Chao Zhang

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

Office: CODA 1309
Address: 756 W Peachtree St NW, Atlanta, GA 30308
Email: chaozhang@gatech.edu

Hi! I am an Assistant Professor at the School of CSE at Georgia Tech. Before joining Georgia Tech, I received my Ph.D. in Computer Science from UIUC in 2018, where I worked with Prof. Jiawei Han.

Research

Research Interests

I develop machine learning and data-driven approaches, for solving practical prediction and design problems in science and engineering. The problems I currently study are often motivated by and find applications in material science, biomedical science, and public health. On the data side, I work a lot with spatiotemporal data, text data, and graph data. On the methodology side, I am interested in developing more robust and data-efficient ML models for these problems, via probabilistic modeling, uncertainty quantification, self-supervised learning, and weakly-supervised learning.

My broader interests include:

  • Data Mining: Spatiotemporal Data Mining, Text Mining, Graph Mining
  • Machine Learning: Probabilistic & Uncertainty-Aware Models, Decision Making Under Uncertainty, Learning from Limited Supervision
  • Natural Language Processing: Information Extraction

Research Projects

Ongoing research projects at my group include:

News

  • [Pinned] Check out my book Multidimensional Mining of Massive Text Data published by Morgan & Claypool, also available on Amazon.
  • Grateful to receive 2021 Facebook Faculty Research Award.
  • Multiple papers accepted by KDD'20 and ICML'20.
  • Multiple papers accepted by EMNLP'20, and NAACL'21.
  • Congrats to my student Wendi Ren for winning the Marshall D. Williamson Fellowship.
  • Grateful to receive 2020 Amazon Faculty Award.
  • Thanks to NSF for supporting our research on using transformers for sequential data.
  • Grateful to receive 2020 Google Faculty Research Award.
  • Two papers accepted by the Web Conference 2020.
  • Honored to receive the ACM SIGKDD 2019 Dissertation Runner-up Award.

Publications

(* denotes equal contribution)

2021

2020

2019

2018

2017

2016

2015

2014

Earlier

Awards

  • 2021 Facebook Faculty Research Award
  • 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

Software

  • SDE-Net: Efficient uncertainty estimation for deep neural networks
  • 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

Teaching

Students

Prospective students: I am always looking for strong and motivated students to join our group. But due to the large volume of emails I receive, I am unable to respond to every email. If you are interested in working with me, please fill out this form, for which I will review the responses regularly. You can also apply to GT's related Ph.D. Programs (CSE, CS, ML) and specify my name in your applications.

Current:

  • Rui Feng: Ph.D. Student in CS
  • Lingkai Kong: Ph.D. Student in CSE
  • Yinghao Li: Ph.D. Student in ML
  • Kevin Tynes: Ph.D. Student in ML
  • Yanbo Xu: Ph.D. Student in ML
  • Yue Yu: Ph.D. Student in CSE
  • Rongzhi Zhang: Ph.D. Student in ML
  • Yuchen Zhuang: Ph.D. Student in ML

Alumni:

  • Isaac Rehg: M.S. in CS
  • Wendi Ren: M.S. in CSE
  • Ruijia Wang: M.S. in CSE
  • Yi Rong: Visiting Ph.D. Student