I am an Assistant Professor in the Department of Computer Science at Purdue University. Before that, I was a postdoctoral fellow at Institute for Foundations of Machine Learning, UT Austin. I completed my PhD at Cornell University, where I was advised by Chris De Sa.
I am looking for highly motivated students (PhD, MS, undergrads, and interns) to join our lab. If you are interested, feel free to reach out.
I am interested in developing scalable, reliable and efficient probabilistic methods for machine learning and generative AI. Our work bridges theoretical foundations and practical implementations, aiming to address fundamental challenges in building trustworthy and efficient AI systems. Currently, I focus on the following key directions: (1) alignment and safety of foundation models, including LLMs, VLMs, and diffusion models; (2) Probabilistic inference, uncertainty estimation, and Bayesian methods; and (3) Generation and learning on discrete data.
Pascal Jutras-Dube, Patrick Pynadath, Ruqi Zhang Preprint, 2025 [Paper]
Debadyuti Mukherjee, Chris Zhuang, Yingzhou Lu, Tianfan Fu, Ruqi Zhang Preprint, 2025 [Paper][Code]
Bolian Li, Yifan Wang, Ananth Grama, Ruqi Zhang Preprint, 2024 [Paper][Code]
Wenlong Chen, Bolian Li, Ruqi Zhang, Yingzhen Li Chapter in the 2nd edition of the Handbook of Markov Chain Monte Carlo, 2025 [Paper]
Muheng Li, Ruqi Zhang Transactions on Machine Learning Research (TMLR), 2025 [Paper][Code]
Yi Ding, Bolian Li, Ruqi Zhang International Conference on Learning Representations (ICLR), 2025 [Paper][Code][Project Page]
Patrick Pynadath, Ruqi Zhang International Conference on Learning Representations (ICLR), 2025 [Paper][Code][Project Page]
Xinyang Liu, Hengrong Du, Wei Deng, Ruqi Zhang International Conference on Artificial Intelligence and Statistics (AISTATS), 2025 [Paper][Code]
Bolian Li, Ruqi Zhang Transactions on Machine Learning Research (TMLR), 2025 [Paper][Code]
Xukun Liu, Bowen Lei, Ruqi Zhang, Dongkuan Xu The 39th Annual AAAI Conference on Artificial Intelligence (AAAI), 2025 [Paper][Code][Project Page]
Patrick Pynadath, Riddhiman Bhattacharya, Arun Hariharan, Ruqi Zhang Neural Information Processing Systems (NeurIPS), 2024 [Paper][Code]
Pascal Jutras-Dube, Ruqi Zhang, Aniket Bera International Conference on Intelligent Robots and Systems (IROS), 2024 [Paper][Code]
Theodore Papamarkou, Maria Skoularidou, [and 20+ authors], Ruqi Zhang International Conference on Machine Learning (ICML), 2024 [Paper]
Ziyi Wang, Yujie Chen, Qifan Song, Ruqi Zhang Transactions on Machine Learning Research (TMLR), 2024 [Paper][Code]
Bowen Lei, Dongkuan Xu, Ruqi Zhang, Bani K Mallick Transactions on Machine Learning Research (TMLR), 2024 [Paper][Code]
Junbo Li, Zichen Miao, Qiang Qiu, Ruqi Zhang International Conference on Learning Representations (ICLR), 2024 [Paper][Code]
Bolian Li, Ruqi Zhang International Conference on Learning Representations (ICLR), 2024 [Paper][Code]
Bowen Lei, Dongkuan Xu, Ruqi Zhang, Shuren He, Bani K Mallick Conference on Parsimony and Learning (CPAL), 2024 [Paper][Code]
Dongyao Zhu, Bowen Lei, Jie Zhang, Yanbo Fang, Yiqun Xie, Ruqi Zhang, Dongkuan Xu International Conference on Computer Vision (ICCV), 2023 [Paper][Code]
Katayoon Goshvadi, Haoran Sun, Xingchao Liu, Azade Nova, Ruqi Zhang, Will Grathwohl, Dale Schuurmans, Hanjun Dai Neural Information Processing Systems (NeurIPS) Datasets and Benchmarks Track, 2023 Short Version at ICML Workshop on Sampling and Optimization in Discrete Space, 2023 [Paper][Code]
Bolian Li, Ruqi Zhang Symposium on Advances in Approximate Bayesian Inference (AABI), 2023 [Paper]
Tunazzina Islam, Ruqi Zhang, Dan Goldwasser AAAI/ACM Conference on AI, Ethics, and Society (AIES), 2023 Oral Presentation, top 11% [Paper]
Wanrong Zhang, Ruqi Zhang International Conference on Machine Learning (ICML), 2023 [Paper][Code]
Bowen Lei, Ruqi Zhang, Dongkuan Xu, Bani K Mallick International Conference on Learning Representations (ICLR), 2023 [Paper][Code]
Yue Xiang, Dongyao Zhu, Bowen Lei, Dongkuan Xu, Ruqi Zhang International Conference on Artificial Intelligence and Statistics (AISTATS), 2023 [Paper][Code]
Ruqi Zhang, Qiang Liu, Xin T. Tong Neural Information Processing Systems (NeurIPS), 2022 [Paper][Code]
Ruqi Zhang, Xingchao Liu, Qiang Liu International Conference on Machine Learning (ICML), 2022 [Paper] [Code][Video][Slides]
Ruqi Zhang, Andrew Gordon Wilson, Christopher De Sa International Conference on Machine Learning (ICML), 2022 [Paper] [Code][Video][Slides]
Ruqi Zhang, Yingzhen Li, Christopher De Sa, Sam Devlin, Cheng Zhang International Conference on Artificial Intelligence and Statistics (AISTATS), 2021 [Paper]
Ruqi Zhang, A. Feder Cooper, Christopher De Sa Neural Information Processing Systems (NeurIPS), 2020 Spotlight Presentation, top 3% [Paper][Code][Video][Slides]
Ruqi Zhang, A. Feder Cooper, Christopher De Sa International Conference on Artificial Intelligence and Statistics (AISTATS), 2020 [Paper] [Code]
Ruqi Zhang, Chunyuan Li, Jianyi Zhang, Changyou Chen, Andrew Gordon Wilson International Conference on Learning Representations (ICLR), 2020 Oral Presentation, top 2% [Paper] [Code][Video][Slides] [BlackJAX Implementation]
Ruqi Zhang, Christopher De Sa Neural Information Processing Systems (NeurIPS), 2019 Spotlight Presentation, top 2.5% [Paper] [Code] [Poster] [Slides]
Ruqi Zhang, Zhiwu Lu International Joint Conference on Artificial Intelligence (IJCAI), 2016 [Paper]
Invited talk at NeurIPS 2023 Workshop on ML with New Compute Paradigms, December 2023 [Video (my talk starts at 2:32:25)][Slides]
Invited talk at ICML 2023 Workshop on Structured Probabilistic Inference & Generative Modeling, July 2023 [Video (my talk starts at 5:32:25)][Slides]
Center for Data Science and Machine Learning, National University of Singapore, October 2022 Invited talk at Simons Institute, UC Berkeley, November 2021 [Video][Slides]
Spotlight talk in Rising Stars in Data Science Workshop at University of Chicago, January 2021 Spotlight presentation at NeurIPS, December 2020 [Video][Slides]
Spotlight presentation at NeurIPS, December 2019 [Slides]
