Computational Cameras and Displays

Shree K. Nayar is the T. C. Chang Professor of Computer Science at Columbia University. He heads the Columbia Vision Laboratory (CAVE), which develops computational imaging and computer vision systems. His research is focused on three areas - the creation of novel cameras that provide new forms of visual information, the design of physics-based models for vision and graphics, and the development of algorithms for understanding scenes from images. His work is motivated by applications in the fields of imaging, computer vision, robotics, virtual reality, augmented reality, visual communication, computer graphics and human-computer interfaces. Nayar received his PhD degree in Electrical and Computer Engineering from the Robotics Institute at Carnegie Mellon University. For his research and teaching he has received several honors including the David Marr Prize (1990 and 1995), the David and Lucile Packard Fellowship (1992), the National Young Investigator Award (1993), the NTT Distinguished Scientific Achievement Award (1994), the Keck Foundation Award for Excellence in Teaching (1995), the Columbia Great Teacher Award (2006), the Carnegie Mellon Alumni Achievement Award (2009), Sony Appreciation Honor (2014), the Columbia Engineering Distinguished Faculty Teaching Award (2015), the IEEE PAMI Distinguished Researcher Award (2019), the Funai Achievement Award (2021), and the Okawa Prize (2023). For his contributions to computer vision and computational imaging, he was elected to the National Academy of Engineering in 2008, the American Academy of Arts and Sciences in 2011, the National Academy of Inventors in 2014, and the Indian National Academy of Engineering in 2022.

Ioannis Gkioulekas is an associate professor at the Robotics Institute, Carnegie Mellon University (CMU). He is a Sloan research fellow and a recipient of the NSF CAREER award and the Best Paper award at CVPR 2019, the Best Student Paper award at CVPR 2024, the Best Paper award at SIGGRAPH 2024, and more. He has PhD and MS degrees from Harvard University, where he was advised by Todd Zickler, and a Diploma from the National Technical University of Athens, where Petros Maragos advised him. His works broadly on computer vision, computer graphics, and computational imaging, with a focus on problems including non-line-of-sight imaging, tissue imaging, interferometric imaging systems, physically based rendering, and differentiable rendering.

Laura Waller leads the Computational Imaging Lab at UC Berkeley, which develops new methods for optical imaging, with optics and computational algorithms designed jointly. She holds the Ted Van Duzer Endowed Professorship and is a Senior Fellow at the Berkeley Institute of Data Science (BIDS), with affiliations in Bioengineering and Applied Sciences & Technology. Laura Waller earned her B.S., M.Eng., and Ph.D. degrees from the Massachusetts Institute of Technology, USA. She was a postdoctoral research associate at Princeton University, USA before joining the UC Berkeley. Waller has established herself as a visionary in the important new field of computational imaging through her pioneering work on phase retrieval from intensity measurements. She has also made advancements in Fourier ptychography, 3D imaging in scattering media and in imaging using a diffuser. In the past four years, Waller has generated ~$6M in research funding and published 27 journal papers and 6 patent applications. Her research has been recognized through over 100 invited talks, and she has contributed to the research community by serving on 44 conference committees (14 as chair) and as Associate Editor of IEEE Transactions on Computational Imaging. She has received many other awards, including the SPIE Early Career Achievement Award, the Chan-Zuckerberg Initiative Biohub Investigator Award, and the OSA Foundation’s Ivan P. Kaminow Outstanding Early Career Professional Prize. She is a Fellow of OSA and the American Institute for Medical and Biological Engineering. In 2021, she received OSA's Adolph Lomb Medal "for important contributions to the advancement of computational microscopy and its applications”, and in 2024 she received the Max Planck-Humboldt Medal for her outstanding achievements in computational microscopy.

