Chao Zhang

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Assistant Professor
School of Computational Science and Engineering
College of Computing
Georgia Institute of Technology

Office: CODA E1358B
Address: 756 W Peachtree St NW, Atlanta, GA 30308


I develop machine learning and data-centric solutions to build AI models for task support and decision making. My research is focused on two primary themes: (1) Data-Centric AI – How can we enhance AI models by addressing challenges in data quality and data scarcity? (2) Trustworthy AI – How can we make AI models more reliable and better aligned with human values? The ultimate goal is to rapidly develop more data-efficient and trustworthy AI systems that are customized for diverse domains in science and engineering. Currently, my group is actively working on the following topics:

  • Large Language Models – Language model agents; Aligning LLMs to make them more trustworthy.
  • Learning from Noisy Data – Fine-tuning language models with easy-to-obtain noisy labels.
  • Uncertainty Quantification and Decision Making – Quantifying uncertainty in deep learning; Decision making under uncertainty.
  • Spatiotemporal Dynamics and Design – Deep learning to simulate and forecast spatiotemporal dynamics (e.g., molecular simulation) for optimizing spatiotemporal systems.

On the application side, I am passionate about interdisciplinary research and enjoy developing data-driven solutions to accelerate scientific discovery through close collaboration with domain experts. The techniques I develop are motivated by applications in material science, biomedical science, transportation, and public health.

Acknowledgment: My work has been generously supported by research funding/gift from NSF (IIS CAREER-2144338, IIS-2106961, IIS-2008334), ONR MURI , Kolon, HomeDepot, ADP, and Adobe. My work has also been recognized by an NSF CAREER Award, a Facebook Faculty Award, an Amazon AWS Machine Learning Research Award, a Google Faculty Research Award, a Kolon Faculty Fellowship, an ACM SIGKDD Dissertation Runner-up Award, and several paper awards from IMWUT (UbiComp), ECML/PKDD, and ML4H.


Below are the main research projects at my group and some recent representative works:


  • 2022 ML4H Outstanding Paper Award
  • 2022 NSF Career Award
  • 2021 Facebook Faculty Research Award
  • 2021 Kolon Faculty Fellowship
  • 2020 Amazon AWS Machine Learning Research Award
  • 2020 Google Faculty Research Award
  • 2019 ACM SIGKDD Dissertation Award Runner-up
  • 2018 ACM IMWUT Distinguished Paper Award
  • 2015 ECML/PKDD Best Student Paper Runner-up Award
  • 2013 Chiang Chen Overseas Graduate Fellowship


(* denotes equal contribution)









  • SDE-Net: Efficient uncertainty estimation for deep neural networks
  • CHMM: BERT-conditional hidden Markov model for multi-source weakly-supervised learning
  • COSINE: Language model fine-tuning with weak supervision
  • BOND: Distantly-supervised named entity recognition
  • STEAM: Automatic taxonomy expansion
  • TaxoGen: Unsupervised topic taxonomy construction from text corpus
  • WestClass: Weakly-supervised text classification
  • GeoBurst: Unsupervised spatiotemporal event detection



Prospective students: I am always looking for strong and motivated students to join our group. If you are interested in working with me, you can either email me or fill out this form.


  • Rui Feng: Ph.D. Student in CS
  • Lingkai Kong: Ph.D. Student in CSE
  • Yinghao Li: Ph.D. Student in ML
  • Agam A. Shah: Ph.D. Student in ML (co-advised with Sudheer Chava)
  • Phillip Si: Ph.D. Student in CSE (co-advised with Peng Chen)
  • Haotian Sun: Ph.D. Student in ML (co-advised with Bo Dai)
  • Haorui Wang: Ph.D. Student in CSE
  • Kuan Wang: Ph.D. Student in CSE
  • Yue Yu: Ph.D. Student in CSE
  • Rongzhi Zhang: Ph.D. Student in ML
  • Yuchen Zhuang: Ph.D. Student in ML
  • Jacob Wessell: M.S. student in CS
  • Wenhao Mu: M.S. student in CS
  • Shangqing Xu: M.S. student in CS


  • Yanbo Xu: Ph.D., 2023 (First Employment: Microsoft Research)
  • Binghong Chen: Ph.D., 2023 (co-advised with Prof. Le Song, First Employment: Citadel Capital)
  • Pranav Shetty: Ph.D., 2023 (JP Morgan AI Ph.D. Fellowship, co-advised with Prof. Rampi Ramprasad, First Employment: JP Morgan Chase)
  • Vidit Jain: M.S. Student in CS
  • Mukund Rungta: M.S. Student in CS
  • Junyang Zhang: M.S. Student in CS
  • Piyush Patil: M.S. Student in CS
  • Mengyang Liu: M.S. Student in CSE
  • Isaac Rehg: M.S. in CS
  • Wendi Ren: M.S. in CSE
  • Ruijia Wang: M.S. in CSE
  • Yi Rong: Visiting Ph.D. Student