Quang Truong

Bio

I am a second-year Ph.D. student supervised by Dr. Jiliang Tang at Michigan State University (MSU). Before joining MSU, I did my M.S. at Dartmouth College. I also graduated summa cum laude in Computer Science at Texas Christian University.

I am broadly interested in graph-related problems. My area of specialization is at the intersections of Machine Learning on Graphs and Topological Deep Learning. In the past, I had opportunities to participate in Computer Vision projects, specifically Vehicle Re-identification and 3D Object Detection.

I am always open to collaborations and discussions. Feel free to reach out to me via email! 🖐️

News

• [02/2026] Our preprint Plain Transformers are Surprisingly Powerful Link Predictors is now online on arXiv!
• [01/2026] I started my internship at Nokia as an AI/R&D Engineer Co-op at Sunnyvale, CA! 🌴
• [10/2025] I am honored to receive the NeurIPS 2025 Scholar Award! 🎉
• [09/2025] Paper A Pre-training Framework for Relational Data with Information-theoretic Principles has been accepted to NeurIPS 2025. See you in San Diego! ✈️
• [07/2025] Our preprint on Relational Deep Learning is now online on arXiv.
• [01/2025] Our TopoX paper is published in the Journal of Machine Learning Research (JMLR)! 🎉
• [08/2024] I will join Michigan State University as a Ph.D. student in the Department of Computer Science and Engineering! 🥳 🎉
• [03/2024] I will give a talk on Topological Deep Learning at the HPCC Special Seminar, an event hosted by the Advanced Institute of Interdisciplinary Science and Technology - HCMUT, VNU-HCM.
• [02/2024] TopoX article is now online on arXiv! TopoX is a suite of libraries facilitating deep learning on topological spaces.
• [01/2024] Our paper was mentioned in the blog Graph & Geometric ML in 2024: Where We Are and What's Next, a comprehensive review of highlights from the fields in 2023. So proud to be a part of an ever-growing community!
• [12/2023] Paper Weisfeiler and Lehman Go Paths: Learning Topological Features via Path Complexes has been accepted to AAAI 2024.
• [09/2023] We are proud to contribute our research to the TopoNetX initiative!

Publications

Most recent publications on Google Scholar.
^‡ indicates equal contribution.

• Selected
• All

@misc{truong2026plaintransformerssurprisinglypowerful,
  title={Plain Transformers are Surprisingly Powerful Link Predictors}, 
  author={Quang Truong and Yu Song and Donald Loveland and Mingxuan Ju and Tong Zhao and Neil Shah and Jiliang Tang},
  year={2026},
  eprint={2602.01553},
  archivePrefix={arXiv},
  primaryClass={cs.LG},
  url={https://arxiv.org/abs/2602.01553}, 
}

@misc{truong2025pretrainingframeworkrelationaldata,
  title={A Pre-training Framework for Relational Data with Information-theoretic Principles}, 
  author={Quang Truong and Zhikai Chen and Mingxuan Ju and Tong Zhao and Neil Shah and Jiliang Tang},
  year={2025},
  eprint={2507.09837},
  archivePrefix={arXiv},
  primaryClass={cs.LG},
  url={https://arxiv.org/abs/2507.09837}, 
}

@article{hajij2024topox,
  author  = {Mustafa Hajij and Mathilde Papillon and Florian Frantzen and Jens Agerberg and Ibrahem 
  AlJabea and Rub{{\'e}}n Ballester and Claudio Battiloro and Guillermo Bern{{\'a}}rdez and Tolga 
  Birdal and Aiden Brent and Peter Chin and Sergio Escalera and Simone Fiorellino and Odin Hoff 
  Gardaa and Gurusankar Gopalakrishnan and Devendra Govil and Josef Hoppe and Maneel Reddy Karri and 
  Jude Khouja and Manuel Lecha and Neal Livesay and Jan Meißner and Soham Mukherjee and Alexander 
  Nikitin and Theodore Papamarkou and Jaro Pr{{\'i}}lepok and Karthikeyan Natesan Ramamurthy and Paul 
  Rosen and Aldo Guzm{{\'a}}n-S{{\'a}}enz and Alessandro Salatiello and Shreyas N. Samaga and Simone 
  Scardapane and Michael T. Schaub and Luca Scofano and Indro Spinelli and Lev Telyatnikov and Quang 
  Truong and Robin Walters and Maosheng Yang and Olga Zaghen and Ghada Zamzmi and Ali Zia and Nina 
  Miolane},
  title   = {TopoX: A Suite of Python Packages for Machine Learning on Topological Domains},
  journal = {Journal of Machine Learning Research},
  year    = {2024},
  volume  = {25},
  number  = {374},
  pages   = {1--8},
  url     = {http://jmlr.org/papers/v25/24-0110.html}
}

@inproceedings{truong2024weisfeiler,
  title={Weisfeiler and Lehman Go Paths: Learning Topological Features via Path Complexes},
  author={Truong, Quang and Chin, Peter},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={38},
  number={14},
  pages={15382--15391},
  year={2024}
}

@misc{truong2026plaintransformerssurprisinglypowerful,
  title={Plain Transformers are Surprisingly Powerful Link Predictors}, 
  author={Quang Truong and Yu Song and Donald Loveland and Mingxuan Ju and Tong Zhao and Neil Shah and Jiliang Tang},
  year={2026},
  eprint={2602.01553},
  archivePrefix={arXiv},
  primaryClass={cs.LG},
  url={https://arxiv.org/abs/2602.01553}, 
}

