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APPOINTMENTS

  • Professor
    Department of Computer Science, Rutgers University - New Brunswick, Piscataway, NJ, USA. Sep. 2024 - present
  • Deputy Director
    DIMACS (the Center for Discrete Mathematics and Theoretical Computer Science), Piscataway, NJ, USA. Sep. 2024 - present

DEGREES

  • Ph.D., Computer Science
    Duke University, Durham, NC , USA. Aug, 2011.
  • M.A., Economics
    Duke University, Durham, NC , USA. Dec., 2010.
  • B.E., Computer Science and Technology
    Tsinghua university, Beijing, China. July, 2004.

POSTGRADUATE TRAINING

  • NSF CI-Fellow, Center for Research on Computation and Society
    Harvard University, Cambridge, MA, USA. Sep., 2011 - July 2013.

RESEARCH INTERESTS

  • Artificial intelligence, machine learning, multi-agent systems, decision-making under uncertainty, algorithm design, social choice theory, game theory, mechanism design, prediction markets, preference learning, differential privacy, blockchain.

BIOGRAPHY

  • Lirong Xia is a Professor of Computer Science at Rutgers University - New Brunswick and the Deputy Director of DIMACS (the Center for Discrete Mathematics and Theoretical Computer Science). Prior to joining Rutgers and DIMACS, he was an assistant then associate professor at RPI (2013-2024), a CRCS fellow and NSF CI Fellow at the Center for Research on Computation and Society at Harvard University (2011-2013). He received his Ph.D. in Computer Science and M.A. in Economics from Duke University. His research focuses on the intersection of computer science and microeconomics. He is an associate editor of Mathematical Social Sciences and Artificial Intelligence Journal. He is the recipient of an NSF CAREER award, a Simons-Berkeley Research Fellowship, the 2018 Rensselaer James M. Tien’66 Early Career Award, and was named as one of “AI’s 10 to watch” by IEEE Intelligent Systems.

PUBLICATIONS

Book and Book Chapters

  • Lirong Xia. Learning and Decision-Making from Rank Data, Morgan & Claypool, 2019. Synthesis Lectures on Artificial Intelligence and Machine Learning.
  • Jerome Lang and Lirong Xia. Voting in Combinatorial Domains. In Felix Brandt, Vincent Conitzer, Ulle Endriss, Jerome Lang, and Ariel Procaccia, editors, Handbook of Computational Social Choice, chapter 9. Cambridge University Press, 2016.

Ongoing work

  • Joshua Kavner, Lirong Xia. Average-Case Analysis of Iterative Voting. [arXiv]
  • Zhechen Li, Zimai Guo, Lirong Xia, Yongzhi Cao, Hanpin Wang. Differentially Private Approval-Based Committee Voting. [arXiv]
  • Zhechen Li, Ao Liu, Lirong Xia, Yongzhi Cao, Hanpin Wang. Trading Off Voting Axioms for Privacy. [arXiv]
  • Inwon Kang, Sikai Ruan, Tyler Ho, Jui-Chien Lin, Farhad Mohsin, Oshani Seneviratne, Lirong Xia. LLM-augmented Preference Learning from Natural Language. [arXiv]
  • Jui Chien Lin, Farhad Mohsin, Sahith Bhamidipati and Lirong Xia. Generating Election Data Using Deep Generative Models. To be presented at the AI for social good workshop at AAAI-23.
  • Farhad Mohsin, Inwon Kang, Yuxuan Chen, Jingbo Shang and Lirong Xia. Dependency and Coreference-boosted Multi-Sentence Preference model. To be presented at the AAAI 2023 Workshop on Deep Learning on Graphs: Methods and Applications.
  • Hadi Hosseini, Joshua Kavner, Sujoy Sikdar, Rohit Vaish, Lirong Xia. Hide, Not Seek: Perceived Fairness in Envy-Free Allocations of Indivisible Goods. [arXiv]
  • Farhad Mohsin, Lei Luo, Wufei Ma, Inwon Kang, Zhibing Zhao, Ao Liu, Rohit Vaish and Lirong Xia. Making Group Decisions from Natural Language-Based Preferences. Presented at COMSOC-21. [COMSOC version] [dataset]
  • Qishen Han, Sikai Ruan, Yuqing Kong, Ao Liu, Farhad Mohsin, Lirong Xia. Truthful Information Elicitation from Hybrid Crowds. Presented at COMSOC-21 student poster session. [arXiv]
  • Farhad Mohsin, Inwon Kang, Pin-Yu Chen, Francesca Rossi and Lirong Xia. Learning Individual and Collective Priorities over Moral Dilemmas with the Life Jacket Dataset. Presented at MREF-22.

