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Events for February 17, 2015
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Epstein ISE Department Seminar
Tue, Feb 17, 2015 @ 10:00 AM - 11:00 AM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Hoda Bidkhori, Lecturer and Postdoctoral Associate, Operations Research and Statistics Group, Sloan School of Management, Massachusetts Institute of Technology
Talk Title: Flexibility, Adaptability and Pareto Efficiency in Manufacturing Operations
Abstract: Process and operational flexibility have been widely applied in many industries as competitive strategies to improve responsiveness to demand uncertainty. The first part of this talk addresses the problem of managing process and operational flexibility in a fairly general manufacturing system. In our model, each plant might have a different cost for adding flexibility or extra capacity, and different costs for transporting its different products. We model this problem as an adaptive optimization problem and discuss different approaches to solve it efficiently. One of the features of our model is that it captures information about the uncertainty in the demand; different demand uncertainties lead to different design suggestions. We conclude this talk with several computational and theoretical results.
In the second part of the talk, we introduce a method for worst-case analysis of stochastic programming for a class of truncated distributions. We use this to evaluate the performance of general unbalanced process flexibility structures.
Biography: Hoda Bidkhori is a lecturer and postdoctoral associate in the Operations Research and Statistics group at MIT's Sloan School of Management. She holds a Ph.D. degree in Applied Mathematics from MIT. Her current research centers around decision making under uncertainty and the development and implementation of robust and computationally tractable solutions for problems arising in manufacturing and logistics. She is a recipient of the Roger Family Prizes at MIT for excellent mentorship, and Second and Third Prizes in the 8th and 9th International Competition for University Students.
Host: Daniel J. Epstein Department of Industrial and Systems Engineering
More Information: SEMINAR-Bidkhori.doc
Location: 206
Audiences: Everyone Is Invited
Contact: Georgia Lum
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From Systems to Networks: Theory and Computation for Distributed Predictive Control
Tue, Feb 17, 2015 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Melanie Zeilinger, University of California, Berkeley and the Empirical Inference Department at the Max Planck Institute for Intelligent Systems
Talk Title: From Systems to Networks: Theory and Computation for Distributed Predictive Control
Abstract: The control of a network of interacting dynamical systems is a central challenge for addressing a range of emerging application problems; examples include energy systems balancing a network of generation, load and storage devices, or robotic systems comprising a large number of components or agents. Utilizing the connectivity and interactions in the network by exploiting advances in communication and computation technologies offers the potential for pushing these systems to higher performance while increasing efficiency of operation, which will reduce system over-design and associated costs. However, safety requirements and high system complexity represent key limiting factors for leveraging these new opportunities.
This talk will present some of our recent work that brings high-performance control with hard guarantees on system safety to distributed systems, offering a scalable and modular approach that exploits interconnection effects and flexibly adjusts to network changes. A new framework for plug and play distributed predictive control will be introduced and we will discuss essential theoretical and practical aspects for certifying distributed decision-making based on an optimization-in-the-loop paradigm. We will show how the proposed scheme ensures the fundamental properties of stability and constraint satisfaction of the global system without recourse to any centralized coordination and even in the presence of online network changes, while allowing the control systems to optimize for performance. Application examples in area generation control and grid-aware electric vehicle charging will demonstrate the capabilities of the proposed theory. Lastly, we will address the computational aspects of the framework and present new results for certifying optimization with limited-precision computation or communication.
Biography: Melanie Zeilinger is a Postdoctoral Researcher and Marie Curie fellow in a joint program with the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley and the Empirical Inference Department at the Max Planck Institute for Intelligent Systems in Tuebingen, Germany. From 2011-2012 she was a postdoctoral fellow at the Ãcole Polytechnique Fédérale de Lausanne (EPFL) in Switzerland. She received the Ph.D. degree in Electrical Engineering from ETH Zurich in Switzerland in 2011, and the diploma in Engineering Cybernetics from the University of Stuttgart in Germany in 2006. She conducted her diploma thesis research at the University of California at Santa Barbara in 2005-2006. She received the ETH medal for her dissertation in 2012 and was awarded a Marie Curie Fellowship for Career Development by the European Commission in 2011. Her research interests are centered around real-time and distributed control and optimization, as well as safe learning-based control, with applications to energy distribution and management systems and human-in-the-loop control.
Host: Urbashi Mitra, ubli@usc.edu, EEB 540, x04667
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Gerrielyn Ramos
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From Systems to Networks: Theory and Computation for Distributed Predictive Control
Tue, Feb 17, 2015 @ 10:00 AM - 11:00 AM
Sonny Astani Department of Civil and Environmental Engineering
University Calendar
Abstract: The control of a network of interacting dynamical systems is a central challenge for addressing a range of emerging application problems; examples include energy systems balancing a network of generation, load and storage devices, or robotic systems comprising a large number of components or agents. Utilizing the connectivity and interactions in the network by exploiting advances in communication and computation technologies offers the potential for pushing these systems to higher performance while increasing efficiency of operation, which will reduce system over-design and associated costs. However, safety requirements and high system complexity represent key limiting factors for leveraging these new opportunities.
