I am a Computer Science Ph.D. student at the University of Massachusetts (UMass) Amherst, advised by Professor Ramesh K. Sitaraman and Professor Mohammad Hajiesmaili. Before joining UMass, I received a M.S. degree in Computer Science from National Taiwan University (NTU), where I worked with Professor Winston Hsu.
My research sits at the intersection of systems and machine learning, focusing on practical volumetric video streaming systems. In particular, I develop neural-enhanced content-distribution frameworks that capture, compress, deliver, and render 3D visual media. This entails minimizing both the size of the 3D representations and the ML inference latency, all while preserving high visual quality. Currently, I am exploring 1) a novel memory-efficient 3D scene representation that can be compressed through 2D video codec, and 2) efficient serving of text-to-image diffusion models by enabling dynamic model scaling and resource allocation.
Prior to my Ph.D. work, I focused on few-shot learning in computer vision, with applications that enhance the generalizability and adaptability of object detectors.
Selected Publications
HADIS: Hybrid Adaptive Diffusion Model Serving for Efficient Text-to-Image Generation
Qizheng Yang, Tung-I Chen, Siyu Zhao, Ramesh K. Sitaraman, Hui Guan
Submitted to ASPLOS, 2026, Under Review
[Paper]
NIVM: Real-time View Morphing via Neural Implicit Function
Tung-I Chen, D.-Y. Lee, G.-M. Su, Mohammad Hajiesmaili, Ramesh K. Sitaraman
Accepted by ACM Multimedia, 2025, Patent Filed by Dolby
[paper]
Dual-Awareness Attention for Few-Shot Object Detection
Tung-I Chen, Y.-C. Liu, H.-T. Su, Y.-C. Chang, Y.-H. Lin, J.-F. Yeh, Winston Hsu
Accepted by IEEE Transactions on Multimedia (TMM), 2021
[Paper, Code]
News
[July 2025] Our paper “NIVM: Real-time View Morphing via Neural Implicit Functio” has been accepted as a main paper in ACM Multimedia 2025
[September 2024] Our work “NIVM: Real-time View Morphing via Neural Implicit Functio” has been filed as a patent by Dolby!
[April 2024] Received PhD research internship from Dolby Laboratories