2024 +

  • Lirong Xia. Computing Most Equitable Voting Rules. In Proceedings of WINE-24. [arXiv]   
  • Hadi Hosseini, Joshua Kavner, Tomasz Wąs, Lirong Xia. Distribution of Chores with Information Asymmetry. In Proceedings of ECAI-24. [arXiv]
  • Qishen Han, Amélie Marian, Lirong Xia. Determining Winners in Elections with Absent Votes. In Proceedings of IJCAI-24. [arXiv]
  • Farhad Mohsin, Qishen Han, Sikai Ruan, Pin-Yu Chen, Francesca Rossi and Lirong Xia. Computational Complexity of Verifying the Group No-show Paradox. In Proceedings of IJCAI-24. (Previously appeared as a non-archival extended abstract at AAMAS-23.)

2023

  • Lirong Xia. Most Equitable Voting Rules. In Proceedings of WINE-23. [arXiv]
  • Qishen Han, Biaoshuai Tao, Lirong Xia. Average Envy-freeness for Indivisible Items. In Proceedings of EAAMO-23. [arXiv]
  • Ao Liu, Qishen Han, Lirong Xia, Nengkun Yu. Accelerating Voting by Quantum Computation. In Proceedings of UAI-23. [arXiv]
  • Lirong Xia. The Impact of a Coalition: Assessing the Likelihood of Voter Influence in Large Elections. In Proceedings of EC-23. [arXiv]
  • Qishen Han, Grant Schoenebeck, Biaoshuai Tao, Lirong Xia. The Wisdom of Strategic Voting. In Proceedings of EC-23. [arXiv]
  • Xiaoxi Guo, Sujoy Sikdar, Lirong Xia, Yongzhi Cao, Hanpin Wang. First-Choice Maximality Meets Ex-ante and Ex-post Fairness. In Proceedings of IJCAI-23. [arXiv]
  • Joshua Kavner, Reshef Meir, Francesca Rossi and Lirong Xia. Convergence of Iterative Combinatorial Voting under Uncertainty. In Proceedings of IJCAI-23. [arXiv]
  • Hadi Hosseini, Sujoy Sikdar, Rohit Vaish, Lirong Xia. Fairly Dividing Mixtures of Goods and Chores under Lexicographic Preferences. In Proceedings of AAMAS-23. [arXiv]
  • Inwon Kang, Qishen Han and Lirong Xia. Learning to Explain Voting Rules. AAMAS-23 (extended abstract).
  • Lirong Xia. Semi-Random Impossibilities of Condorcet Criterion. In Proceedings of AAAI-23. [arXiv]
  • Zhechen Li, Ao Liu, Lirong Xia, Yongzhi Cao, Hanpin Wang. Differentially Private Condorcet Voting. In Proceedings of AAAI-23. [arXiv]
  • Reshef Meir, Ofra Amir, Gal Cohensius, Omer Ben-Porat, and Lirong Xia. Frustratingly Easy Truth Discovery. In Proceedings of AAAI-23. [arXiv]
  • Ao Liu, Yu-Xiang Wang, Lirong Xia. Smoothed Differential Privacy. TMLR. Dec, 2023. [arXiv]
  • Jingwen Qian, Sujoy Sikdar, Ge Wang, Lirong Xia. Anti-Collusion Dynamic Distanced Online Testing. Technology & Innovation, 2023.
  • Qian Li, Liang Wang, Lirong Xia, Wenxun Zheng, Yuxuan Zhou. A practical multi-objective auction design and optimization framework for sponsored search. Operations Research Letters, 2023.
  • Dorothea Baumeister, Marc Neveling, Magnus Roos, Jörg Rothe, Lena Schend, Robin Weishaupt, Lirong Xia. The Possible Winner with Uncertain Weights Problem. Journal of Computer and System Sciences, 2023.
  • Xiaoxi Guo, Sujoy Sikdar, Lirong Xia, Hanpin Wang, Yongzhi Cao. Favoring Eagerness for Remaining Items: Achieving Efficient and Fair Assignments. Journal of Artificial Intelligence Research, 76 (2023). [arXiv]
  • Haibin Wang, Sujoy Sikdar, Xiaoxi Guo, Lirong Xia, Yongzhi Cao, Hanpin Wang. Multi-type Resource Allocation with Partial Preferences. Artificial Intelligence, 314 (2023).

