Jun Han

Incoming Assistant Professor
Division of Emerging Interdisciplinary Areas
The Hong Kong University of Science and Technology

Previously, I was an assistant professor at the Chinese Univesity of Hong Kong (Shenzhen). I received Ph.D. in Computer Science and Engineering from the University of Notre Dame, advised by Prof. Chaoli Wang. Before that, I obtained my BS in Software Engineering and MS in Computer Software and Theory. Both are from Xidian University. My research interests lie in the general area of human-computer interaction, scientific visualization, and machine learning.

PhD applicants: I have several openings for PhD positions starting in Fall 2025, as well as research assistant (RA) positions. If you are interested in working with me, please email to junhanvis@outlook.com. The email title should be “School-Name-PhD/RA.” In the email, briefly describe your motivation for wanting to work with me. Additionally, please attach your resume, academic rankings, and research experience (e.g., papers under review or published). Both the email and CV should be in English. If suitable, I will contact you as soon as possible. Reaching out early can help you apply for the Hong Kong government scholarship!

I will read all application emails, but I may not be able to respond to each one. If you don’t receive a response within a month, it may indicate that we are not a good fit.


news

Dec 5, 2023

KD-INR accepted to IEEE TVCG!

Apr 5, 2023

GMT accepted to C&G!

Feb 14, 2023

Invited to Serve on the Program Committee at IEEE VIS 2023!

Jul 29, 2022

CoordNet accepted to IEEE TVCG!

Apr 13, 2022

DL4SciVis accepted to IEEE TVCG!

selected publications

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Jun Han, Hao Zheng, Danny Z. Chen, and Chaoli Wang
IEEE TVCG (IEEE VIS 2021) / Paper

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Hao Zheng, Jun Han, Hongxiao Wang, Lin Yang, Zhuo Zhao, Chaoli Wang, and Danny Z. Chen
MICCAI 2021 / Paper

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Jun Han, Hao Zheng, Yunhao Xing, Danny Z. Chen, and Chaoli Wang
IEEE TVCG (IEEE VIS 2020) / Paper

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Sicong Liu, Zimu Zhou, Junzhao Du, Longfei Shangguan, Jun Han, and Xin Wang
ACM IMWUT (Distinguished Paper Award at ACM UbiComp 2018) / Paper