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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.
Thank you for your interest in joining Φ lab. Please review this information before contacting me.
Prospective PhD students: Please apply through the CS graduate admissions and mention my name in your Statement of Purpose. You can also fill out this Google Form.
Prospective postdocs and interns: Fill out the Google form and email me with your CV (subject: "Prospective Postdoc" or "Prospective Intern").
Current SBU students: Fill out the Google form and email me with your CV (subject:"SBU Student").
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:
- Computational imaging of unique light dimensions, such as polarization and time-of-flight.
- Differentiable rendering of complex light transport, such as scattering and birefringence.
- Physics-based learning to extract hidden information, such as through neural representations and priors.
News
- I'll be at CVPR 2025 co-organizing NFBCC workshop and presenting NeST at CV4Science and PI3DVI workshops, Blurred LiDAR as highlight poster, and Real-time NLOS as demo. Let's meet up!
- "Neural Stress Tensor Tomography leveraging 3D Photoelasticity" accepted for Transactions on Graphics.
- Honored to be selected in the 2024 cohort of INK Fellows.
- My TEDx talk "Superhuman Vision: AI Sees What You Can't" is up on Youtube.
- Honored to receive the 2024 Ralph Budd Award for the best engineering Ph.D thesis at Rice University.
Teaching
Publications ( show highlighted / show all by date / show by topic )
Aaron Young* , Nevindu M. Batagoda* , Harry Zhang , Akshat Dave , Adithya Pediredla , Dan Negrut , Ramesh Raskar
[Project Page] • [Video] • [Preprint]
Akshat Dave
[Thesis] • [Doctoral Consortium Abstract] Ralph Budd Thesis Award , SIGGRAPH Asia 2023 Doctoral Consoritum
Seung-Hwan Baek , Ramesh Raskar , Jinwei Ye , Akshat Dave , Achuta Kadambi , Huaijin (George) Chen
Kushagra Tiwary* , Akshat Dave* , Nikhil Behari , Tzofi Klinghoffer , Ashok Veeraraghavan , Ramesh Raskar
[Project Page] • [Paper] • [Code] • [Talk] • [MIT News] MIT Front Page Spotlight
Akshat Dave , Yongyi Zhao , Ashok Veeraraghavan
[Project Page] • [Paper] • [Code] • [Dataset] • [Talk]
Tianyi Zhang , Mel White* , Akshat Dave* , Shahaboddin Ghajari , Ankit Raghuram , Alyosha C Molnar , Ashok Veeraraghavan
Byeongjoo Ahn , Akshat Dave , Ashok Veeraraghavan , Ioannis Gkioulekas , Aswin C. Sankaranarayanan
[Project Page] • [Paper] • [Supplement] • [Code] Oral Presentation
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
- [2023/02] PixelCafe Seminar @ University of California, San Diego
- [2023/01] Invited Talk @ Stanford University
- [2022/09] Invited Talk @ Massachusetts Institue of Technology
- [2022/08] Invited Talk @ Carnegie Mellon University
- [2022/04] Invited Talk @ University of Maryland
- [Show more]
TEDxBoston
The 'Quin House
Grundfest Lecture
UCLA
Honors and Awards
- Ralph Budd Award for the best Ph.D. Engineering Thesis at Rice University in 2024
- Selected for SIGGRAPH Asia 2023 Doctoral Consortium
- Lodieska Stockbridge Vaughn Fellowship in 2023 for outstanding graduate research
- Rice D2K Research Mentoring Fellowship in 2022 for datasceince solutions to real-world problems.
- Best Student Paper Prize at the 2020 OSA Imaging and Applied Optics Congress
- Texas Instruments Fellowship in 2017 for Ph.D. study at Rice University
- Qualcomm Innovation Fellowship in 2016 and 2017 for Masters thesis research
- Svaagata Erasmus Mundus Scholarship in 2015 for semester exchange at KTH University, Sweden
- All India Rank 212 amongst 1.1 million participants in undergraduate entrance exam AIEEE 2012
- KVPY National Fellowship for high school and undergraduate research by the Government of India
Professional Service
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Organizer
- ECCV 2024 Workshop on Neural Fields Beyond Conventional Cameras
- SIGGRAPH 2023 Course on Polarization-Based Visual Computing
- MIT Media Lab Fall Meeting 2023 Workshop on Extreme Sensing
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Publications Chair
- ICCP 2024
-
Conference Reviewer
- SIGGRAPH • SIGGRAPH Asia • ICCP • CVPR • ECCV • IROS
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Journal Reviewer
- ACM TOG • IEEE TPAMI • IEEE TCI • OSA Optics Express • OSA Applied Optics