Service & Mentoring

At Duke, I am committed to building the best undergraduate program possible. I primarily serve the department through undergraduate advising, mentoring in research, and leadership in undergraduate project and research programs such as CS+. In the broader community, I serve in the review and organization of several major conferences in computer science.

CS+ Summer Undergraduate Projects in Computer Science

CS+ is a ten week summer program only for Duke undergraduates to get involved in computer science research projects with faculty in a fast-paced but supportive community environment. Students participate in teams of 3-4 and are jointly mentored by a faculty project lead and a graduate student mentor. The experience is meant as a rich entry point into computer science research and applications beyond the classroom. I direct the program with the support of the Department of Computer Science and Trinity College of Arts and Sciences, in collaboration with our partner programs Data+ and Code+.

Student Research Mentoring

I am passionate about and commited to involving diverse and talented students in my research. I have experience working with both high school and undergraduate students, and have published extensively with both groups in top conferences in computer science.

Duke University Undergraduate Students

  • Nianli Peng, Muhang (Tony) Tian, & Zimeng (Olivia) Fan [2022-2023] – Mentored research project on multi-objective reinforcement learning, published in AAMAS 2023. Nianli Peng graduated with highest distinction with a thesis on the same topic and is beginning the PhD program in Applied Math at Harvard in 2023.
  • Zeyu Shen, Zhiyi (George) Wang, & Xingyu (Jupiter) Zhu [2021-2023] – Co-mentored research project on fair assignment problems with uncertain priorities, published in AAMAS 2023.
  • Carolyn Chen, Jerry Lin, Marc Chmielewski, & Samia Zaman [2020-2022] – Mentored summer CS+ project on Algorithms for Fair & Unbiased Districting: geometric local search optimization for measuring and correcting gerrymandering. Work published in ACM FAccT 2022.
  • Liang (Charles) Lyu [2018-2020] – collaborated on Proportionally Fair Clustering in ICML 2019 and Centrality with Diversity in WSDM 2021. Charles won an honorable mention from CRA Outstanding Undergraduate Researchers Award in 2019 and was a finalist in 2020. He began the PhD program at MIT in fall 2021.
  • Xingyu Chen [2018-2019] – collaborated on Proportionally Fair Clustering in ICML 2019. Xingyu won the Alex Vasilos Memorial Award for excellence in research from Duke Computer Science.

North Carolina School of Science and Mathematics Students

  • William Fan [2019-2020] – collaborated on Concentration of Distortion: The Value of Extra Voters in Randomized Social Choice. Accepted to appear in Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI) (2020). William will begin the Singh Program in Networked and Social Systems Engineering at the University of Pennsylvania in fall 2020.
  • Nina Prabhu [2018-2019] – collaborated on Random Dictators with a Random Referee: Constant Sample Complexity 2019 Mechanisms for Social Choice. In Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (2019). Nina is currently studying computer science at Stanford University.

Academic Reviewing

Program Committee Member

Program Committee Subreviewer

Journal Reviewer

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