experience

	Founder, Dondon Technologies Inc. Website: dondontech.com 2024 April – present Our goal at Dondon is to assist traditional 2D animators working in the Japanese anime pipeline. Many labor-intensive tasks like douga and shiage (CUIB/DIP) can be accelerated with the help of new vision/graphics techniques.
	PhD Graduate Research Assistant, UMD CS Advisor: Prof. Matthias Zwicker 2020 June – 2024 June 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.
	Research Scientist Intern, Meta Mentors: Amit Kumar, Xiaoyu Xiang, Sreyas Mohan, Rakesh Ranjan 2023 August – 2024 March Menlo Park, California, USA Worked on diffusion models applied to non-photorealistic 3D modeling topics.
	Research Collaborator, OLM Digital Inc. 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.
	Visiting Researcher, Arch Inc. 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.
	Vision Research Intern, ByteDance/TikTok 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.
	Summer Intern, MIT Lincoln Laboratory 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.
	Undergrad Research Assistant, Rutgers ECE 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.

education

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

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

teaching + mentorship

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

BS students advised:
2022: Andy Qu
2020: Nikhil Pateel

classes taught:
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

invited talks

2023 July, University of Tokyo, Takeo Igarashi Lab, “ML for Anime: Illustration, Animation, and 3D Models”
2023 March, Chimera Entertainment, “What are Generative Image Models?”

awards

2024 Pitch Dingman Semi-finalist, UMD Smith School of Business
2023 Startup Fellow, UMD Startup Shell
2021 Honorable Mention, NSF GRFP (graduate)
2019 Honorable Mention, NSF GRFP (undergrad)
2019 Dean’s Fellowship, UMD Graduate School of CS
2019 Startup Allocation Proposal, XSEDE PSC Bridges
2018 Alan Marc Schreiber Memorial Scholarship, Rutgers SAS Excellence Award in Math
2017 Grant for Conference Funding, Aresty Research Center
2017 Grant for Conference Funding, Rutgers ECE
2015 Rutgers Trustee Scholarship, Rutgers University
2018 Top 6 Shark-Tank Finalist, MIT Intern Innovative Idea Challenge
2017 Best Healthcare Hack, HackRU F2017
2017 Best Use of Machine Learning (4th), HackRU F2017
2021: nominated for Sigma Xi Associate Membership
2018: member of Phi Beta Kappa Honors Society
2017: member of IEEE