Me
Yen-Yu Chang
CS PhD Student
@Cornell Tech, Cornell University
yenyuchang [at] cs.cornell.edu
Another Me
I love sports, especially basketball and table tennis.

Biography

I am a second year PhD student at Cornell University working with Prof. Noah Snavely. I am generally interested in computer vision, graphics, and machine learning. My recent research focuses on 3D reconstruction, motion analysis, and view synthesis.

I received my Bachelor's degree in Electrical Engineering from National Taiwan University (NTU) in 2018, and my Master's in Electrical Engineering from Stanford University in 2021. I have had the privilege to work with Prof. Li Fei-Fei, Prof. Jiajun Wu, Prof. Leonidas Guibas, Prof. Jure Leskovec, and Prof. Pan Li at Stanford. If you would like to learn more about me, please see my [ Résumé ] or contact me at yenyuchang [at] cs.cornell.edu.

Interests

  • Machine Learning
  • Computer Vision
  • Computer Graphics

Education

National Taiwan University (NTU)
B.S. in Electrical Engineering, 2018
Stanford University
M.S. in Electrical Engineering, 2021

Timeline & Experiences

2022 Aug. - present
CS Phd student @ Cornell Tech, Cornell University
Machine Learning, Computer Vision, and Graphics
2021 Dec. - 2022 Jun.
Research Engineer @ Horizon Robotics
Representation Learning, Object-oriented Learning, & Reinforcement Learning
2021 Jul. - 2021 Nov.
Research Assistant @ Stanford Vision and Learning Lab (SVL)
Computer Vision, Neural Rendering, and Multimodal Learning
2019 Sep. - 2021 Jun.
EE master student @ Stanford University
Research Assistant @ Stanford Network Analysis Project (SNAP)
Deep Learning, Graph Mining, Anomaly Detection
Research Assistant @ Stanford Vision & Learning Lab (SVL)
Computer Vision, Neural Rendering, Multimodal Learning
Graduate Researcher @ Stanford Geometric Computation Group
Computer Vision, 3D learning, CAD Model Analysis
Supervisor: Prof. Leonidas Guibas
2019 Jul. - 2019 Sep.
Summer Research Intern @ Stanford Network Analysis Project (SNAP)
2014 - 2018
Undergraduate student & researcher @ NTU
Electrical Engineering department
1996
He was born.

Selected Publications

Tracking Everything Everywhere All at Once
ICCV 2023 (Oral) Paris, France
Learning Object-centric Neural Scattering Functions for Free-viewpoint Relighting and Scene Composition
TMLR 2023
Point2Cyl: Reverse Engineering 3D Objects from Point Clouds to Extrusion Cylinders
CVPR 2022 New Orleans, LA
ObjectFolder 2.0: A Multisensory Object Dataset for Sim2Real Transfer
CVPR 2022 New Orleans, LA
ObjectFolder: A Dataset of Objects with Implicit Visual, Auditory, and Tactile Representations
CoRL 2021 (Virtual)
Inductive Representation Learning in Temporal Networks via Causal Anonymous Walks
ICLR 2021 (Virtual)
F-FADE: Frequency Factorization for Anomaly Detection in Edge Streams
WSDM 2021 (Virtual)
A Regulation Enforcement Solution for Multi-agent Reinforcement Learning
AAMAS 2019 Montreal, QC
Designing Non-greedy Reinforcement Learning Agents with Diminishing Reward Shaping
AAAI/ACM conference on AI, Ethics, Society 2018 (Oral) New Orleans, LA
A Memory-Network Based Solution for Multivariate Time-Series Forecasting
preprint
ANS: Adaptive Network Scaling for Deep Rectifier Reinforcement Learning Models
preprint
Heterogeneous Star Celebrity Games
preprint
[ pdf ]

Honors & Awards

    International

  • Ranked 19th (out of 4180) / KDD CUP - Main Track / 2018
  • Ranked 4th (out of 4180) / KDD CUP - Specialized Prize for long term prediction / 2018

    Domestic

  • Dean's List / National Taiwan University / 2016
  • Finalist (Top 30) / International Physics Olympiad Domestic Final / 2013
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