Dr. Xinyi Zhou is an Assistant Professor in the Computer Science Department at Boise State University. She was a Postdoctoral Scholar in the Paul G. Allen School of Computer Science & Engineering at the University of Washington. She earned her Ph.D. in Computer and Information Science and Engineering from Syracuse University. Her research interests span machine learning and data science, with a focus on trustworthy, multimodal, and human-centered AI. Her work has been published in journals such as ACM Computing Surveys and conferences including WWW, CHI, CIKM, WSDM, and ICWSM. She received two Rising Star awards in 2024: one in EECS from MIT, and another in Data Science from UCSD, UChicago, and Stanford. For more details, please visit http://xinyizhou.xyz/.

2024

• Madrona Prize (featured in Madrona News, GeekWire), Madrona Venture Group
• Rising Stars in Data Science, University of California San Diego, University of Chicago, and Stanford University
• Rising Stars in EECS, Massachusetts Institute of Technology
• Postdoc Research Award ($9,200), University of Washington

2023

• All-University Doctoral Prize (highest dissertation award), Syracuse University

2022

• Data Science Postdoctoral Fellow, University of Washington
• Research Excellence Doctoral Funding ($10,438), Syracuse University

2020

• Varshney Scholarship (featured in Syracuse University News), Syracuse University

2018

• Top 100 Influential Papers of 2017, Ministry of Science and Technology of China

2016

• National Scholarship, Ministry of Education of China

Ph.D. Qualifying Examination Committee Member

2025

• Garumuni Isuru Chamara Lakmal De Zoysa (Department of Mathematics at Boise State University)

Program Committee Member

2023–2026

• AAAI Intl. Conf. on Artificial Intelligence (AAAI)
• ACM Intl. Conf. on Information and Knowledge Management (CIKM)
  2023
• European Conf. on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD)
• IEEE Intl. Joint Conf. on Neural Networks (IJCNN)

2022–2026

• ACM Intl. Conf. on Knowledge Discovery and Data Mining (KDD, Applied Data Science)
• ACM Intl. Conf. on Web Search and Data Mining (WSDM)

2022

• ACM Intl. Conf. on Information and Knowledge Management (CIKM, Short Papers)
• ACM Intl. Conf. on Human Information Interaction & Retrieval (CHIIR, Demos/Resources)

2021–2024

• IEEE Intl. Conf. on Cognitive Machine Intelligence (CogMI)

2021–2023

• ACM Intl. Conf. on Research and Development in Information Retrieval (SIGIR, Resources)

2021–2022

• IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)

2021

• European Conference on Information Retrieval (ECIR, Tutorials)

2020–2021

• ACM Intl. Conf. on Information and Knowledge Management (CIKM, Resources)

Journal Reviewer

2025

• IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)

2023

• World Wide Web: Internet and Web Information Systems (WWW)
• Knowledge and Information Systems (KAIS)

2022, 2025

• IEEE Transactions on Computational Social Systems (TCSS)

2022, 2024

• ACM Transactions on Information Systems (TOIS)

2022

• OMEGA-International Journal of Management Science

2021, 2024

• ACM Transactions on the Web (TWEB)

2021

• IEEE Transactions on Knowledge and Data Engineering (TKDE)
• IEEE Transactions on Information Forensics and Security (TIFS)
• Pattern Recognition Letters (PRL)

2020–2025

• ACM Computing Surveys (CSUR)

2020, 2022

• Neurocomputing

2020–2021

• IEEE Transactions on Multimedia (TMM)
• Social Network Analysis and Mining (SNAM)

2020

• ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM)
• IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
• ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP)
• IEEE Transactions on Emerging Topics in Computational Intelligence (TETCI)
• Information Processing and Management (IPM)

2019

• ACM Digital Threats: Research and Practice (DTRAP)