shuhong (shu) chen
陈舒鸿
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email: shuhong[a]terpmail.umd.edu
web: shuhongchen.github.io
github: ShuhongChen
myanimelist: shuchen
linkedin: link
cv: latest
academic
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. |
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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. |
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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. |
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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]archinc.jp. |
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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. |
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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. |
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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.
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PhD in CS Class of 2024 (expected) Advisor: Prof. Matthias Zwicker |
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BS in CS and Math, minor in Econ Class of 2019, Honors College Inaugural Class Summa cum laude |
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
2015 Rutgers Trustee Scholarship, Rutgers University
2017 Grant for Conference Funding, Rutgers ECE
2017 Best Use of Machine Learning (4th), HackRU F2017