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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 Energy-Aware Computing Group (EnyAC) at The University of Texas at Austin (UT) under Prof. Diana Marculescu’s supervision. Before joining EnyAC, Hung-Yueh was a deep learning engineer at XYZ Robotics, a start-up company in Shanghai. From 2016 to 2018, Hung-Yueh worked with Prof. Winston Hsu on 3D point cloud learning and received his M.S. degree from National Taiwan University (NTU), Taipei, Taiwan in 2018. He earned his B.S. degree from National Yang Ming Chiao Tung University (NYCU, formerly National Chiao Tung University), Hsinchu, Taiwan in 2015. In the last semester at NYCU, he had an exchange program to ETH Zürich.
News
Jun 30, 2024 | ![]() Topics: Efficient Machine Learning, including optimization techniques for deep learning models, diffusion models, and large language models. |
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Jan 31, 2025 | ![]() Our paper: Quamba: A Post-Training Quantization Recipe for Selective State Space Models has been accepted in 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 in 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 in ICLR 2024 PML4LRS Workshop. |
Education
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(National Chiao Tung University)
Sep. 2011 - Sep. 2015
B.S. in computer science
Work experience
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May 2023 - Aug. 2023
Neural architecture search for object detection
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May 2022 - Nov. 2022
Image synthesis and generation for shoe virtual try-on
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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
- Conference Oral paper AAAIMobileTL: On-device Transfer Learning with Inverted Residual BlocksIn Proceedings of the AAAI Conference on Artificial Intelligence (AAAI) 2023
Academic service
Conference Reviewer: NeurIPS 2024, ICLR 2025, ICML 2025, NeurIPS 2025Pro 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.