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Short Bio
I am an Assistant Professor in the Department of Computer Science at Purdue University. Prior to joining Purdue, I was a Research Assistant Professor at Toyota Technological Institute at Chicago (TTIC).
I completed my Ph.D. and M.S. in Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign (UIUC) advised by Prof. Alexander Schwing and Prof. Minh Do. I received my B.S. degree in Electrical Engineering from UIUC working with Prof. Mark Hasegawa-Johnson.
I am interested in research relating to machine learning and computer vision. My research focuses on developing algorithms to learn and design effective models across several domains including audio, vision, language, and multi-agent systems.
To prospective students. We are looking for highly motivated and talented students! (Fall 2026)
Thank you for your interest in joining! Due to the high volume of emails, I am unable to respond to everyone.
To get a sense of what we work on, read at least three papers for which I am the first or last author then follow the instructions below.
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To prospective Ph.D. students NOT at Purdue:
- Apply to Purdue Computer Science Graduate Program and list my name in the application.
- There is no need to email me unless you have specific topics/interests that fits my group. Keep it brief. Finally, list which of the three papers you have read.
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To prospective Ph.D. students at Purdue:
- Email me your CV, transcript, research experience, and a topic of interest. Explain why your background is suitable and how it fits in the group. Keep it brief. Finally, list which of the three papers you have read.
- Make sure to have communicated with the current/initial adivsor that you intended to work with me and include the advisor's name in the email.
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To master/undergraduate students at Purdue:
- Email me your CV, transcript, time commitment, e.g., 15 hours per week for six months, and how you plan to be involved. Finally, list which of the three papers you have read.
Current and Past Affiliations
News
| Nov, 2025 | Two papers accepted to AAAI 2026, one paper accepted to NeurIPS 2025. |
| Jun, 2025 | One paper accepted to ICML 2025 as oral presentation and four papers accepted to ICCV 2025. |
| Jun, 2025 | We are grateful for the support from Google with a Google Research Scholar 2025. |
| Feb, 2025 | One paper accepted to ICLR, CVPR 2025 and Area Chair for NeurIPS 2025. |
| Dec, 2024 | One paper accepted to AAAI 2025 and Area Chair for CVPR, ICML 2025. |
| Sep, 2024 | We are grateful for the support from National Science Foundation (NSF IIS RI) of our research. |
| Sep, 2024 | Two papers accepted to NeurIPS 2024 and Area Chair for ICLR 2025. |
| Jul, 2024 | Four papers accepted to ECCV 2024 and Area Chair for NeurIPS, ACML 2024. |
| Feb, 2024 | Two papers accepted to CVPR 2024. |
| Sep, 2023 | Paper accepted to NeurIPS 2023 and Area Chair for ICLR 2024. |
| Aug, 2023 | Area Chair for CVPR 2024 and Associate Editor for IET Computer Vision. |
| Apr, 2023 | Paper accepted to ICML 2023. |
| Mar, 2023 | Two papers accepted to CVPR 2023. |
| Mar, 2023 | Area Chair for NeurIPS 2023. |
| Jan, 2023 | SPC for IJCAI 2023. |
| Oct, 2022 | Area Chair for CVPR 2023. |
| Sep, 2022 | Papers accepted at NeurIPS 2022, BMVC 2022, and ACCV 2022. |
| Aug, 2022 | Joined Purdue University in the CS department! |
Publications
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
Auto-Vocabulary 3D Object Detection
Haomeng Zhang,
Kuan-Chuan Peng,
Suhas Lohit,
Raymond A. Yeh
arXiv preprint, 2025
PDF
4D-RGPT: Toward Region-level 4D Understanding via Perceptual Distillation
Chiao-An Yang,
Ryo Hachiuma,
Sifei Liu,
Subhashree Radhakrishnan,
Raymond A. Yeh,
Yu-Chiang Frank Wang,
Min-Hung Chen
arXiv preprint, 2025
PDF
Tuning-Free Amodal Segmentation via the Occlusion-Free Bias of Inpainting Models
Jae Joong Lee,
Bedrich Benes,
Raymond A. Yeh
The AAAI Conference on Artificial Intelligence (AAAI), 2026
PDF
Building Instance Segmentation for Dense Urban Settlements
Adnan Firoze,
Raymond A. Yeh,
Daniel Aliaga
The AAAI Conference on Artificial Intelligence (AAAI), 2026
Toward Long-Tailed Online Anomaly Detection through Class-Agnostic Concepts
Chiao-An Yang,
Kuan-Chuan Peng,
Raymond A. Yeh
International Conference on Computer Vision (ICCV), 2025
PDF
DarkDiff: Advancing Low-Light Raw Enhancement by Retasking Diffusion Models for Camera ISP
Amber Yijia Zheng,
Yu Zhang,
Jun Hu,
Raymond A. Yeh,
Chen Chen
arXiv preprint, 2025
PDF
Pretraining Codomain Attention Neural Operators for Solving Multiphysics PDEs
Md Ashiqur Rahman,
Robert J. George,
Mogab Elleithy,
Daniel Leibovici,
Zongyi Li,
Boris Bonev,
Colin White,
Julius Berner,
Raymond A. Yeh,
Jean Kossaifi,
Kamyar Azizzadenesheli,
Anima Anandkumar
Neural Information Processing Systems (NeurIPS), 2024
PDF
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
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
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
Teaching
Purdue University
- Fall 2025: Computer Vision with Deep Learning
- Spring 2025: Introduction to Artificial Intelligence
- Fall 2024: Computer Vision with Deep Learning
- Spring 2024: Foundations Of Deep Learning
- Fall 2023: Introduction to Artificial Intelligence
- Spring 2023: Introduction to Artificial Intelligence
- Fall 2022: Topics in Machine Perception
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
Services
Area Chair: NeurIPS, CVPR, ICLR, ICML, IJCAI, ACMLAssociate Editor: IET Computer Vision
Conference Reviewer: CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, AISTATS
Journal Reviewer: TPAMI, IJCV, SIGGRAPH, TMLR, Pattern Recognit.
Awards and Honors
- Google Research Scholar (Machine Perception) | Google, 2025
- Dissertation Completion Fellowship (Declined) | UIUC, 2020
- Robert T. Chien Memorial Award | UIUC, 2020
- Mavis Future Faculty Fellowship | UIUC, 2019
- Google PhD Fellowship (Machine Perception) | Google, 2018
- James M. Henderson Fellowship | UIUC, 2015
- Henry Ford II Scholar Award | UIUC, 2014
- Henry O. Koehler Merit Scholarship | UIUC, 2014
- Bronze Tablet Award | UIUC, 2014
- Teachers Ranked Excellent | UIUC, 2014
- Graduation Highest Honors | UIUC, 2014