國立陽明交通大學及IEEE Taipei Section特邀美國伊利諾大學厄巴納-香檳分校的電腦科學創始教授Dr. Sheldon Howard Jacobson至陽明交大進行學術演講，敬祈各位共襄盛舉。
演講時間：2025年6月9日 15:00 ~ 16:30 (14:50入場)
演講地點：國立陽明交通大學 工程四館108室
Speaker：Dr. Sheldon Howard Jacobson/ University of Illinois Urbana-Champaign
主 持 人：王蒞君終身講座教授 國立陽明交大電機學院院長 / IEEE Taipei Section理事長
主 題：An Optimization Framework for Causal Inference Using Observational Data
Abstract：Exact matching is widely used in the estimation of treatment effects in observational studies in medicine and public health. However, the exact matching paradigm may be too limiting is some scenarios given that exact matches often do not exist in most data sets. One mechanism for overcoming this issue is to relax the requirement of exact matching on the covariates (attributes that may affect the response to treatment) to a requirement of balance on the covariate distributions for the treatment and control groups. The resulting optimization framework, termed balance optimization subset selection (BOSS), can be used to identify a control group featuring optimal covariate balance. This presentation looks at implementation issues associated with BOSS and under what assumptions it yields unbiased estimators. We also discuss the computational challenges associated with solving BOSS instances, as well as the benefits and limitations of using this optimization framework.
About Speaker：Sheldon H. Jacobson is a Founder Professor of Computer Science at the University of Illinois at Urbana-Champaign, where he also directs the Simulation and Optimization Laboratory and founded the Bed Time Research Institute. He holds appointments across multiple departments, including Industrial and Enterprise Systems Engineering, Electrical and Computer Engineering, Mathematics, Statistics, and the College of Medicine. He earned his B.Sc. and M.Sc. in Mathematics from McGill University and his Ph.D. in Operations Research from Cornell University.
Professor Jacobson’s seminal research applies operations research and optimization-based artificial intelligence to critical societal problems. He pioneered aviation security analytics, demonstrating how probabilistic models, optimization, and AI can enhance security systems. His work on multi-level passenger screening was a precursor to risk-based security, influencing the design of TSA Precheck©.
His contributions extend to pediatric vaccine formulary design, utilizing operations research for immunization, and bridging the link between obesity, transportation, and fuel consumption to inform non-medical obesity interventions. He also developed computational redistricting methods, using optimization-based AI to combat gerrymandering.
Recognized with numerous accolades, Professor Jacobson received a Guggenheim Fellowship (2003) and the INFORMS Impact Prize (2018). He is an elected Fellow of the American Association for the Advancement of Science (AAAS), the Institute for Operations Research and the Management Sciences (INFORMS), and the Institute of Industrial and Systems Engineers (IISE).
報名連結：https://docs.google.com/forms/d/1e0AJnjLlmHlD1cq6IZikpvU_MaeKeoRCPzeAJ1kBQlQ/edit
Contact Information:
Tel: (03)5712121#54484/ 54014
E-mail : yayihuang@nycu.edu.tw/ peggy3631@nycu.edu.tw