shuhong (shu) chen

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research publications
top anime

email: shuhong[a]
github: ShuhongChen
myanimelist: shuchen
linkedin: link
cv: latest

google scholar: TcGJKGwAAAAJ
orcid: 0000-0001-7317-0068
erdős number: ≤4

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Advisor: Prof. Matthias Zwicker
2020 June – present
College Park, Maryland, USA

I am exploring novel ways of creating and manipulating illustrations and animations, by leveraging both data-driven vision techniques and 3D graphics representations. I am also interested in new rendering methods using deep learning.

Mentors: Amit Kumar, Xiaoyu Xiang, Sreyas Mohan, Rakesh Ranjan
2023 August – 2023 December
Menlo Park, California, USA

Working on diffusion models applied to non-photorealistic 3D modeling topics.

Supervisors: Maejima Akinobu, Marc Salvati, Tatsuo Yotsukura
2023 July
Setagaya, Tokyo, Japan

Research & Development Division, worked on automatic cleanup of genga to douga. Collaborated in-person in Setagaya, Tokyo to learn more about the anime production process, and to train deep models on real production data.

Affiliate contact: Jun Kato
2023 January
Yoyogi Shibuya, Tokyo, Japan (remote)

Thanks to colleagues at Arch Inc. for setting me up as a visiting researcher, to help foster collaboration with anime industry professionals in Japan. Please direct Arch-related inquiries to shuhong[a]

Mentors: Yiheng Zhu, Heng Wang, Yichun Shi, Xiao Yang
2022 May – 2022 November
Mountain View, California, USA (remote)

Intelligent Creation & Computer Vision - Generation Team, worked on generative modeling of 3D VR character assets; specifically, stylized single-view 3D reconstruction from illustrated character portraits.

Advisor: Dr. Michael Chan
2018 June – 2018 August
Lexington, Massachusetts, USA

I looked at automatically discovering recurrent neural network architectures for video action recognition. I was also a finalist at the lab’s Intern Innovative Idea Challenge.

Advisor: Prof. Ivan Marsic
2015 October – 2019 May
New Brunswick, New Jersey, USA

I worked with grad students on healthcare informatics for trauma resuscitations; topics included process mining, workflow analysis, data visualization, NLP, and CV.


Special thanks to Prof. Matthew Stone, Prof. Iian Smythe, and Prof. Qiang Xu for their invaluable guidance and mentorship.

PhD in CS
Class of 2024 (expected)
Advisor: Prof. Matthias Zwicker
BS in CS and Math, minor in Econ
Class of 2019, Honors College Inaugural Class
Summa cum laude

invited talks

teaching + mentorship

2022: Eric Changzhi Li, Srinidhi Hegde
2021: Janus Thor Kristjansson, Jiaxuan Mary Wu

2022: Andy Qu
2020: Nikhil Pateel

M2021 UMD AI4ALL Project Lead: Making Art with Neural Networks
S2020 TA CMSC417: Computer Networks, Prof. Nirupam Roy, UMD
F2019 TA CMSC132: OOP II, Prof. Nelson Pauda-Perez and Pedram Sadeghian, UMD
2016-2019 Lecturer, ML/AI Division Director, Rutgers IEEE E-Board
2016 Tutor, Math & Engineering, Rutgers OSS Educational Opportunity Fund
2013-2016 TA Chinese Second Language, Huaxia Morris Chinese Academy