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 :briefcase: I am open to research scientist internship positions for 2025 spring/summer/fall.
Topics: Efficient Machine Learning, including optimization techniques for deep learning models, diffusion models, and large language models.
Oct 17, 2024 :page_with_curl: Paper Released
Our newest paper: Quamba: A Post-Training Quantization Recipe for Selective State Space Models is released on Arxiv.
May 14, 2024 :tada: Paper Accepted
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 :tada: Paper Accepted
Our paper: SCAN-Edge: Finding MobileNet-speed Hybrid Networks for Commodity Edge Devices has been accepted in ICLR 2024 PML4LRS Workshop.
Feb 8, 2024 :tada: Fellowship Finallist
Advance to the Finals of the 2024 Qualcomm Innovation Fellowship (North America).

Education


The University of Texas at Austin
Sep. 2021 - Current
Ph.D. in electrical and computer engineering

National Taiwan University
Sep. 2016 - Sep. 2018
M.S. in computer science

ETH Zürich
Jan. 2015 - Sep. 2015
Exchange student

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


Work experience


Rivian - Software Engineering Intern (Deep Learning)
May 2023 - Aug. 2023
Neural architecture search for object detection
Amazon - Research Scientist Intern
May 2022 - Nov. 2022
Image synthesis and generation for shoe virtual try-on
XYZ Robotics - Deep Learning Engineer
Jun. 2019 - May 2021
Image segmentation and object detection for logistics robots

Selected publications

* Equal contribution

  1. Quamba: A Post-Training Quantization Recipe for Selective State Space Models
    arXiv preprint arXiv:2410.13229 2024
  2. Efficient Low-rank Backpropagation for Vision Transformer Adaptation
    Yuedong YangHung-Yueh Chiang, Guihong Li, Diana Marculescu, and Radu Marculescu
    In Advances in Neural Information Processing Systems (NeurIPS) 2023
  3. Conference Oral paper AAAI
    MobileTL: On-device Transfer Learning with Inverted Residual Blocks
    Hung-Yueh ChiangNatalia FrumkinFeng Liang, and Diana Marculescu
    In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI) 2023
  4. Learning from 2D: Pixel-to-Point Knowledge Transfer for 3D Pretraining
    Yueh-Cheng Liu, Yu-Kai Huang, Hung-Yueh Chiang, Hung-Ting Su, Zhe-Yu Liu, and 3 more authors
    arXiv preprint arXiv:2104.04687 2021
  5. A unified point-based framework for 3d segmentation
    Hung-Yueh Chiang, Yen-Liang Lin, Yueh-Cheng Liu, and Winston H Hsu
    In International Conference on 3D Vision (3DV) 2019

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.

CV of failures

Life can be tough. We fail all the time, but failures pave the way to success. I am working on my CV of failures. Stay tuned...

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.