I am a researcher at the intersection of computer systems and computer graphics. I currently work at NVIDIA Research in the Hyperscale Graphics Systems group. My focus is designing systems for practical and resilient neural video and graphics. My research efforts span systems and networking, neural video and graphics representations, and visual perception.
Before joining NVIDIA, I ran a startup commercializing my PhD research on neural video compression systems. I received my PhD from the Allen School of Computer Science at the University of Washington, where I was advised by Luis Ceze and Mark Oskin. My dissertation proposed perceptual optimizations for visual computing hardware accelerators, storage systems, and data management systems. I received my bachelors degree at Columbia University.
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August 2023
July 2023
October 2022
May 2022
Publications
AI-Mediated 3D Video Conferencing.
In
SIGGRAPH Emerging Technologies, 2023.
We present an AI-mediated 3D video conferencing system that can reconstruct and autostereoscopically display a life-sized talking head using consumer-grade compute resources and minimal capture equipment.
VSS: A Storage System for Video Analytics.
In
SIGMOD, 2021.
A video storage system for video data management that enables fine-grained access to video content, caching, and redundancy elimination for overlapping field-of-view.
TASM: A Tile-Based Storage Manager for Video Analytics.
In
IEEE International Conference on Data Engineering, 2021.
A tile-based storage manager enabling spatial random access to encoded videos for analytics workloads.
VisualWorldDB: A DBMS for the Visual World.
In
Conference on Innovative Data Systems Research (CIDR), 2020.
paper (pdf),
bibtex
A vision and initial architecture for a new type of database system optimized for large-scale multicamera applications.
Vignette: Perceptual Compression for Video Storage and Processing Systems.
In
ACM Symposium on Cloud Computing (SoCC), 2019.
paper (pdf),
slides (pdf),
more recent slides (pdf),
bibtex,
SoCC Best Poster Award Winner
A system that integrates machine learning-improved compression with cloud video storage and distribution, compatible with modern codecs and hardware accelerators.
Visual Road: A Video Data Management Benchmark.
In
SIGMOD, 2019.
paper (pdf),
bibtex
A scalable analytics benchmark suite and video generator for video databases.
LightDB: A DBMS for Virtual Reality.
In
Proceedings of the VLDB Endowment (PVLDB) 11(10), 2018.
paper (pdf),
bibtex,
code (github)
A database management system designed for multi-dimensional video, like 360-degree and light field videos.
Application Codesign of Near-Data Processing for Similarity Search.
In
IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2018.
paper (pdf),
bibtex
A k-nearest neighbors hardware accelerator using processing-in-memory, for content-based image retrieval.
A Hardware-Friendly Bilateral Solver for Real-Time Virtual Reality Video.
In
High Performance Graphics (HPG), 2017.
paper (pdf),
slides (pdf),
bibtex,
code (github),
blog post
A hardware-software codesign approach to accelerate a 16-camera VR video pipeline for real-time performance.
Exploring Computation-Communication Tradeoffs in Camera Systems.
In
IEEE International Symposium on Workload Characterization (IISWC), 2017.
paper (pdf),
slides (pdf),
bibtex
A data movement characterization for resource-constrained vision and VR camera hardware.
Principles and Techniques of Schlieren Imaging Systems.
In
Columbia University Computer Science Technical Reports, 2013.
,
bibtex
A survey paper on modern Schlieren optics systems.