Xueru Zhang
Profile - xueru zhang

I am an Assistant Professor in the Department of Computer Science and Engineering at The Ohio State University. I am also affiliated with the Translational Data Analytics Institute and Center on Responsible AI and Governance.

At OSU, I lead the Ethical and Trustworthy Human-Intelligent Computing (ETHIC) Lab, where we advance the theoretical and algorithmic foundations of trustworthy machine learning in high-stakes, dynamic, multi-agent, and human-interactive environments. This includes (1) understanding the societal and economic impacts of ML systems; (2) developing principled methods that enhance algorithmic fairness, privacy, robustness, safety, interpretability, and alignment with human values; and (3) designing steering and incentive mechanisms that guide multi-agent and human-ML interactions toward socially beneficial outcomes. These efforts have broad interdisciplinary impact across healthcare, earth sciences, finance, transportation, and social domains.

For more details, please see my group and publications. Our research is generously supported by the National Science Foundation, Cisco, Center for Clinical and Translational Science, and Nationwide Children's Hospital, and OSU Translational Data Analytics Institute.

Prior to joining OSU, I completed my PhD under the supervision of Mingyan Liu at the University of Michigan.


I am always looking for highly motivated students! Please see group page for details.



News

  • [11/2025] – Our work is featured in “Chicago Booth Review.”
  • [11/2025] – Presented “Reliable Federated Learning in Dynamic Environments” at Federated Learning in the Generative AI Era Workshop.
  • [2024-2025] We are organizing TDAI Yearlong Research Themes: The Geometrization of AI: Bridging the Gap Between Geometric Structures and Statistical Models. Reach out if you are interested in giving a talk!
  • [11/2025] – Check out our AAAI and AAAI-AISI papers on algorithmic fairness, robustness, and reliable generative AI: stabilizing self-consuming diffusion models (AAAI), tackling unfairness in performative prediction (AAAI), enhancing fairness without harm (AAAI-AISI), fair AI in medical image prognosis (NeurIPS)
  • [07/2025] – Check out our ICML, AAAI, AAAI-AISI, and IISWC papers on generative models, domain adaptation, and AI systems: self-consuming generative models (ICML), open-set heterogeneous domain adaptation (AAAI), drought prediction (AAAI-AISI), benchmarking AI accelerators for LLMs (IISWC)
  • [02/2025] – Presented “Long-Term Safety for Human-AI Ecosystem” at NSF Workshop on the Science of Safe AI.
  • [11/2024] – Organized Workshop on Machine Learning under Strategic Behavior and Social Dynamics, TDAI Interdisciplinary Research Fall Forum, OSU.
  • [2024] – Awarded College of Engineering Strategic Research Initiative Grant.
  • [10/2024] – NSF Safe Learning-Enabled Systems (SLES) Program grant on “Long-Term Safety for Human-AI Ecosystems.” See detalis here.
  • [07/2024] – Check out our NeurIPS, TMLR, AAAI, and AAAI-AIES papers on fairness, federated learning, and strategic learning:
  • [07/2024] – Check out our UAI papers on domain generalization and privacy-preserving ML: privacy-aware quantization (UAI), non-stationary domain generalization (UAI)
  • [04/2024] – Participated in ShowOHI/O Panel Discussion at Ohio State's Tech Entrepreneurship Showcase.
  • [04/2024] – Presented “How Do Models Fare when Retrained with Human Strategic Feedback?” at Midwest Machine Learning Symposium.
  • [02/2024] – Presented “Ethical Machine Learning under Social Dynamics” at ShowOHI/O Keynote.
  • [12/2023] - I will lead the discussion on "long-term fairness" in Algorithmic Fairness through the Lens of Time workshop at NeurIPS.
  • [12/2023] - One paper "Performative Federated Learning: A Solution to Model-Dependent and Heterogeneous Distribution Shifts" got accpeted in AAAI 2024.
  • [9/2023] - Check out our paper "Counterfactually Fair Representation" in NeurIPS 2023!
  • [06/2023] - Our paper "Loss Balancing for Fair Supervised Learning" got accpeted in ICML 2023.
  • [05/2023] - I gave a talk about strategic classification at "Midwest Machine Learning Symposium". Check out the slide here.
  • [03/2023] - Thrilled to receive Translational Data Analytics Institute (TDAI) Interdisciplinary Research Pilot Awards at OSU!
  • [01/2023] - Our paper "Fairness and Accuracy under Domain Generalization" got accpeted in ICLR 2023.
  • [10/2022] - Thanks Cisco for supporting our research!
  • [09/2022] - New grant from NSF to work on fairness in machine learning.
  • [08/2022] - Thrilled to receive Center for Clinical and Translational Science (CCTS) Pilot Award at OSU.
  • [06/2022] - I gave a talk "Towards Ethical AI: Improving Model Fairness and Privacy in Online Marketing and Advertising" at Walmart Global Tech.
  • [06/2022] - I am co-organizing the Deep Learning Summer School at OSU.
  • [05/2022] - Our paper "Fairness Interventions as (Dis)Incentives for Strategic Manipulation" got accpeted in ICML 2022.
  • [05/2022] - Our paper "Incentive Mechanisms for Strategic Classification and Regression Problems" got accpeted in EC 2022.
  • [05/2022] - Our paper "Differentially Private Real-Time Release of Sequential Data" got accpeted in ACM Transactions on Privacy and Security.
  • [04/2022] - I served as a penalist at CogFest 2022.
  • [04/2022] -Thrilled to receive President’s Research Excellence Accelerator Award at OSU.
  • [01/2022] - I am co-organizing the ICLR 2022 Workshop on Socially Responsible Machine Learning (SRML). Please submit your paper here.
  • [12/2021] - I am invited to give a talk in USC ML Symposium.
  • [10/2021] - One paper got accepted to the 35th Conference on Neural Information Processing Systems (NeurIPS).
  • [10/2021] - One paper got accepted to IEEE International Conference on Data Mining (ICDM).
  • [6/2021] - I am invited to give a talk in Caltech's Young Investigator Forum.
  • [6/2021] - I am co-organizing the Workshop on Socially Responsible Machine Learning in ICML 2021. Please submit your paper here.
  • [12/2020] - One paper got accepted to the 35th AAAI Conference on Artificial Intelligence (AAAI).
  • [10/2020] - I was selected to participate in EECS Rising Stars workshop.
  • [09/2020] - One paper got accepted to the 34th Conference on Neural Information Processing Systems (NeurIPS).
  • [07/2020] - I gave a talk at the University of Michigan-Shanghai Jiao Tong University Joint Institute.
  • [07/2020] - We (with Swetasudha Panda and Emily Black) organized the session Fairness and bias in ML and NLP at the WiML Un-Workshop at ICML 2020.
  • [04/2020] - I was awarded Rackham Predoctoral Fellowship.
  • [03/2020] - One paper got accepted to 2020 American Control Conference (ACC).
  • [02/2020] - I gave a talk on Graduation Day at Information Theory and Applications (ITA) Workshop.