I am a researcher at the intersection of computer graphics, vision, and networked systems. I currently work at NVIDIA Research in the AMRI research group. My focus is practical and resilient neural video and graphics, particularly compressed representations for streaming media. My research efforts span 3D and 4D representations, visual perception, and systems and networking.
Before joining NVIDIA, I ran a startup commercializing neural video compression. I received my PhD from the Allen School of Computer Science at the University of Washington. My dissertation proposed perceptual optimizations for visual computing hardware accelerators, storage systems, and data management systems. I received my bachelors degree at Columbia University.
Interns: I am always looking for motivated interns. If you are a PhD student interested in computer vision/graphics/generative AI for compressed 3D and 4D representations, particularly for use in interaction or multimodal learning systems, please send me an email.
Recent News (see all →)
December 2024
August 2023
Publications
Democratizing Immersive Experiences with NVIDIA AI.
In
NVIDIA GTC, 2025.
The AMRI team at NVIDIA Research presents novel immersive 3D experiences at GTC 2025 that allows users to move around in a streaming video, in 3D, in real-time. This allows for a highly immersive video viewing experience, especially when paired with 3D displays such as the Looking Glass Go or virtual/mixed reality headsets.
QUEEN: QUantized Efficient ENcoding for Streaming Free-viewpoint Videos.
In
NeurIPS, 2024.
We present an efficient representation for streamable free-viewpoint videos with dynamic Gaussians. Our method QUEEN is able to capture dynamic scenes at high visual quality and reduce the model size to just 0.7 MB per frame while training in under 5 seconds and rendering at ∼350 FPS.
GRACE: Loss-Resilient Real-Time Video through Neural Codecs.
In
NSDI, 2024.
We present a loss-resilient real-time video system called GRACE, which preserves the user's quality of experience (QoE) across a wide range of packet losses through an autoencoder-based neural video codec.
Online Overexposed Pixels Hallucination in Videos with Adaptive Reference Frame Selection.
In
arXiV, 2023.
We present a learning-based system to hallucinate HDR content in overexposed video sequences, without resorting to complex acquisition mechanisms like alternating exposures or costly processing typical of HDR imaging.
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.