ChengXiang Zhai

About

ChengXiang Zhai is the Donald Biggar Willett Professor in Engineering at the University of Illinois Urbana-Champaign, affiliated with the Siebel School of Computing and Data Science. His research areas include Artificial Intelligence, Bioinformatics and Computational Biology, Computers and Education, and Data and Information Systems. He has received numerous awards for his research and teaching, including the ACM SIGIR Gerard Salton Award in 2021, the ACM SIGIR Academy Membership in 2020, and the Presidential Early Career Award for Scientists and Engineers in 2004. Zhai has also been recognized for excellence in graduate student mentoring and undergraduate advising, and has received multiple teaching awards. His professional contributions are distinguished by his leadership in research and education within the field of computing and data science.

Research topics

• Computer Science
• Artificial Intelligence
• Machine Learning
• Engineering
• Data Mining
• Natural Language Processing
• Computational biology
• Biology
• Epistemology
• Philosophy

Selected publications

• AutoML to Date and Beyond: Challenges and Opportunities

  ACM Computing Surveys · 2021 · 279 citations

  As big data becomes ubiquitous across domains, and more and more stakeholders aspire to make the most of their data, demand for machine learning tools has spurred researchers to explore the possibilities of automated machine learning (AutoML). AutoML tools aim to make machine learning accessible for non-machine learning experts (domain experts), to improve the efficiency of machine learning, and to accelerate machine learning research. But although automation and efficiency are among AutoML’s ma…

  DOI

• Proceedings of the 34th ACM International Conference on Information and Knowledge Management

  2025-11-07 · 166 citations

  paratext

  Warm welcome to the 2016 ACM International Conference on Information and Knowledge Management (CIKM 2016)! is held annually at locations all over the world. The last two years it has been in Australia and China. In 2016 it returns to the United States in Indianapolis and is held Oct. 24-28. CIKM 2016 will be the 25th running of the conference, which remains the only conference that inherently focuses on the need for users to have unified systems that access structured and unstructured data. With…

  PublisherDOI

• Biosystems Design by Machine Learning

  ACS Synthetic Biology · 2020 · 134 citations

  Biosystems such as enzymes, pathways, and whole cells have been increasingly explored for biotechnological applications. However, the intricate connectivity and resulting complexity of biosystems poses a major hurdle in designing biosystems with desirable features. As -omics and other high throughput technologies have been rapidly developed, the promise of applying machine learning (ML) techniques in biosystems design has started to become a reality. ML models enable the identification of patter…

  DOI

• Joint Biomedical Entity and Relation Extraction with Knowledge-Enhanced Collective Inference

  2021 · 62 citations

  Tuan Lai, Heng Ji, ChengXiang Zhai, Quan Hung Tran. Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). 2021.

  DOI

• Theory and Toolkits for User Simulation in the Era of Generative AI: User Modeling, Synthetic Data Generation, and System Evaluation

  2025-07-13 · 16 citations

  articleOpen accessSenior author

  Interactive AI systems, including search engines, recommender systems, conversational agents, and generative AI applications, are increasingly central to user experiences. However, rigorously evaluating their performance, training them effectively with interaction data, and modeling user behavior for personalization remain significant challenges, often difficult to address reproducibly and at scale. User simulation, which employs intelligent agents to mimic human interaction patterns, offers a p…

  PublisherOA PDFDOI

Recent grants

• III-COR: QueryClinic: Improve Search Accuracy for Difficult Queries

  NSF · $397k · 2007–2011

• CDI-Type II: Collaborative Research: Joint Image-Text Parsing and Reasoning for Analyzing Social and Political News Events

  NSF · $500k · 2010–2015

• CAREER: User-centered Adaptive Information Retrieval

  NSF · $522k · 2004–2010

Frequent coauthors

• Jiawei Han

  University of Illinois Urbana-Champaign

  26 shared

• Hui Fang

  First Affiliated Hospital of Jiangxi Medical College

  26 shared

• Sean Massung

  25 shared

• Qiaozhu Mei

  24 shared

• Heng Ji

  22 shared

• Shanfeng Zhu

  Fudan University

  18 shared

• Shengwen Peng

  Fudan University

  18 shared

• Hiroshi Mamitsuka

  Kyoto University

  18 shared

Labs

• Siebel School of Computing and Data SciencePI

Education

• Ph.D., Computer Science

  University of Illinois at Urbana-Champaign

  2003

• M.S., Computer Science

  University of Illinois at Urbana-Champaign

  1999

• B.S., Computer Science

  University of Science and Technology of China

  1996

Awards & honors

• Campus Award for Excellence in Graduate Student Mentoring, U…
• Rose Award for Teaching Excellence, College of Engineering,…
• ACM SIGIR Gerard Salton Award (2021)
• ACM SIGIR Academy Member (2020)
• Donald Biggar Willett Professor in Engineering (2018)

Similar researchers at University of Illinois Urbana-Champaign

• Kaiyu Guanh-86
• Jimeng Sunh-82