quantitative Finance
Thaleia Zariphopoulou, Oxford University - Title: A New Approach for Investment Performance Measurement
Abstract: A new method for measuring the performance of investment policies will be introduced. Optimality of investment strategies will be associated with a stochastic partial differential equation (spde). The novel concept of performance volatility, as the driver
to this spde, will be presented. Examples of performance volatility processes, modeling different numeraires, benchmarks and market views, will be presented.
Bio: Professor Thaleia Zariphopoulou is the first holder of the Man Professorship of Quantitative Finance at the University of Oxford. Previously, Professor Zariphopoulou was the VF Neuhaus Centennial Professor at the University of Texas at Austin. At UT-Austin, Professor Zariphopoulou held a joint appointment between the Department of Mathematics and the Department of Information, Risk and Operations Management at the Red McCombs School of Business. She is an expert in quantitative finance, portfolio management and stochastic optimization. She was President of the Bachelier Finance Society from 2006-2008; and also sits on the editorial board of five academic journals in financial mathematics and quantitative finance. To see video of this presentation, please click here. - Tuesday, November 17th, 2009 – The development of models and solution methods for decision making under uncertainty, in particular, stochastic programming models and algorithmic methods for their solution
Dr. Julie Higle, Ohio State University - Title: How Industrial Engineers Impact the World
Abstract: Industrial engineering isn't quite as tangible as other types of engineering. The industrial engineering function evolves from a viewpoint and training that transcends an amazing breadth of "businesses". This makes it hard to nail down a simplistic sound-bite-sized descriptor that can be applied to industrial engineering. Because of this, the contributions of industrial engineers often fail to capture the mainstream imagination. This seminar will explore the impact of industrial engineering -- past, present, and future.
Bio:Professor Julie Higle joined the faculty of Systems and Industrial Engineering at the University of Arizona in 1985, after completing her PhD in IOE at the University of Michigan. Her primary research has been in models algorithms for decision making under uncertainty, with an emphasis on stochastic programming. She is currently the chair of the department of Integrated Systems Engineering at THE Ohio State University, and Sr. Vice President for Academics of the Institute of Industrial Engineers. - Monday, November 23rd, 2009 -
Robert Smith, National Science Foundation - Title: A Fictitious Play Approach to Complex Systems Optimization
Abstract: Complex systems consisting of a large number of interacting components are in practice increasingly modeled through computer simulations rather than via traditional equation based approaches. The resulting model typically allows for little or no structural assumptions on the form of the objective function or constraints, thus posing a challenging optimization problem. We explore in this talk a novel optimization paradigm inherited from game theory that animates the components of the system within a non-cooperative game of identical interest. The optimizations take place though individual best replies of the players, thus vastly reducing the dimensionality of the optimization problems solved (the components joint interactions are reflected indirectly through their shared objective function). We will illustrate the approach by discussing an application to intelligent transportation systems. Opportunities for NSF funding in Operations Research will be discussed at the end of the talk.
Bio: Robert L. Smith is Director of the Operations Research Program at NSF. Dr. Smith received his Ph.D. in Engineering Science from the University of California at Berkeley where he held an NSF Fellowship. He holds a bachelors degree in Physics from Harvey Mudd College and an MBA from Berkeley. He is on leave from the University of Michigan in Ann Arbor where he is the Altarum/ERIM Russell D. O'Neal Professor of Engineering. He is the recipient of the first Altarum/ERIM Russell D. O'Neal Professorship of Engineering at the University of Michigan. He has also been honored with the Distinguished Faculty Achievement Award from the University of Michigan, the College of Engineering Research Excellence Award, the Industrial and Operations Engineering Award for Outstanding Accomplishment, an Outstanding Teacher Award from the Michigan Student Assembly, and National Science Foundation Fellowship. He is a Fellow of the Institute for Operations Research and the Management Sciences. Professor Smith teaches courses in dynamic programming and stochastic processes. He has supervised the doctoral research of twenty-eight students since 1984. At the University of Michigan, he serves as Director of the Dynamic Systems Optimization Laboratory. The Laboratory research is directed toward the modeling and analysis of dynamical systems over time. Dr. Smith worked earlier at Bell Laboratories in the Network Planning Department where he developed models and algorithms for optimal routing of communications traffic. He is an Associate Editor of Operations Research and past Associate Editor of Management Science, and is the author of nearly one hundred peer reviewed publications.
- Tuesday, December 1st, 2009 -
Ahmad Faruqui, Principal – The Brattle Group - Title: TBA
Abstract: TBA
Bio:TBA
