Chenyan Wu

I am currently a Research Scientist in the perception team at TuSimple, focusing on object detection algorithms for self-driving trucks. In Oct. 2023, I defended my Ph.D. thesis in the College of Information Sciences & Technology at The Pennsylvania State University, advised by Prof. James Z. Wang. Before joining Penn State, I received my B.E. in Electronic Information Engineering from the School of the Gifted Young, University of Science and Technology of China. I have also had a wonderful time as an intern at Amazon Astro, Amazon Alexa, Microsoft Research Asia, and SenseTime Research.

Email / CV / Google Scholar / LinkedIn / Github

Research

I'm interested in computer vision and affective computing. During my Ph.D., much of my research is about modeling and understanding human behaviors from images or videos, such as human bodily expressed emotion understanding and 2D/3D human pose estimation. Representative papers are highlighted.

	Unlocking the Emotional World of Visual Media: An Overview of the Science, Research, and Impact of Understanding Emotion James Z. Wang, Sicheng Zhao, Chenyan Wu, Reginald B. Adams, Michelle G. Newman, Tal Shafir, Rachelle Tsachor Proceedings of the IEEE, 2023 (sole student author) paper / arXiv This 51-page article provides a comprehensive overview of the field of emotion analysis in visual media and discusses the latest research, challenges, and potential impact of artificial emotional intelligence on society.
	Bodily Expressed Emotion Understanding Through Integrating Laban Movement Analysis Chenyan Wu, Dolzodmaa Davaasuren, Tal Shafir, Rachelle Tsachor, James Z. Wang Patterns, Cell Press, 2023 (featured cover article) paper / arXiv / data / code
	Learning to Adapt to Online Streams with Distribution Shifts Chenyan Wu, Yimu Pan, Yandong Li, James Z. Wang arXiv, 2023 (under peer review) arXiv
	MUG: Multi-human Graph Network for 3D Mesh Reconstruction from 2D Pose Chenyan Wu, Yandong Li, Xianfeng Tang, James Z. Wang arXiv, 2022 (under peer review) arXiv
	The Ninth Visual Object Tracking VOT2021 Challenge Results Matej Kristan, Jiří Matas, ..., Chenyan Wu, et al. IEEE/CVF International Conference on Computer Vision Workshop (ICCVW), 2021 paper
	MEBOW: Monocular Estimation of Body Orientation In the Wild Chenyan Wu, Yukun Chen, Jiajia Luo, Che-Chun Su, Anuja Dawane, Bikramjot Hanzra, Zhuo Deng, Bilan Liu, James Z. Wang, Cheng-hao Kuo IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020 paper / arXiv / data / code
	AI-PLAX: AI-based Placental Assessment and Examination Using Photos Yukun Chen, Zhuomin Zhang, Chenyan Wu, Dolzodmaa Davaasuren, Jeffery Goldstein, Alison Gernand, James Z. Wang Computerized Medical Imaging and Graphics (CMIG), 2020 paper
	Multi-region Saliency-aware Learning for Cross-domain Placenta Image Segmentation Zhuomin Zhang, Dolzodmaa Davaasuren, Chenyan Wu, Jeffery Goldstein, Alison Gernand, James Z. Wang Pattern Recognition Letters (PRL), 2020 paper
	PlacentaNet: Automatic Morphological Characterization of Placenta Photos with Deep Learning Yukun Chen, Chenyan Wu, Zhuomin Zhang, Jeffery Goldstein, Alison Gernand, James Z. Wang Medical Image Computing and Computer Assisted Intervention (MICCAI), 2019 paper

Education
08/2018 - Present	Ph.D., The Pennsylvania State University
08/2014 - 06/2018	Bachelor, University of Science and Technology of China

Experiences
10/2023 - Present	Research Scientist in TuSimple
03/2021 - 09/2021	Research intern in Microsoft Research Asia
06/2020 - 09/2020	Applied scientist intern in Amazon Alexa
05/2019 - 08/2019	Applied scientist intern in Amazon Lab126 (the Astro team)
03/2018 - 07/2018	Research intern in SenseTime Research
07/2017 - 09/2017	Visiting scholar in University of Technology, Sydney

Service
Conference Reviewer	WACV 2021, ECCV 2022, AAAI 2023, CVPR 2023, AAAI 2024
Journal Reviewer	IEEE Transactions on Cybernetics

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Research

Education

Experiences

Service