dave@cs.stonybrook.edu

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About Me

I am a tenure-track Assistant Professor in the Department of Computer Science at Stony Brook University (SUNY) , where I lead the Photon Intelligence Lab (Φ lab). Before Stony Brook, I was a Postdoctoral Associate at MIT Media Lab with Prof. Ramesh Raskar. I received my Ph.D. from Rice University ECE Department where I was advised by Prof. Ashok Veeraraghavan. Before Rice, I obtained B.Tech. and M.Tech from Indian Institute of Technology Madras. My work has been recognized by Rice University's Best Ph.D. Thesis Award, Optica Best Paper Prize and fellowships by Texas Instruments and Qualcomm. I am hiring at all levels: interns, visiting students, PhDs, and postdocs. Please read this if you are interested.

Photon Intelligence Lab

We develop physics-aware computer vision systems that surpass human perception, enabling machines to see the invisible. These superhuman vision systems can, for instance, see beyond line-of-sight, reveal material properties of objects and detect internal mechanical stress—enabling critical applications such as navigation in adverse conditions, noninvasive biomedical imaging and smart infrastructure monitoring.

My research leverages the synergy between optics, graphics and machine learning using three pillars:

  1. Computational imaging of unique light dimensions, such as polarization and time-of-flight.
  2. Differentiable rendering of complex light transport, such as scattering and birefringence.
  3. Physics-based learning to extract hidden information, such as through neural representations and priors.

News

Teaching

Publications   ( show highlighted / show all by date / show by topic )
Keywords:  Polarization •  Time of Flight •  Single Photon •  Neural Rendering •  Deep Priors •  AR/VR •  Seeing Around Corners •  Stress Analysis
(* indicates equal contribution)
DeepIR: A Deep Network-based Image Processing Framework for Thermal Images
Vishwanath Saragadam , Akshat Dave , Ashok Veeraraghavan , Richard Baraniuk
IEEE/CVF International Conference on Computer Vision Workshop (ICCV Workshop) , 2021
[PDF] • [Code]
Foveated Non-line-of-sight Imaging
Akshat Dave , Muralidhar Madabhushi Balaji , Prasanna Rangarajan , Ashok Veeraraghavan , Marc P Christensen
Conference on Computational Optical Sensing and Imaging (COSI) , 2020
[Link] • [Paper] Best Paper Award
SNLOS: Non-line-of-sight Scanning through Temporal Focusing
Adithya Pediredla* , Akshat Dave* , Ashok Veeraraghavan
IEEE International Conference on Computational Photography (ICCP) , 2019
[Paper]
SILC: Smoother Imitation with Lipschitz Costs
Sapana Chaudhary* , Akshat Dave* , Balaraman Ravindran
International Conference on Machine Learning Workshop (ICML Workshop) , 2018
[PDF]
IITMSAT Communications System - A LeanSat Design Approach
Akshay Gulati , Shubham Chavan , Akshat Dave , et al.
IAA Conference on University Satellites Missions & CubeSat Workshop (USMCW) , 2015
[Paper]

Talks
  • [2024/06] Invited Talk @ TEDxBoston in 'Quin House
  • [2024/06] Invited Talk @ CCD Workshop in CVPR 2024
  • [2024/05] Invited Talk @ Janelia Computational Optics Conference 2024
  • [2024/02] Invited Talk @ Meta Polarization Workshop 2024
  • [2023/12] Doctoral Consortium @ SIGGRAPH Asia 2023
  • [2023/08] Course on Polarization @ SIGGRAPH 2023
  • [2023/08] Invited Talk @ University of Washington
  • [2023/04] Grundfest Lecture @ University of California, Los Angeles
  • [Show more]

TEDxBoston
The 'Quin House
Grundfest Lecture
UCLA
Honors and Awards

Professional Service

Design and source code modifed from Yuzhe Yang's webpage with permission.