Monday, February 27

3108 Etcheverry Hall, 3:30 p.m. - 5:00 p.m.

Abstract: Risk pooling and sharing are commonly used strategies for firms to mitigate their risks due to various uncertainties. For example, retailers may serve different demand streams using centralized inventory to reduce inventory cost; wind power producers may form coalitions to reduce aggregate power output variability; and insurance companies can share risk in reinsurance market to diversify their risk. In these settings, a key issue is how to design sharing mechanisms to fairly allocate the cost and/or risk among the players. In this talk, I will cast this problem into cooperative game theory framework and propose fair sharing mechanisms using duality theory in optimization. I will also identify conditions under which the sharing mechanisms have certain monotonicity property.
 
Xin Chen is a professor, an Abel Bliss Faculty Scholar and the Jerry S. Dobrovolny Faculty Scholar at the University of Illinois at Urbana-Champaign. He obtained his PhD from MIT in 2003, MS from Chinese Academy of Sciences in 1998 and BS from Xiangtan University in 1995. His research interest lies in optimization, data analytics, revenue management and supply chain management. He received the Informs revenue management and pricing section prize in 2009. He is the coauthor of the book “The Logic of Logistics: Theory, Algorithms, and Applications for Logistics and Supply Chain Management (Second Edition & Third Edition, 2005 & 2014)”.

 

Monday, March 6

3108 Etcheverry Hall, 3:30 p.m. - 5:00 p.m.

Professor Guo is the Coleman Fung Chair in Financial Modeling at UC Berkeley and specializes in stochastic control, semi-martingale and filteration expansions, credit risk, and (ir)reversible investment.

 

Monday, March 13

3108 Etcheverry Hall, 3:30 p.m. - 5:00 p.m.

Ken Goldberg is an artist, inventor, and UC Berkeley Professor. His home department is Industrial Engineering and Operations Research, with secondary appointments in EECS, Art Practice, the School of Information, and Radiation Oncology at the UCSF Medical School. Ken is Director of the CITRIS "People and Robots" Initiative and the UC Berkeley AUTOLAB where he and his students pursue research in geometric algorithms and machine learning for robotics and automation in surgery, manufacturing, and other applications. Ken developed the first provably complete algorithms for part feeding and part fixturing and the first robot on the Internet. Despite agonizingly slow progress, Ken persists in trying to make robots less clumsy. He has over 200 peer-reviewed publications and eight U.S. Patents. He co-founded and served as Editor-in-Chief of the IEEE Transactions on Automation Science and Engineering. Ken's artwork has appeared in 70 exhibits including the Whitney Biennial and films he has co-written have been selected for Sundance and nominated for an Emmy Award. Ken was awarded the NSF PECASE (Presidential Faculty Fellowship) from President Bill Clinton in 1995, elected IEEE Fellow in 2005 and selected by the IEEE Robotics and Automation Society for the George Saridis Leadership Award in 2016. He lives in the Bay Area and is madly in love with his wife, filmmaker and Webby Awards founder Tiffany Shlain, and their two daughters. He is fiercely protective of his family, his students, and his frequent-flier miles.

 

Monday, March 20

3108 Etcheverry Hall, 3:30 p.m. - 5:00 p.m.

As the share of renewable energy becomes an increasing part of electricity generation, electric vehicles (EVs) have the potential to be used as virtual power plants (VPP) to provide reliable back-up power. This could generate additional profits for EV carsharing rental firms. We design a computational control mechanism for VPPs that decide whether EVs should be charging, discharging, or rented out. We validate our computational design by developing a discrete-event simulation platform based on real-time GPS information from 1,100 electric cars from Daimlers carsharing service Car2Go in San Diego, Amsterdam, and Stuttgart. We compute trading prices (bids) for participating in secondary control reserve markets and investigate what effect the density of charging infrastructure, battery technology, and rental demand for vehicles have on the pay-off for the carsharing fleet. We show that VPPs can create sustainable revenue streams for electric vehicle carsharing fleets without compromising their rental business.

