Xiaoqi Tan, PhD

Area of Study / Keywords

Online algorithms Algorithmic economics Decision-making under uncertainty

Research

Xiaoqi Tan’s research focuses on developing algorithms for decision-making under uncertainty (course), with applications to systems and online platforms shaped by dynamics and strategic behavior. His current work centers on algorithm design problems that involve two key challenges: (i) the need to make sequential decisions before the full input is revealed (online algorithms), and (ii) the presence of private, unknown preferences among self-interested agents in resource allocation, systems and market design (algorithmic economics).

For more details about Xiaoqi’s research, or if you are interested in joining his lab as an undergraduate, graduate, or postdoc, see his SODALab page: https://sodalab.ca.

The SODALab@UofA is constantly looking for highly motivated graduate students at both the MSc and PhD level. If you are already at UofA and want to join us, feel free to email your CV to Xiaoqi. For prospective students who are not currently enrolled at UofA, read Xiaoqi's Letter to Prospective Students first before reaching out.

CMPUT 204 - Algorithms I

The first of two courses on algorithm design and analysis, with emphasis on fundamentals of searching, sorting, and graph algorithms. Examples include divide and conquer, dynamic programming, greedy methods, backtracking, and local search methods, together with analysis techniques to estimate program efficiency. Prerequisites: CMPUT 175 or 275, and CMPUT 272; and one of MATH 100, 114, 117, 134, 144, or 154.

Browse more courses taught by Xiaoqi Tan

• Google Scholar
• Personal Website
• SODALab