2022

2021

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2005 and before

GROUP

Postdoc

Yichi Zhang

Ph.D. Students

Qishen Han (Y4)

M.S. Students

 

Undergraduate Students

 

Alumni

  • Ph.D. 2024 (RPI). Joshua Kavner
  • Ph.D. 2023 (RPI). Farhad Mohsin → Assistant professor, Department of Math and Computer Science, College of the Holy Cross
  • Ph.D. 2023 (RPI). Ao Liu → Google
  • Ph.D. 2022 (RPI). Jun Wang → Machine Learning Engineer at Meta 
  • Ph.D. 2020 (RPI). Zhibing Zhao → Data & Applied Scientist at Microsoft → research scientist at ByteDance.
  • Ph.D. 2018 (RPI). Sujoy Sikdar (co-supervised with Prof. Sibel Adali) → Postdoc at Washington University in St. Louis → Assistant professor in CS at Binghamton University.
  • Postdoc 2020 (RPI). Rohit Vaish → visiting fellow at TIFR → Assistant professor at CSE IIT-Delhi.
  • MS 2024 (RPI). Sikai Ruan → Tencent; Alex Montes (voted best poster award at RPI CS poster session 2024 spring) → Amazon Web Services;
  • MS 2022 (RPI). Inwon Kang → Ph.D. at RPI; Sahith Bhamidipati → Epic Systems
  • MS 2021 (RPI). Chris Vanderloo → MIT Lincoln Laboratory; Gary Wang → Amazon Web Services
  • MS 2018 (RPI). Robert Martino → Assured Information Security - AIS; Tyler Shepherd → Microsoft.
  • MS 2017 (RPI). Binghui Deng → Corning Inc; Jason Ko → Bloomberg.
  • MS 2016 (RPI). Peter Piech → FactSet Research Systems Inc. Kevin Hwang. → FactSet Research Systems Inc.
  • BS 2024 (RPI). Tyler Ho → MSAII at CMU; Mason duBoef
  • BS 2023 (RPI). Daniel Della Vecchia → MSCS at CMU
  • BS 2022 (RPI). Ben Kelly (4.0 Award, Founders Award of Excellence) → Ph.D. at U. Michigan; Jingwen Qian (Paul A. McGloin Prize, 4.0 Award, Founders Award of Excellence) → Google; Haoyu Chen → MS ECE at CMU; Yuxuan Chen → MS CS at Columbia
  • BS 2021 (RPI). Shikan Chen → MS at UCSD; Shuo Han → MS ECE at CMU; Yutao Sun→M. Eng CS at Cornell; Yanting Wang→MS at Duke→PhD at PSU; Weijian Zeng→ MS at Columbia
  • BS 2020 (RPI). Wufei Ma→CS Ph.D. at JHU; Lei Luo→CS M.S. at Duke; Yiwei Chen→CS M.S. at NYU; Gavriel Zahavi
  • BS 2019 (RPI). Paween Pitimanaaree→ master student at Imperial College London; Kaijian Zhong→ master student at U. Toronto → Google; Chang Xu → master student at Duke CS; Shuze Liu → master student at Yale CS→ CS Ph.D. at UVa; Junming Wang → master student at Stanford CS; William Hsu→ Amazon; Yanlin Zhu→Bloomberg.
  • BS 2018 (RPI). Mengyi Li→ master student at Columbia CS; Haoming Li → master student at Duke EconCS→ CS Ph.D. at USC; Xiaochuang Yuan →Amazon; Tristan Villamil→Clean Power Research.
  • BS 2017 (RPI). Chaonan Ye → master student at Stanford CS.
  • BS 2016 (RPI). Samuel Yuan →master student at CMU.

TEACHING

Economics and Computation

  • 2025S
  • (RPI) 2023F, 2023S, 2022S, 2021S, 2020S, 2019S

Introduction to Artificial Intelligence

  • (RPI) 2024S, 2023S, 2022S, 2021S, 2020S, 2019S, 2018S, 2017S, 2014S

Computational Social Choice

  • (RPI) 2016S, 2014F, 2013F

Computational Social Processes

  • (RPI) 2016F

Introduction to Algorithms

  • (RPI) 2017F, 2016S

Computer Science Graduate Skills Seminar

  • (RPI) 2023F, 2022F, 2021F, 2021S, 2019F