
Hung-Yueh Chiang
江泓樂
[Curriculum Vitae] [Résumé]
Ph.D. Candidate
Affiliations: EnyAC
Department of Electrical and Computer Engineering
The University of Texas at Austin
About me
Hung-Yueh Chiang is a fourth-year Ph.D. student in the Energy-Aware Computing Group (EnyAC) at The University of Texas at Austin (UT), advised by Prof. Diana Marculescu. Before joining EnyAC, he worked as a deep learning engineer at XYZ Robotics, a startup in Shanghai. From 2016 to 2018, he collaborated with Prof. Winston Hsu on 3D point cloud learning and earned his M.S. degree from National Taiwan University (NTU), Taipei, Taiwan. He completed his B.S. degree at National Yang Ming Chiao Tung University (NYCU, formerly National Chiao Tung University) in Hsinchu, Taiwan, in 2015. During his final semester at NYCU, he participated in an exchange program at ETH Zürich.
Research interests: efficient fine-tuning, model quantization, computer vision
News
Mar 21, 2025 | ![]() Topics: Efficient Machine Learning, including optimization techniques for deep learning models, diffusion models, and large language models. |
---|---|
Jan 31, 2025 | ![]() Our paper: Quamba: A Post-Training Quantization Recipe for Selective State Space Models has been accepted to ICLR 2025. |
Oct 17, 2024 | ![]() Our newest paper: Quamba: A Post-Training Quantization Recipe for Selective State Space Models is released on Arxiv. |
May 14, 2024 | ![]() Our paper: Cache and Reuse: Rethinking the Efficiency of On-device Transfer Learning has been accepted to CVPR 2024 Efficient Deep Learning for Computer Vision (ECV) Workshop. |
Mar 5, 2024 | ![]() Our paper: SCAN-Edge: Finding MobileNet-speed Hybrid Networks for Commodity Edge Devices has been accepted to ICLR 2024 PML4LRS Workshop. |
Education

(National Chiao Tung University)
Sep. 2011 - Sep. 2015
B.S. in computer science
Work experience

May 2023 - Aug. 2023
Neural architecture search for object detection

May 2022 - Nov. 2022
Image synthesis and generation for shoe virtual try-on

Jun. 2019 - May 2021
Image segmentation and object detection for logistics robots
Selected publications
* Equal contribution
- Efficient Low-rank Backpropagation for Vision Transformer AdaptationIn Advances in Neural Information Processing Systems (NeurIPS) 2023
Academic service
Conference Reviewer: NeurIPS 2024, ICLR 2025, ICML 2025, NeurIPS 2025Open-source contributions
- HolisticTraceAnalysis -- A PyTorch profiling tool by Facebook Research
- fast-hadamard-transform -- An efficient Hadamard transform implementation from Dao-AILab (Tri Dao)
Pro bono office hours
I've committed to set aside 1 hour every week to provide mentorship and/or guidance for whoever is in need. If you find my research, work, oversea and/or life experience useful, welcoming to fill in this form. For feedback, questions, and/or random messages, please use this link.Miscellaneous
- I like playing table tennis, piano, and taking pictures of new visiting places (Instagram).
- I served in marine corp from 2015-2016 as the mandatory military service in Taiwan.
- I was diagnosed with thyroid cancer in 2016 and had a total thyroidectomy. Fortunately, I am fine now.