Xintong Wang 王欣曈 Ph.D. Candidate in Computer Science and Engineering University of Michigan Email: xintongw@umich.edu Office: BBB 3945

Hi! I am a Ph.D. student in the Computer Science and Engineering Department at University of Michigan.
I am advised by Prof. Michael P. Wellman and work in the Strategic Reasoning Group (SRG).
Before coming to Michigan, I received my bachelor degree from Washington University in St. Louis in 2015.

• Market Manipulation: An Adversarial Learning Framework for Detection and Evasion.
  Xintong Wang and Michael P. Wellman.
  International Joint Conference on Artificial Intelligence (IJCAI) 2020.
  Preliminary version presented at the NeurIPS-19 Workshop on Robust AI in Financial Services: Data, Fairness, Explainability, Trustworthiness, and Privacy.

  @inproceedings{wang2020advgan,
    title = {Market Manipulation: An Adversarial Learning Framework for Detection and Evasion.},
    author = {Wang, Xintong and Wellman, Michael P.},
    booktitle = {29th International Joint Conference on Artificial Intelligence (IJCAI)},
    year = {2020}
  }
  

[bib] [paper]



• Learning-Based Trading Strategies in the Face of Market Manipulation
  Xintong Wang, Christopher Hoang, and Michael P. Wellman
  ACM International Conference on AI in Finance (ICAIF) 2020.
  Preliminary version presented at the ICML-19 Workshop on AI in Finance: Applications and Infrastructure for Multi-Agent Learning.

  @inproceedings{wang2020lts,
    title = {Learning-Based Trading Strategies in the Face of Market Manipulation.},
    author = {Wang, Xintong and Hoang Christopher and Wellman, Michael P.},
    booktitle = {ACM International Conference on AI in Finance (ICAIF)},
    year = {2020}
  }
  

[bib] [paper][slides][poster]



• Generating Realistic Stock Market Order Streams
  Junyi Li, Xintong Wang, Yaoyang Lin, Arunesh Sinha, and Michael P. Wellman.
  AAAI Conference on Artificial Intelligence (AAAI) 2020.
  Preliminary version presented at the ICML-19 Workshop on AI in Finance: Applications and Infrastructure for Multi-Agent Learning.

  @inproceedings{li2020stockgan,
    title = {Generating Realistic Stock Market Order Streams},
    author = {Li, Junyi and Wang, Xintong and Lin, Yaoyang and Sinha, Arunesh and Wellman, Michael P.},
    booktitle = {34th AAAI Conference on Artificial Intelligence (AAAI)},
    pages     = {727--734},
    year = {2020}
  }
  

[bib] [paper][slides] [poster]



• Studies on the Computational Modeling and Design of Financial Markets
  Xintong Wang.
  International Conference on Autonomous Agents and Multiagent Systems, Doctoral Consortium (AAMAS) 2019.

  @inproceedings{wang2019dc,
    title     = {Studies on the Computational Modeling and Design of Financial Markets},
    author    = {Wang, Xintong},
    booktitle = {18th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS)},          
    pages     = {2452--2454},
    year      = {2019}
  }
  

[bib] [paper][slides] [poster]



• A Cloaking Mechanism to Mitigate Market Manipulation
  Xintong Wang, Yevgeniy Vorobeychik, and Michael P. Wellman.
  International Joint Conference on Artificial Intelligence (IJCAI) 2018.

  @inproceedings{wang2018cloaking,
    title     = {A Cloaking Mechanism to Mitigate Market Manipulation},
    author    = {Wang, Xintong and Vorobeychik, Yevgeniy and Wellman, Michael P.},
    booktitle = {27th International Joint Conference on Artificial Intelligence (IJCAI)},         
    pages     = {541--547},
    year      = {2018}
  }
  

[bib] [paper][slides] [poster]



• Spoofing the Limit Order Book: An Agent-Based Model
  Xintong Wang and Michael P. Wellman.
  International Conference on Autonomous Agents and Multiagent Systems (AAMAS) 2017.
  Preliminary version presented at the AAAI-17 Workshop on Computer Poker and Imperfect Information Games.

  @inproceedings{wang2017spoofing,
    title = {Spoofing the Limit Order Book: An Agent-Based Model},
    author = {Wang, Xintong and Wellman, Michael P.},
    booktitle = {16th Conference on Autonomous Agents and MultiAgent Systems (AAMAS)},
    pages = {651--659},
    year = {2017}
  }
  

[bib] [paper][slides] [poster]

• University of Michigan
  Sep. 2015 - Present
  Ph.D. student in Computer Science and Engineering


• Washington University in St. Louis
  Aug. 2011 - May. 2015
  B.S. in Computer Science
  Second Major in Mathematics, Finance

• Research Intern at J.P. Morgan AI Research, New York City, NY.
  May. 2019 - Aug. 2019
  Mentor: Tucker Balch and Manuela Veloso


• Research Intern at Microsoft Research, New York City, NY.
  May. 2018 - Aug. 2018
  Mentors: David Pennock and David Rothschild


• Algorithmic Trading Summer Intern at IMC Financial Markets, Chicago, IL.
  May. 2014 - Aug. 2014
  Mentor: Floris Ouwendijk

• Selected as one of the Rising Stars in EECS, 2019
• Travel grants: AAMAS 2017, IJCAI 2018, Rackham Conference Travel Grant 2017-2018, CRA-W Grad Cohort Workshop 2017,
  Grace Hopper Celebration 2018
• D. E. Shaw Exploration Fellowship, July 2017
• Graduated Magna cum laude, Distinction in Mathematics, Washington University in St. Louis, 2015
• Washington University Scholarship, Washington University in St. Louis, 2014 - 2015
• Dean's List, Washington University in St. Louis, 2011 - 2015

• Graduate Student Instructor for EECS203: Discrete Mathematics, University of Michigan, Fall 2015.
• Tutor for Computer Science I: Java Programming, Washington University in St. Louis, 2013-2015
• Teaching Assistant for Microeconomics, Olin Business School, Washington University in St. Louis, Spring 2013.
• Teaching Assistant for Introduction to Management, Olin Business School, Washington University in St. Louis, Fall 2012, 2013, 2014.

• I am actively involved in AI seminar tsar, The Ensemble of CSE Ladies (ECSEL) mentor, and Intramural badminton team. Let me know if
  you are interested in participating any of these!
• My name is pronounced as "shīn-tóng", meaning twilight before sunrise.
• I grew up in Beijing, China.
• When I am not doing research, I love to play badminton, play card games, go/plan roadtrip, and watch movies.

• Some resources I find inspiring and encouraging! [Expand]
  - Adversarial ML Tutorial.
  - Special Topics on Adversarial Machine Learning by Bo Li at UIUC.
  - BAIR blog.
  - Bitcoin Resources.
  - Andrej Karpathy's blog on A Survival Guide to a PhD.