Haifeng Xu is an assistant professor in the Department of Computer Science at UChicago, where he directs the Strategic IntelliGence for Machine Agents (SIGMA) lab (hyperlink to https://www.haifeng-xu.com/sigma/index.html). He studies the economics of data and machine learning, including designing learning algorithms for multi-agent decision making and designing markets for data and ML algorithms. Haifeng publishes regularly at leading machine learning and computational economics conferences, and serves as area chair or senior program committee for premier venues such as ICML, EC, AAAI, IJCA, etc. His research has been recognized by multiple awards, including the AI2050 Early Career fellow, IJCAI Early Career Spotlight, Google Faculty Research Award, ACM SIGecom Dissertation Award (honorable mention), IFAAMAS Distinguished Dissertation Award (runner-up), and multiple best paper awards; his works have been generously supported by varied agencies including NSF, ARO, ONR, Schmidt Science, and Google Research.
Focus Areas: computational economics, machine learning, multi-agent systems, algorithms
More descriptions:
The following research themes are the recent focus of our research lab. Please refer to our lab’s website for more details.
- The economics of data/information, including selling, acquiring, and exploiting information
- Machine learning in multi-agent setups under information asymmetry, incentive conflicts, and deception
- Resource allocation in adversarial domains, with applications to security and privacy protection