@misc{truong2025pretrainingframeworkrelationaldata,
  title={A Pre-training Framework for Relational Data with Information-theoretic Principles}, 
  author={Quang Truong and Zhikai Chen and Mingxuan Ju and Tong Zhao and Neil Shah and Jiliang Tang},
  year={2025},
  eprint={2507.09837},
  archivePrefix={arXiv},
  primaryClass={cs.LG},
  url={https://arxiv.org/abs/2507.09837}, 
}

@article{hajij2024topox,
  author  = {Mustafa Hajij and Mathilde Papillon and Florian Frantzen and Jens Agerberg and Ibrahem 
  AlJabea and Rub{{\'e}}n Ballester and Claudio Battiloro and Guillermo Bern{{\'a}}rdez and Tolga 
  Birdal and Aiden Brent and Peter Chin and Sergio Escalera and Simone Fiorellino and Odin Hoff 
  Gardaa and Gurusankar Gopalakrishnan and Devendra Govil and Josef Hoppe and Maneel Reddy Karri and 
  Jude Khouja and Manuel Lecha and Neal Livesay and Jan Meißner and Soham Mukherjee and Alexander 
  Nikitin and Theodore Papamarkou and Jaro Pr{{\'i}}lepok and Karthikeyan Natesan Ramamurthy and Paul 
  Rosen and Aldo Guzm{{\'a}}n-S{{\'a}}enz and Alessandro Salatiello and Shreyas N. Samaga and Simone 
  Scardapane and Michael T. Schaub and Luca Scofano and Indro Spinelli and Lev Telyatnikov and Quang 
  Truong and Robin Walters and Maosheng Yang and Olga Zaghen and Ghada Zamzmi and Ali Zia and Nina 
  Miolane},
  title   = {TopoX: A Suite of Python Packages for Machine Learning on Topological Domains},
  journal = {Journal of Machine Learning Research},
  year    = {2024},
  volume  = {25},
  number  = {374},
  pages   = {1--8},
  url     = {http://jmlr.org/papers/v25/24-0110.html}
}

@inproceedings{truong2024weisfeiler,
  title={Weisfeiler and Lehman Go Paths: Learning Topological Features via Path Complexes},
  author={Truong, Quang and Chin, Peter},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={38},
  number={14},
  pages={15382--15391},
  year={2024}
}

@inproceedings{truong2021not,
  author={Quang Truong and Bo Mei},
  booktitle={2021 IEEE International Intelligent Transportation Systems Conference (ITSC)}, 
  title={Not All Data Matters: An Efficient Approach to Multi-Domain Learning in Vehicle Re-Identification}, 
  year={2021},
  volume={},
  number={},
  pages={1278-1285},
  doi={10.1109/ITSC48978.2021.9564945}
}

@article{truong2020imagebased,
  title={Image-based Vehicle Re-identification Model with Adaptive Attention Modules and Metadata Re-ranking},
  author={Quang Truong and Hy Dang and Zhankai Ye and Minh Nguyen and Bo Mei},
  journal={The Boller Review},
  volume={5},
  publisher={TCU Press},
  year={2020},
  doi={10.18776/tcu/br/5/130},
}

Open-Source Projects

TopoNetX: Computing with Relational Data Abstracted as Topological Domains

Stars -

Forks -

TopoNetX (TNX) is a package for computing with topological domains and studying their properties. With its dynamic construction capabilities and support for arbitrary attributes and data, TopoNetX allows users to easily explore the topological structure of their data and gain insights into its underlying geometric and algebraic properties.

Part of the TopoX suite, published in JMLR 2024

CV

Full CV in PDF.

• Nokia Corporation 2026 - Present

  AI/R&D Engineer Co-op
  CNS P&E AI
  Mentors: Dr. Liang Wu, Dr. Liangjie Hong
• Michigan State University 2024 - Present

  Ph.D. Student
  Computer Science
  Advisor: Dr. Jiliang Tang
• Dartmouth College 2022 - 2024

  M.S. Student
  Engineering Sciences
  Advisor: Dr. Peter Chin
• University of Illinois at Chicago 2021 - 2021

  Research Intern
  Vision Lab, Department of Computer Science
  Advisor: Dr. Wei Tang
• Texas Christian University 2019 - 2022

  B.S. Student
  Computer Science
  Summa Cum Laude
  Advisor: Dr. Bo Mei

Talks

[03/2024] Talk about Topological Deep Learning at HPCC Special Seminar: Decoding Computational Challenges, hosted by the Advanced Institute of Interdisciplinary Science and Technology - HCMUT, VNU-HCM.

Academic Services

• [Fall 2025] Conference Reviewer, Learning on Graphs (LoG).
• [Fall 2025] Program Committee Member / Conference Reviewer, Annual AAAI Conference on Artificial Intelligence (AAAI).
• [Summer 2025] Conference Reviewer, Conference on Neural Information Processing Systems (NeurIPS).
• [Summer 2025] Journal Reviewer, IEEE Transactions on Big Data (TBD).
• [Fall 2024] Conference Reviewer, International Conference on Learning Representations (ICLR).
• [Fall 2024] Journal Reviewer, ACM Transactions on Knowledge Discovery from Data (TKDD).

Teaching Experience

• [Fall 2025] CSE 335: Object-oriented Software Development - Teaching Assistant, Michigan State University.
• [Winter 2024] ENGS 96: Mathematics for Machine Learning - Teaching Assistant, Dartmouth College.

Misc.

Acknowledgement