 

 
Monday, April 3

3108 Etcheverry Hall, 3:30 p.m. - 5:00 p.m.

In recent years, personal location data is continuously captured by mobile devices, GPS chips and other sensors. Such data provides a unique learning opportunity on individuals’ mobility behavior that may be used for various applications in transportation, marketing, homeland security and smart cities. Nonetheless, modeling such data poses new challenges related to data volume, diversity, inhomogeneity and the required granularity level. In this talk, we will address a real ‘smart city’ use-case and cover some of its associated opportunities and challenges. We will present a new set of mobility-behavior models that generalizes Markov Chains and Variable-Order Bayesian Networks. We will discuss how they can be used in different smart city applications such as pattern recognition, anomaly detection, clustering and classification.

Bio:
Irad Ben-Gal is a full professor in the Department of Industrial Engineering at Tel Aviv University and a visiting professor at MS&E Stanford University. His research focuses on applied probability, machine learning and information theory applications to industrial and service systems. He wrote 3 books, published more than 80 scientific papers and patents and received several best papers awards. He is a Department Editor in IIE Transactions and serves on the Editorial Boards of several data science journals. Irad led various R&D projects and worked with companies such as Siemens, Intel, Applied Materials, GM, Nokia, AT&T and Oracle.  Irad is the co-founder of CB4 (“See Before”), a startup backed by Sequoia Capital that provides predictive analytics solutions to retail organizations. 

 

Monday, April 10

3108 Etcheverry Hall, 3:30 p.m. - 5:00 p.m.

Mariana Olvera-Cravioto is a Visiting Associate Professor in the Department of Industrial Engineering and Operations Research at UC Berkeley. She does research in Applied Probability, in particular, she works on problems involving heavy-tailed phenomena. Her current work is focused on the analysis of information ranking algorithms and their large-scale behavior, which is closely related to the study of the solutions to certain stochastic recursions constructed on weighted branching processes. She is also interested in the analysis of complex networks, in particular, scale-free random graphs such as those used to model the web and other social networks. Some of her ongoing projects include the study of queueing networks with parallel servers and synchronization constraints and the development of efficient simulation algorithms for computing the solutions to branching distributional equations.

 

Monday, April 17

3108 Etcheverry Hall, 3:30 p.m. - 5:00 p.m.

Professor Siqian Shen earned her BS from Tsinghua University in China in 2007 and her Ph.D. from the University of Florida in 2011. She joined the faculty in Fall 2011. Her research is in integer programming, stochastic programming, and network optimization. The models she considers usually feature stochastic parameters and discrete decision variables. In general, optimal solutions are desired for trading off between the immediate benefits and the long-run gains, or between cost effectiveness and operational risk. Applications include risk analysis and optimization of energy, healthcare, cloud-computing, and transportation systems. In particular, she has worked on problems of optimal power flow and load management, surgery planning and appointment scheduling, cloud computing server management, and carsharing system optimization. Her research is funded by the National Science Foundation. Prof. Shen teaches courses of Linear Programming, Network Flows, and Optimization under Uncertainty.

 

Monday, April 24

3108 Etcheverry Hall, 3:30 p.m. - 5:00 p.m.

Burak Kazaz is an invited speaker to the IEOR Spring 2017 seminar series. Dr. Kazaz is the Steven Becker Professor of Supply Chain Management, and the Laura J. and L. Douglas Meredith Professor for Teaching Excellence at Syracuse University’s Martin J. Whitman School of Management. He is the Executive Director of the first research center established in the field of supply chain management in the US (in 1919), the H.H. Franklin Center for Supply Chain Management at Syracuse University. He presently serves as the Whitman Research Fellow.

 

Monday, May 1

3108 Etcheverry Hall, 3:30 p.m. - 5:00 p.m.

Deepak Rajan is an Operations Research expert in the Center for Applied Scientific Computing (CASC). His research broadly lies in the areas of computational optimization and integer programming, and more specifically in applying such techniques in solving large-scale problems. Recently, Deepak has been working on optimization problems that involve uncertainty in the energy area (power generation, in particular). He has also worked on a variety of optimization problems in other domains, including network design and graph data mining.

Since 2016, Deepak is also an Associate Adjunct Professor of Industrial Engineering and Operations Research at the University of California at Berkeley.