Welcome!

I am Raymond A. Yeh, a Research Assistant Professor at Toyota Technological Institute at Chicago (TTIC). I will be joining the Computer Science Department at Purdue University as a tenure-track Assistant Professor in Fall 2022!

I am interested in research relating to machine learning and computer vision. My research focuses on developing algorithms to learn effective and explainable models ranging across several domains including audio, vision, language, and multi-agent systems.

I completed my Ph.D. in Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign (UIUC) advised by Prof. Alexander Schwing, Prof. Minh Do, and Prof. Mark Hasegawa-Johnson. I received my M.S. and B.S. degree in Electrical Engineering from UIUC as well.

Raymond A. Yeh
Email: yehr at ttic dot edu

           

Current and Past Affiliations


Fall 2022-
2021-2022
2014-2021
Summer '19, '18
Summer '17, '16, '15
Summer '14, '13



Publications

Cooperative Exploration for Multi-Agent Deep Reinforcement Learning

Iou-Jen Liu, Unnat Jain, Raymond A. Yeh, Alexander G. Schwing
International Conference on Machine Learning (ICML), 2021
Long Talk
PDF Project Code


SAIL-VOS 3D: A Synthetic Dataset and Baselines for Object Detection and 3D Mesh Reconstruction from Video Data

Yuan-Ting Hu, Jiahong Wang, Raymond A. Yeh, Alexander G. Schwing
Computer Vision and Pattern Recognition (CVPR), 2021
Oral Presentation
PDF Project


Not All Unlabeled Data are Equal: Learning to Weight Data in Semi-supervised Learning

Zhongzheng Ren*, Raymond A. Yeh*, Alexander G. Schwing
Neural Information Processing Systems (NeurIPS), 2020
PDF Project Code


High-Throughput Synchronous Deep Reinforcement Learning

Iou-Jen Liu, Raymond A. Yeh, Alexander G. Schwing
Neural Information Processing Systems (NeurIPS), 2020
PDF Project Code


Chirality Nets for Human Pose Regression

Raymond A. Yeh*, Yuan-Ting Hu*, Alexander G. Schwing
Neural Information Processing Systems (NeurIPS), 2019
Also presented at Sets & Paritions Workshop

Contributed Talk
PDF Project Code


Learning Motion in Feature Space: Locally-Consistent Deformable Convolution Networks for Fine-Grained Action Detection

Khoi-Nguyen C. Mac, Dhiraj Joshi, Raymond A. Yeh, Jinjun Xiong, Rogerio S. Feris, Minh N. Do
International Conference on Computer Vision (ICCV), 2019
Oral Presentation
PDF Project Code


Diverse Generation for Multi-agent Sports Games

Raymond A. Yeh, Alexander G. Schwing, Jonathan Huang, Kevin Murphy
Computer Vision and Pattern Recognition (CVPR), 2019
Oral Presentation
PDF Project


Unsupervised Textual Grounding: Linking Words to Image Concepts

Raymond A. Yeh, Minh N. Do, Alexander G. Schwing
Computer Vision and Pattern Recognition (CVPR), 2018
Spotlight Presentation
PDF Project


Interpretable and Globally Optimal Prediction for Textual Grounding using Image Concepts

Raymond A. Yeh, Jinjun Xiong, Wen-mei W. Hwu, Minh N. Do, Alexander G. Schwing
Neural Information Processing Systems (NeurIPS), 2017
Oral Presentation
PDF Project


Video Frame Synthesis using Deep Voxel Flow

Ziwei Liu, Raymond A. Yeh, Xiaoou Tang, Yiming Liu, Aseem Agarwala
International Conference on Computer Vision (ICCV), 2017
Oral Presentation
PDF Project Code


Semantic Image Inpainting with Deep Generative Models

Raymond A. Yeh*, Chen Chen*, Teck Yian Lim, Alexander G. Schwing, Mark Hasegawa-Johnson, Minh N. Do
Computer Vision and Pattern Recognition (CVPR), 2017
PDF Project Code


Semantic Tracklets: An Object-Centric Representation for Visual Multi-Agent Reinforcement Learning

Iou-Jen Liu*, Zhongzheng Ren*, Raymond A. Yeh*, Alexander G. Schwing
International Conference on Intelligent Robots and Systems (IROS), 2021
Also presented at Reinforcement Learning for Real Life Workshop at ICML, 2021

PDF Project


Cooperative Exploration for Multi-Agent Deep Reinforcement Learning

Iou-Jen Liu, Unnat Jain, Raymond A. Yeh, Alexander G. Schwing
International Conference on Machine Learning (ICML), 2021
Long Talk
PDF Project Code


