We are the Systems Optimization & Decision Analytics Lab (SODALab) based at the Department of Computing Science, University of Alberta and the Alberta Machine Intelligence Institute (Amii), Edmonton, Canada. We are committed to optimizing complex decision-making in dynamic and multi-agent systems, striving for theoretically-elegant and practically-relevant research at the interface of systems science, artificial intelligence, and economics & computation.
In the SODALab, we view much of the modern world as systems of interacting and possibly strategic, intelligent agents, sharing and competing for limited resources under different forms of dynamics and uncertainty. This is particularly true for high-impact, safety-critical systems (e.g., electrical grids and transportation systems), where multi-agent interactions are ubiquitous, robust performance against uncertainty is crucial, and unexplainable results are undoubtedly less acceptable if not utterly unbearable. This motivates the long-term goal of our research in the SODALab — to create a common set of mathematical tools that can help develop algorithms and market mechanisms, with formal guarantees on performance, robustness and explainability, for optimization and decision-making under uncertainty.
Latest News
Jan 2023: Hossein joined the lab as a M.Sc. student. Welcome!!
Nov 2022: Xiaoqi gave an invited lecture, “Optimization & Decision-Making under Uncertainty,” at Tsinghua-Berkeley Shenzhen Institute (TBSI).
Oct 2022: Vedant joined the SODALab as an undergraduate research intern. Welcome!!
Sept 2022: Yanzhao (M.Sc. student) and Yu (Ph.D. student) joined the SODALab. Welcome!!
Aug 2022: Xiaoqi is now a Fellow of Alberta Machine Intelligence Institute (Amii). We are proud to join the Amii family to play our part in making AI for good and for all!!
Jul 2022: Xiaoqi presented our recent work, “Online Allocation with Convex Costs,” at C2E@HKUST.
Jun 2022: Xiaoqi presented our recent work, “Online Allocation with Convex Costs,” at RSRG@Caltech.
Jun 2022: Xiaoqi presented our recent work, “Online Selection with Convex Costs (slides),” at ACM MAMA 2022.
May 2022: Our short paper “Online Selection with Convex Costs” was accepted by ACM MAMA 2022 - in conjunction with ACM SIGMETRICS/IFIP Performance 2022.
May 2022: Henry, Johnson, and Yanze joined the SODALab as undergraduate research interns. Welcome!!
Apr 2022: New NSERC Discovery Grant, “A Unified Framework for Balancing Robustness, Effectiveness, and Fairness in Online Mechanism Design.”
Feb 2022: Siyuan presented our recent work, “Online Search under Convex Costs,” at Reverse EXPO 2022 organized by AI4Society.
July 2021: Siyuan joined the SODALab as an undergraduate research intern. Welcome!!
Contact Us
SODALab@UofA Dr. Xiaoqi Tan The SODALab
Central Academic Building (CAB) 385,
University of Alberta,
116 St and 85 Ave, Edmonton, Alberta,
Canada T6G 2E8
Email: $ \textsf{contact}@\textsf{sodalab.ca} $
Web: https://sodalab.caXiaoqi Tan
Athabasca Hall (ATH) 303,
Dept. of Computing Science, University of Alberta,
116 St and 85 Ave, Edmonton, Alberta,
Canada T6G 2E8
Email: $ \textsf{xiaoqi.tan}@\textsf{ualberta.ca} $
Web: https://xiaoqitan.org