Ren Ng is a professor in Electrical Engineering and Computer Science at the University of California, Berkeley. His research interests are in imaging, graphics, computer vision, human vision and artificial intelligence. Prior to Berkeley, Ren was founder and CEO of Lytro, Inc., which commercialized his Ph.D. research and brought consumer light field cameras to market. Ren completed his Ph.D. in computer science at Stanford University, and received the ACM Doctoral Dissertation Award and Stanford's Arthur Samuel Award. Ren has received the 2020 ECCV Best Paper Honorable Mention, Jim and Donna Gray Faculty Award for Undergraduate Teaching, Hellman Faculty Fellowship, Sloan Research Fellowship, the HIPA Photographic Research Award, PMDA Technical Achievement Award, R.I.T.'s Imaging Hall of Fame, the Selwyn Award from the Royal Photographic Society, MIT Tech Review's TR35 and Entrepreneur of the Year, Fast Company's 100 Most Creative People in Business, and Silicon Valley Journal's 40 under 40.

Manasi is currently a Ph.D student advised by Prof. Davide Scaramuzza at Robotics and Perception Group, in the Department of Informatics, University of Zurich, and the Department of Neuroinformatics, University of Zurich and ETH Zurich. Manasi’s interests lie at the intersection of computer vision and computational photography with particular interest in developing algorithms for event-based cameras, and their applications in robotics and augmented reality. Manasi was recently featured in the NCCR Robotics campaign for her work on event cameras. Previously, Manasi graduated from Carnegie Mellon University with Masters in Electrical and Computer Engineering in 2018, where she was advised by Prof. Srinivasa Narasimhan. During her Ph.D, she also worked at the Camera Culture Group at MIT, advised by Prof. Ramesh Raskar.

Suyeon is currently a postdoctoral scholar at the Stanford Computational Imaging Lab, working with Prof. Gordon Wetzstein. He is generally interested in developing computational optical systems at the intersection of graphics, optics, AI, and vision science. Lately, he has been developing holographic display systems incorporating machine learning towards next-generation VR/AR displays. His research has been partly supported by a Meta Research PhD Fellowship, a SPIE Optics and Photonics Education Scholarship, a Kwanjeong Scholarship, a Korean Government Scholarship, and a GPU gift from NVIDIA.

Florian Willomitzer an Associate Professor at the Wyant College of Optical Sciences and directs the Computational 3D Imaging and Measurement (3DIM) Lab. He graduated from the University of Erlangen-Nuremberg, Germany, where he received his Ph.D. degree with honors (‘summa cum laude’) in 2017. During his doctoral studies, he investigated physical and information-theoretical limits of optical 3D-sensing for medical imaging and industrial inspection, and implemented sensors that operate close to these limits. In the 3DIM Lab, Prof. Willomitzer and his team work on novel methods to image hidden objects through scattering media or around corners, high-resolution holographic displays, unconventional methods for precise VR eye-tracking, and the implementation of high-precision metrology methods in low-cost mobile handheld devices. Moreover, the group develops novel time-of-flight and structured light imaging techniques working at depth resolutions in the 100μm-range. Prof. Willomitzer serves/served as Chair and Committee Member of several Optica COSI conferences, Optics Chair of the 2022 IEEE ICCP conference, Chair and Host of the Optica Incubator on Imaging Through 100 Scattering Lengths, Committee member of Optica FiO conferences and as reviewer for Nature, Optica (OSA), SPIE, IEEE and CVPR. He is a recipient of the NSF CRII grant, winner of the Optica 20th Anniversary Challenge, and his Ph.D. thesis was awarded with the Springer Theses Award for Outstanding Ph.D. Research.

Rick is currently a research scientist at Apple where he focuses on neural rendering, generative models for sequences, and computational imaging and displays. His research has been incorporated into various Apple products, including Siri, Scribble on iPad, QuickPath keyboard on iOs, and watchOS. His current research interests are broadly in generative models, computational photography, and novel sensors. Rick obtained his PhD from the ECE Department at Carnegie Mellon University, where he worked with Prof. Vijayakumar Bhagavatula and Prof. Aswin Sankaranarayanan on computational photography and displays, computer vision, and machine learning. He received hs M.S. and B.S. degrees in electrical engineering from National Taiwan University, where he worked with Prof. Tian-Li Yu, and Dr. Yu-Chiang Frank Wang on image processing.