SAIL-VOS 3D: A Synthetic Dataset and Baselines for Object Detection and 3D Mesh Reconstruction from Video Data

Yuan-Ting Hu, Jiahong Wang, Raymond A. Yeh, Alexander G. Schwing
Computer Vision and Pattern Recognition (CVPR), 2021
Oral Presentation
PDF Project


MULTI-DECODER DPRNN: Source Separation for Variable Number of Speakers

Junzhe Zhu, Raymond A. Yeh, Mark Hasegawa-Johnson
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021
PDF


Not All Unlabeled Data are Equal: Learning to Weight Data in Semi-supervised Learning

Zhongzheng Ren*, Raymond A. Yeh*, Alexander G. Schwing
Neural Information Processing Systems (NeurIPS), 2020
PDF Project Code


High-Throughput Synchronous Deep Reinforcement Learning

Iou-Jen Liu, Raymond A. Yeh, Alexander G. Schwing
Neural Information Processing Systems (NeurIPS), 2020
PDF Project Code


Chirality Nets for Human Pose Regression

Raymond A. Yeh*, Yuan-Ting Hu*, Alexander G. Schwing
Neural Information Processing Systems (NeurIPS), 2019
Also presented at Sets & Paritions Workshop

Contributed Talk
PDF Project Code


PIC: Permutation Invariant Critic for Multi-Agent Deep Reinforcement Learning

Iou-Jen Liu*, Raymond A. Yeh*, Alexander G. Schwing
Conference on Robot Learning (CoRL), 2019
PDF Project Code


Learning Motion in Feature Space: Locally-Consistent Deformable Convolution Networks for Fine-Grained Action Detection

Khoi-Nguyen C. Mac, Dhiraj Joshi, Raymond A. Yeh, Jinjun Xiong, Rogerio S. Feris, Minh N. Do
International Conference on Computer Vision (ICCV), 2019
Oral Presentation
PDF Project Code


Diverse Generation for Multi-agent Sports Games

Raymond A. Yeh, Alexander G. Schwing, Jonathan Huang, Kevin Murphy
Computer Vision and Pattern Recognition (CVPR), 2019
Oral Presentation
PDF Project


Unsupervised Textual Grounding: Linking Words to Image Concepts

Raymond A. Yeh, Minh N. Do, Alexander G. Schwing
Computer Vision and Pattern Recognition (CVPR), 2018
Spotlight Presentation
PDF Project


Time-Frequency Networks for Audio Super-Resolution

Teck Yian Lim*, Raymond A. Yeh*, Yijia Xu, Minh N. Do, Mark Hasegawa-Johnson
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018
PDF Project Code


Image Restoration with Deep Generative Models

Raymond A. Yeh*, Teck Yian Lim*, Chen Chen, Alexander G. Schwing, Mark Hasegawa-Johnson, Minh N. Do
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018
PDF Project Code


Interpretable and Globally Optimal Prediction for Textual Grounding using Image Concepts

Raymond A. Yeh, Jinjun Xiong, Wen-mei W. Hwu, Minh N. Do, Alexander G. Schwing
Neural Information Processing Systems (NeurIPS), 2017
Oral Presentation
PDF Project


Video Frame Synthesis using Deep Voxel Flow

Ziwei Liu, Raymond A. Yeh, Xiaoou Tang, Yiming Liu, Aseem Agarwala
International Conference on Computer Vision (ICCV), 2017
Oral Presentation
PDF Project Code


Semantic Image Inpainting with Deep Generative Models

Raymond A. Yeh*, Chen Chen*, Teck Yian Lim, Alexander G. Schwing, Mark Hasegawa-Johnson, Minh N. Do
Computer Vision and Pattern Recognition (CVPR), 2017
PDF Project Code


Semantic Facial Expression Editing using Autoencoded Flow

Raymond A. Yeh, Ziwei Liu, Dan B Goldman, Aseem Agarwala
arXiv preprint, 2016
PDF Project


Stable and Symmetric Filter Convolutional Neural Network

Raymond Yeh, Mark Hasegawa-Johnson, Minh N. Do
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2016
PDF Project




Teaching

University of Illinois at Urbana-Champaign (Teaching Assistant)

  • Fall 2019: Pattern Recognition
  • Spring 2018: Machine Learning
  • Fall 2017: Pattern Recognition
  • Fall 2016: Pattern Recognition
  • Fall 2015: Embedded DSP Laboratory
  • Spring 2015: Embedded DSP Laboratory
  • Fall 2014: Embedded DSP Laboratory