Professional and Pedagogical Development

Teaching is at the heart of what I do. My passion for education teaching extends beyond the classrooms. I find great joy in supervising and mentoring students. To continuously improve as an educator, I actively participate in professional development workshops and engage in CS education research projects.

Student Supervision

I regularly supervise undergraduate students on various projects. The projects are typically part of CSC494/495, although I occasionally take students as volunteers as well. If you are interested in joining a project, please apply through the CS undergrad office. The application process typically starts 2 months before the semester (July for Fall, November for Winter, and March for Summer). Below is a list of my past/ongoing projects and a list of students who participated in these projects.

Projects on Games

My love for board games and escape rooms sparked an idea: why not blend my hobby with my professional work? This insight led me to develop research projects focused on creating game simulators and building AI agents that can play the games effectively. So far, I've explored games such as Othello, Gomoku and Hanabi.

• Designing Intelligent Agents to Play Hanabi (co-supervised by Jonathan Calver)
  • Fangshi Du (Jan - Aug 2025)
  • Eleonora Scognamiglio (Jan - Aug 2025)
  • Wilson Sy (Jan - Aug 2025)
  • Siwei Zhan (Jan - Aug 2025)
  • Jiahao Gu (Jan - Apr 2025)
  • Martin Calcaterra (May - Dec 2024)
  • Muhammad Muzammil (May - Dec 2024)
  • Daniel Xu (May - Dec 2024)
• Designing and Evaluating Algorithms for Solving Games
  • Daniel Cheng (May - Aug 2025)
  • Cynthia Luo (May - Aug 2025)
  • Maximillian Djaya (May - Aug 2025)
  • Ryan Ning (Jan - Aug 2025) (Swap 2, a variant of Gomoku)
  • Changdao He (Jan - Aug 2025) (Othello)
  • Justin Li (Jan - Apr 2025) (Renju, a variant of Gomoku)

Projects on AI/ML Education

As an instructor of advanced undergraduate AI and machine learning courses, I'm committed to enhancing educational approaches in these fields. My research projects analyze current AI/ML teaching practices. I also develop evidence-based tools and resources to improve student learning outcomes.

• Designing Interactive Visualizations for Machine Learning Concepts (co-supervised by Lisa Zhang)
  • Carmen Chau (Jan - Apr 2025) (Visualizing Backpropagation)
• A Systematic Literature Review of AI/ML Education at the Post-Secondary Level (co-supervised by Lisa Zhang)
  • Jiahao Gu (Jan - Dec 2024)
  • Ayush Oza (Jan - Dec 2024)

Projects on Academic Procrastination

My research on time management stems from a personal struggle with procrastination throughout my academic journey. This project aims to understand the underlying causes of student procrastination and develop effective strategies to combat it. By bridging personal experience with empirical research, I hope to create practical solutions that help students overcome similar challenges and reach their full potential.

• A Systematic Literature Review of Academic Procrastination in STEM at the Post-Secondary Level (co-supervised by Jonathan Calver)
• Evelyn Chou (May - Dec 2024)
• Daniyaal Farooqi (May - Dec 2024)
• Analyzing Interview Data on Academic Procrastination
• Jiongan Mu (Jan - Apr 2024)
• Why do students procrastinate and what can we do about it?
• Gy Hong (May 2023 - Apr 2024)
• Wise Chua (May 2023 - Apr 2024)
• Analyzing Procrastination Interventions
• Sarah Verreault (Jan - Apr 2023)

Current Research

Below you will find some of my publications in CS education.

• Student Perspectives on the Challenges in Machine Learning
  Naaz Sibia, Amber Richardson, Alice Gao, Andrew Petersen, Lisa Zhang.
  To appear in ITiCSE 2025, June 27 - July 2, 2025, Nijmegen, Netherlands.
  
