News & Events
The DEPARTMENT OF INDUSTRIAL ENGINEERING & OPERATIONS RESEARCH (IEOR) at University of California, Berkeley is conducting a search for candidates for a tenure-track faculty position at the Assistant Professor, Associate Professor, or Professor level. The expected start date is July 1, 2016. We are searching for faculty doing fundamental and applied research in data science and decision analytics, with demonstrated applications in the social or management sciences, including such topics as social networks, financial modeling, healthcare, operations, innovation, entrepreneurship, sustainability, or social media.
For the full job description and information about how to apply, please visit here
Congratulations to Shmuel and alum Tony Papavasiliou for winning the INFORMS Section on Energy, Natural Resources, and the Environment (ENRE) Best Publication Award for 2015 for their paper "Multi-Area Stochastic Unit Commitment for High Wind Penetration in a Transmission Constrained Network".
Over 80 people gathered today in the newly built Jacobs Hall, which recently opened its doors in Fall 2015 as the new home of the Jacobs Institute for Design Innovation, to announce a partnership between the Sutardja Center and the Jacobs Institute. By combining the Sutardja Center’s expertise in techno-centric entrepreneurship and the Jacobs Institute’s knowledge of user experience and design, the collaboration hopes to achieve more innovative project outcomes for students and partners.
The event also introduced the Sutardja Center’s new Global Innovation Partner program. The five global partners that are currently participating in the program include PhilDev (Philippines), Universidade Federal de Minas Gerais (Brazil), Pontificia Universidad Católica de Chile (Chile), Shantou University (China) and Ulsan National Institute of Science and Technology (Korea). Representatives from PhilDev, Chile and UFMG were in attendance and received certificates recognizing them as key contributors for Global Innovation between their university and UC Berkeley. Attendees also included the Dean of the College of Engineering, Shankar Sastry, Jacobs Institute Faculty Director, David Dornfield, and the Sutardja Center’s Chief Scientist and Founding Director, Ikhlaq Sidhu.
Many of the most important economic/business and social issues and challenges of our time have direct implications for supply chain risk and the need for resiliency. They include globalization, climate change, cyber security, social connectedness, CSR and compliance. At the same time, all of the most important technology forces of our time -- what Gartner calls the “Nexus of Forces” (social/mobile, big data/analytics, cloud, IoT/IoE) -- are converging to unleash new and exciting SCRM solution possibilities and business value propositions.
The collision of today’s most important economic/business and social trends with the “Nexus of (technology) Forces”, has created the perfect, disruptive super storm for supply chain risk management stakeholders.
In this presentation, Bindiya Vakil describes these forces and how their convergence is resulting in the transformation of how risk is understood and managed. She concludes that this convergence also results in the business imperative to act now to not only mitigate the near-term financial and business continuity risks associated with disruptions events, security breaches and compliance challenges, but build resiliency strategies to increase brand and shareholder value, and achieve a sustainable competitive advantage.
Professor Lee Schruben was the keynote speaker at the 2015 Biomanufacturing and Process Development (BPD) Process Analytics Symposium hosted by the North Carolina Biotechnology Center where he delivered his talk titled "The Dastardly D's of Data".
My working title for this presentation was “The A,B,C’s of Data Analytics”, but I got stuck at D; ultimately, I had to change the title. I had considered: Dynamic (data changes over time); Dependent (independent sampling, really?); Distorted (measurement and definition errors); Deluge (Big Noise); Doctored (robust estimation); Deleted (censoring); Dangerous (profiling); Damaged (translation and transmission losses); Discrete (two meanings); Distracting; Devious; Deceptive, Disingenuous… and we probably call it “data” because it’s Dated (old the instant it exists). Hopefully, the audience can suggest less disparaging data dimensions beginning with the letter D to help me move beyond my alliterative rut toward “Z-values”.
Motivated by predictive modeling problems in personalized chronic disease management, we present a framework for solving inverse optimization problems with noisy data. These are problems in which noisy measurements of minimizers to a parametric optimization problem are observed and then used to estimate the unknown parameters of the optimization problem. Though a number of approaches have been developed, these approaches require no noise in the measured data and no modeling mismatch. In this talk, we present our framework that deals with the case where the parametric optimization problem is convex, and show this framework is risk consistent (asymptotically provides best possible predictions) or estimation consistent (asymptotically estimates true parameters) under appropriate conditions. Numerically, we provide three optimization formulations to solve inverse problems using our framework, including a new approach to solving bilevel optimization problems, a new approximation algorithm, and an approach based on integer programming. We conclude with a case study on applying these approaches to real data involving personalized chronic disease management.
This is joint work with Elena Flowers (UCSF), Yoshimi Fukuoka (UCSF), Phil Kaminsky (UCB), Yonatan Mintz (UCB), Zuo-Jun Max Shen (UCB), and Auyon Siddiq (UCB).