This talk will present some of our recent work that brings high-performance control with hard guarantees on system safety to distributed systems, offering a scalable and modular approach that exploits interconnection effects and flexibly adjusts to network changes. A new framework for plug and play distributed predictive control will be introduced and we will discuss essential theoretical and practical aspects for certifying distributed decision-making based on an optimization-in-the-loop paradigm. We will show how the proposed scheme ensures the fundamental properties of stability and constraint satisfaction of the global system without recourse to any centralized coordination and even in the presence of online network changes, while allowing the control systems to optimize for performance. Application examples in area generation control and grid-aware electric vehicle charging will demonstrate the capabilities of the proposed theory. Lastly, we will address the computational aspects of the framework and present new results for certifying optimization with limited-precision computation or communication.
Biography: Melanie Zeilinger is a Postdoctoral Researcher and Marie Curie fellow in a joint program with the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley and the Empirical Inference Department at the Max Planck Institute for Intelligent Systems in Tuebingen, Germany. From 2011-2012 she was a postdoctoral fellow at the Ãcole Polytechnique Fédérale de Lausanne (EPFL) in Switzerland. She received the Ph.D. degree in Electrical Engineering from ETH Zurich in Switzerland in 2011, and the diploma in Engineering Cybernetics from the University of Stuttgart in Germany in 2006. She conducted her diploma thesis research at the University of California at Santa Barbara in 2005-2006. She received the ETH medal for her dissertation in 2012 and was awarded a Marie Curie Fellowship for Career Development by the European Commission in 2011. Her research interests are centered around real-time and distributed control and optimization, as well as safe learning-based control, with applications to energy distribution and management systems and human-in-the-loop control.
Host: Urbashi Mitra, ubli@usc.edu, EEB 540, x04667
Location: EEB 248
Audiences: Everyone Is Invited
Contact: Kaela Berry
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Epstein Institute / ISE 651 Seminar Series
Tue, Feb 17, 2015 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Boris Defourny, Assistant Professor, Department of Industrial & Systems Engineering, Lehigh University, Bethlehem, PA
Talk Title: Optimal Learning for a Class of Structured Problems
Abstract: While several methods exist to formulate decision making problems under uncertainty, sometimes we also have the opportunity to make experiments to make more informed decisions. For instance, consider a market survey that tries to identify consumersâ preferences prior to launching a new product. Optimal learning roughly refers to the task of selecting the best experiments to carry out, dynamically as we collect more information. Optimal learning comes in several flavors, depending on the experiments we can make and the model that produces the final decision we implement given the information collected. In this talk, we focus on certain classes of optimal learning problems and approximate solution approaches. We adopt a Bayesian perspective to model the information dynamics, and we develop methods adapted to special structures of interest in optimal learning. This work is motivated in part by the question of valuing information for a risk-averse decision maker.
Biography: Boris Defourny is an Assistant Professor in the Department of Industrial & Systems Engineering at Lehigh University. His research interests are in the broad areas of stochastic optimization and machine learning, with a focus on energy systems analysis, electricity markets, and more generally, valuation of interconnected assets. Boris Defourny obtained his Ph.D. in 2010 from the University of Liege, in Belgium, and then worked as an associate professional specialist in the Operations Research and Financial Engineering department at Princeton University, prior to joining Lehigh in 2013.
More Information: Seminar-Defourny.docx
Location: Ethel Percy Andrus Gerontology Center (GER) - 206
Audiences: Everyone Is Invited
Contact: Georgia Lum
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Interviewing Strategies and Techniques - VCS
Tue, Feb 17, 2015 @ 04:00 PM - 05:00 PM
Viterbi School of Engineering Career Connections
Workshops & Infosessions
Discover tips on how to prepare for both technical and behavioral interviews, as well as the proper steps for follow-up!
Location: Seeley G. Mudd Building (SGM) - 124
Audiences: Everyone Is Invited
Contact: RTH 218 Viterbi Career Services
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PepsiCo Info Session
Tue, Feb 17, 2015 @ 06:00 PM - 08:00 PM
Viterbi School of Engineering Career Connections
Workshops & Infosessions
PepsiCo will be hosting an information session for students interested in learning about the available positions within our Pepsi Americas Beverages division. This is a great way to learn more about the company and our career opportunities. This is also a fantastic opportunity to meet the professionals. Refreshments will be served.
Location: Seeley G. Mudd Building (SGM) - 101
Audiences: Everyone Is Invited
Contact: RTH 218 Viterbi Career Services
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Covidien Networking Event
Tue, Feb 17, 2015 @ 07:30 PM - 09:00 PM
Viterbi School of Engineering Student Organizations
Student Activity
Covidien, a company recently acquired by Medtronic, is coming to USC to offer career development information and speak about internship opportunities with its Irvine, CA Vascular Therapies (ev3) division. Come out to meet University Relations staff and learn more about this global medical device leader. To RSVP: To RSVP, use the following link: https://docs.google.com/forms/d/1obtRGljsu5-8yDu6MJCbiFQ9pnH5o17MuuhUgiel44c/viewform. Then email covidien.resume@gmail.com with an electronic copy of your resume.
Location: John Stauffer Science Lecture Hall (SLH) - 100
Audiences: Everyone Is Invited
Contact: Associated Students of Biomedical Engineering
