“High Resolution, Deep Imaging Using Confocal Time-of-flight Diffuse Optical Tomography” wins the best-paper runner-up at ICCP 2021. This is a collaborative work between Rice ECE and the Department of Biomedical Engineering at New York University.  link: https://iccp-conference.org/  

MIT’s Ramesh Raskar has been named the 2021EI scientist of the year, due to his significant contributions to the field of electronic imaging!

The 'Split Learning for Distributed Machine Learning' (SLDML’21) workshop will be held virtually this year on March 4-5th.  The workshop aims at discussing and identifying open problems and challenges in split learning and its variants.  For full workshop program and...

The Baidu Best Paper Award at NeurIPS-SpicyFL 2020  has been awarded to a multi-institutional team, which includes MIT Camera Culture group head Ramesh Raskar, PhD student Praneeth Vepakomma, and research assistant Abhishek Singh! Check out their paper here: FedML: A Research Library and Benchmark...

COVIDaware has launched in Minnesota to help track COVID-19 exposures and contain its spread. The launch is covered by Star Tribune here: https://www.startribune.com/minnesota-launches-covid-19-tracking-app-for-your-phone/573167411/  Learn more about COVIDaware MN here: https://covidawaremn.com/

The MyDataCan™ has launched! This is a platform that gives you control of your personal data, such as the data you need to *combat COVID today*. Check out more information here: https://mydatacan.org/

Prof. Rebecca Richards-Kortum, from the department of Bioengineering at Rice University, will present “Biophotonics Solutions to Global Health Challenges”

In this work, we present a fast imaging and algorithm for high resolution diffuse optical tomography with a line imaging and illumination system. Key to our approach is a convolution approximation of the forward heterogeneous scattering model that can be inverted to produce deeper than ever before structured beneath the surface.

We take a software- inspired viewpoint of clinical trial designs to design, develop and validate HealthSense to enable expressibility of complex ideas, composability with diverse devices and services while maximally maintaining simplicity for a clinical research user.

In this paper, we present an approach for single frame, single viewpoint, passive 3D imaging using a phase mask at the aperture plane of a camera. Our approach relies on an end-to-end optimization framework to jointly learn the optimal phase mask and the reconstruction algorithm that allows an accurate estimation of range image from captured data.