Xiaoqi Tan, PhD

Area of Study / Keywords

systems and theory decision-making under uncertainty online algorithms algorithmic economics artificial intelligence energy sustainability

Research

Xiaoqi Tan’s research broadly intersects systems, algorithms, and economics, focusing on developing mathematical and algorithmic tools to address uncertainty and strategic behaviors in systems modeling, optimization, learning, and decision-making, such as online algorithms. On the applied side, his research aims to address environmental and economic sustainability challenges in networked systems and markets across various domains, including energy grids and markets, transportation systems, cloud computing, and communication networks.

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.

CMPUT 676 - Topics in Computing Science

Browse more courses taught by Xiaoqi Tan