in Zhan, Xueying (詹雪莹)

Zhan, Xueying (詹雪莹)

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Postdoctoral Research Associate
Gates Hillman Center 7601
Computational Biology Department, SCS
Carnegie Mellon University
5000 Forbes Avenue
Pittsburgh, PA 15213

Spare E-mail:

About me

I received the B.S. degree from Sun Yat-sen University, school of Data and Computer Science, in 2017. I received my PhD degree at City University of Hong Kong, department of Computer Science. From 2015 to 2017, I conducted research on Crowd-sourcing based on sentiment analysis tasks, supervised by Dr. Yanghui Rao. From 2017 to present, I conduct research on Active Learning, supervised by Prof. Antoni B. Chan and Prof. Qing Li. My main research interests include Machine Learning, Active Learning and Crowd-sourcing. Currently, I'm a Postdoc at CMU supervised by Prof. Min Xu.


My research interests include:

  • Active Learning, Machine Learning

  • Crowd-sourcing, Sentiment Analysis

  • Computational Biology, Biomedical Image Analysis


B.S. Sun Yat-sen University, school of Data and Computer Science, department of Mobile Information Engineering, 2013-2017.

  • The Third Prize Scholarship (Sep. 2014), 30% of department. The First Prize Scholarship (Sep. 2015), 5% of department. The Second Prize Scholarship (Sep. 2016), 10% of the department.

  • The Zhuhai Coca-Cola Scholarship for Outstanding Students (5/446).

  • Excellent Graduate (2017).

Ph.D. City University of Hong Kong, college of Science and Engineering, department of Computer Science. 2017-2023.

  • Research Tuition Scholarship, City University of Hong Kong. (Sep. 2019 - Aug. 2020).

  • Outstanding Academic Performance Award, City University of Hong Kong. (Aug. 2019)

  • Postgraduate Studentship, City University of Hong Kong. (Sep. 2017 - Aug. 2021)

Recent publications

  1. X. Zhan*, Z. Dai, Q. Wang, H. Xiong, Q. Li, D. Dou, Antoni B. Chan. Pareto Optimization for Active Learning under Out-of-Distribution Data Scenarios. Transactions on Machine Learning Research (TMLR). June 2023. [PDF]

  2. X. Zhan*, Y. Wang, Antoni B. Chan. Asymptotic Optimality for Active Learning Processes. The 38th Conference on Uncertainty in Artificial Intelligence (UAI). 2022. [PDF]

  3. X. Zhan*, Q. Li, Antoni B. Chan. Multiple-criteria Based Active Learning with Fixed-size Determinantal Point Processes. ICML@Workshop 2021 (SubSetML) [PDF]

  4. X. Zhan*, H. Liu, Q. Li, Antoni B. Chan. A Comparative Survey: Benchmarking for Pool-based Active Learning. IJCAI (Survey Track) 2021 [PDF]

  5. X. Zhan, Y. Wang, Y. Rao*, Q. Li. Learning from Multi-annotator Data: A Noise-aware Classification Framework. ACM Transactions on Information Systems (TOIS), 2019, 37(2): 26. [PDF]

  6. X. Zhan, Y. Wang, Y. Rao*, Q. Li, et al. A network framework for noisy label aggregation in social media. Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (ACL Volume 2). 2017. [PDF]

  7. Y. Wang, Y. Rao, X. Zhan et al. Sentiment and emotion classification over noisy labels. Knowledge-Based Systems, 2016, 111: 207-216. [PDF]

Pre-print papers

  1. X. Zhan*, Q. Wang, K. Huang, H. Xiong, D. Dou, Antoni B. Chan. A Comparative Survey of Deep Active Learning. [PDF]

Note: * indicates the corresponding author.

Full list of publications in Google Scholar.

Open-source softwares

  1. Deep Active Learning plus toolkit. [SOURCE]

Academic service


  • Machine Learning (journal)

  • IEEE Transactions on Emerging Topics in Computational Intelligence (journal)

  • Transactions on Machine Learning Research (journal)

  • NeurIPS 2021, 2022, 2023 (conference)

  • NeurIPS 2023 Track Datasets and Benchmarks 2022, 2023 (conference)

  • ICML 2021, 2022, 2023, 2024 (conference)

  • ICLR 2021, 2022, 2023, 2024 (conference)

  • AISTATS 2022, 2023, 2024 (conference)

  • CVPR 2023, 2024 (conference)

  • UAI 2023 (conference)

  • ICCV 2023 (conference)

  • ECCV 2024 (conference)

PC (Program Committee) member

  • WSDM 2024 (conference)

  • UAI 2024 (conference)


  1. Visiting Scholar, Tsinghua University, department of Computer Science and Technology, Knowledge Engineering Group (KEG lab, lead by Prof. Jie Tang). (Sep. 2020 - Jun. 2021)

  2. Research Intern, Baidu Research, Baidu Inc., Big Data Lab. (Jul. 2021 - Mar. 2023)

  3. Research Assistant, City University of Hong Kong, department of Computer Science. (Sep. 2022 - Jun. 2023)

  4. Teaching Assistant at Sun Yat-sen University. Digital System Design (for BSc) (Sep. 2015 - Jan. 2016). Operating System (for BSc) (Feb. 2016 - Jun. 2016). Principle of Computer Organization (for BSc) (Feb. 2016 - Jun. 2016). Digital Signal Processing (for BSc) (Feb. 2016 - Jun. 2016). Artificial Intelligence (for BSc) (Sep. 2016 - Jan. 2017).

  5. Teaching Assistant at City Univeristy of Hong Kong. CS1102 Introduction to Comp Studies (for BSc) (Sep. 2017 - Dec. 2017 & Jan. 2018 - Jun. 2018). CS4487 Machine Learning (for BSc) (Sep. 2018 - Dec. 2018). CS6487 Topics in Machine Learning (for MSc) (Jan. 2019 - Jun. 2019). CS5487 Machine Learning (for MSc) (Sep. 2019 - Dec. 2019). CS5489 Machine Learning: Algorit&Apns (for MSc) (Jan. 2020 - Jun. 2020).