Hung-Yueh Chiang
江泓樂
About me
Hung-Yueh is a Senior Deep Learning Software Engineer on the Inference and Model Optimization team at NVIDIA. Prior to joining NVIDIA, he obtained his Ph.D. degree at The University of Texas at Austin (UT), advised by Prof. Diana Marculescu. He completed his M.S. degree from National Taiwan University (NTU) and a B.S. degree at National Yang Ming Chiao Tung University.
I’m interested in building efficient agentic AI systems for everyone on every device. My research interests include:
- Quantization and compression: Weight and KV-cache compression with new floating types for faster inference
- Efficient agentic system design: Lightweight architectures and scheduling strategies for multi-step reasoning agents
- On-device agentic systems: Deploying capable AI agents on resource-constrained edge devices
News
| Apr 6, 2026 | I will join NVIDIA as a Senior Deep Learning Software Engineer in Inference and Model Optimization. |
|---|---|
| Feb 20, 2026 | I successfully defended my Ph.D. thesis: Model Adaptation and Compression for Edge Intelligence |
| Jan 26, 2026 | Our paper: UniQL: Unified Quantization and Low-rank Compression for Adaptive Edge LLMs has been accepted to ICLR 2026. |
| Dec 11, 2025 | We release an open-sourced profiling tool: ELANA: A Simple Energy and Latency Analyzer for LLMs, please checkout our GitHub and the technical report |
| Dec 3, 2025 | Our newest paper: UniQL: Unified Quantization and Low-rank Compression for Adaptive Edge LLMs is released on Arxiv. |
Work experience
NVIDIA - Senior Deep Learning Software Engineer
Apr. 2026 - Present
Inference and model optimization
Apr. 2026 - Present
Inference and model optimization
Eigen AI - Research Intern
Dec. 2025 - Feb. 2026
NVFP4 quantization and serving for large language models
Dec. 2025 - Feb. 2026
NVFP4 quantization and serving for large language models
Rivian - Software Engineering Intern (Deep Learning)
May 2023 - Aug. 2023
Neural architecture search for object detection
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
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
Jun. 2019 - May 2021
Image segmentation and object detection for logistics robots
Education
The University of Texas at Austin
Sep. 2021 - Feb. 2026
Ph.D. in electrical and computer engineering
Sep. 2021 - Feb. 2026
Ph.D. in electrical and computer engineering
National Yang Ming Chiao Tung University
(National Chiao Tung University)
Sep. 2011 - Sep. 2015
B.S. in computer science
(National Chiao Tung University)
Sep. 2011 - Sep. 2015
B.S. in computer science
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, 2025), ICLR (2025, 2026), ICML (2025, 2026), AAAI 2026Open-source contributions
- HolisticTraceAnalysis -- A PyTorch profiling tool by Facebook Research
- fast-hadamard-transform -- An efficient Hadamard transform implementation from Dao-AILab (Tri Dao)
- Elana -- A Simple Energy & Latency Analyzer for LLMs
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 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.