  
• Diversity, Equity, and Inclusion in Computing Science: Culture is the Key, Curriculum Contributes
  Giulia Toti, Peggy Lindner, Alice Gao, Ouldooz Baghban Karimi, Rutwa Engineer, Jinyoung Hur, Fiona McNeill, Shanon Reckinger, Rebecca Robinson, Anna Sollazzo, Richard Wicentowski.
  In 2024 Working Group Reports on Innovation and Technology in Computer Science Education (ITiCSE 2024).
  Association for Computing Machinery, New York, NY, USA, 175-225.
  
  
• The impact of COVID-19 on the CS Student Learning Experience: How the Pandemic has Shaped the Educational Landscape
  Angela A. Siegel, Mark Zarb, Emma Anderson, Brent Crane, Alice Gao, Celine Latulipe, Ellie Lovellette, Fiona McNeill, and Debbie Meharg.
  In Proceedings of the 2022 Working Group Reports on Innovation and Technology in Computer Science Education (ITiCSE-WGR '22).
  Association for Computing Machinery, New York, NY, USA, 165-190.
  

Past Research

My doctoral research explored the intersection of artificial intelligence and game theory, focusing on designing incentive systems that elicit truthful information from strategic participants. I investigated various applications including innovative grading mechanisms and predictive forecasting techniques through a combination of theoretical analysis and experimental methods.

• Incentivizing Evaluation via Limited Access to Ground Truth: Peer-Prediction Makes Things Worse
  Xi Alice Gao, James R. Wright, and Kevin Leyton-Brown
  Artificial Intelligence Journal (AIJ), volume 275, pp. 618-638, October 2019.
• Trick or treat: putting peer prediction to the test.
  Xi Alice Gao, Andrew Mao, Yiling Chen, and Ryan Prescott Adams.
  In Proceedings of the fifteenth ACM conference on Economics and computation (EC 2014).
  Association for Computing Machinery, New York, NY, USA, 507–524.
• Market manipulation with outside incentives.
  Chen, Y., Gao, Xi Alice, Goldstein, R.
  Auton Agent Multi-Agent Syst 29, 230–265 (2015).
  (Supersedes the AAAI 2011 paper below.)
• What you jointly know determines how you act: strategic interactions in prediction markets.
  Xi Alice Gao, Jie Zhang, and Yiling Chen.
  In Proceedings of the fourteenth ACM conference on Electronic commerce (EC '13).
  Association for Computing Machinery, New York, NY, USA, 489–506.
• Quality Expectation-Variance Tradeoffs in Crowdsourcing Contests
  Xi Alice Gao, Yoram Bachrach, Peter Key, and Thore Graepel.
  In Proceedings of the 26th Conference on Artificial Intelligence (AAAI 2012), Toronto, ON, Canada, 2012.
• Adaptive Polling for Information Aggregation
  Thomas Pfeiffer, Xi Alice Gao, Andrew Mao, Yiling Chen, and David G. Rand.
  In Proceedings of the 26th Conference on Artificial Intelligence (AAAI 2012), Toronto, ON, Canada, 2012.
• Market Manipulation with Outside Incentives
  Yiling Chen, Xi Alice Gao, Rick Goldstein, and Ian A. Kash.
  In Proceedings of the 25th Conference on Artificial Intelligence (AAAI 2011), San Francisco, CA, 2011.
• An Axiomatic Characterization of Continuous-Outcome Market Makers
  Xi Alice Gao and Yiling Chen.
  In Proceedings of the 6th Workshop on Internet and Network Economics (WINE 2010), Stanford, CA, 2010.
• Learning Game Representations from Data Using Rationality Constraints
  Xi Alice Gao and Avi Pfeffer.
  In Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence (UAI 2010), Catalina Island, CA, 2010.
• Betting on the Real Line
  Xi Alice Gao, Yiling Chen, and David M. Pennock.
  In Proceedings of the 5th Workshop on Internet and Network Economics (WINE 2009), Rome, Italy, 2009.
  

Ph.D. Dissertation

Eliciting and Aggregating Truthful and Noisy Information
School of Engineering and Applied Sciences, Harvard University, September 2014.

SIGecom Doctoral Dissertation Award runner up
IFAAMAS Victor Lesser Distinguished Dissertation Award runner up