Xiaoqi Tan, PhD

Area of Study / Keywords

Algorithms Decision-making under uncertainty Online algorithms Algorithmic economics

Research

Xiaoqi Tan’s research focuses on algorithms and decision-making under uncertainty (course), and their role in systems and networks shaped by dynamics and strategic behavior. His current research focuses on two key challenges in algorithm design: (i) making sequential decisions without access to the full input in advance (online algorithms), and (ii) managing and allocating resources, incentives, and interactions in economic settings while ensuring computational feasibility and performance guarantees (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. For more details, 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