About
I am currently a Research Scientist at Mitsubishi Electric Research Laboratories (MERL) in Cambridge, MA. I received my Ph.D. in electrical engineering from Boston University in 2020, during which I was supported by a Draper Fellowship. Following my PhD, I was a postdoctoral researcher at Stanford University.
My research lies at the intersection of optics, electronics, signal processing, mathematical modeling, and computer vision. A large emphasis of my work is in improving 3D reconstruction methods, including single-photon lidar, FMCW lidar, optical coherence tomography, radiation source localization, and seeing around corners.
News
December 2021
🏆 I'm honored to have won the 2021 Best PhD Dissertation Award from the IEEE Signal Processing Society! The award will officially be presented at ICASSP 2022 in Singapore.
July 2021
🎤 Invited talk for UCLA's Warren Grundfest Lecture in Computational Imaging: "One photon at a time: Compensating for non-ideal electronics in lidar imaging"
June 2021
💼 I've started a new position as a Research Scientist on the Computational Sensing team at Mitsubishi Electric Research Laboratories.
January 2021
📄 High-Flux Single-Photon Lidar appears in Optica, demonstrating how Markov chain modeling can mitigate dead times in both single-photon detectors and timing electronics.
December 2020
🏆 I'm thrilled to have my 2017 paper "A Few Photons Among Many: Unmixing Signal and Noise for Photon-Efficient Active Imaging" selected for the 2020 IEEE Signal Processing Society Young Author Best Paper Award! The award will be officially presented at ICASSP 2021 in Toronto.
November 2020
📄 Seeing Around Corners with Edge-Resolved Transient Imaging published in Nature Communications!
📄 Dithered depth imaging, describing how depth resolution can be improved in quantization-limited time-of-flight systems, is published in the "3D Image Acquisition and Display: Technology, Perception and Applications" feature issue of Optics Express.
July 2020
📄 Advances in Single-Photon Lidar for Autonomous Vehicles: Working Principles, Challenges, and Recent Advances published in IEEE Signal Processing Magazine
May 2020
🏆 My PhD dissertation won the Outstanding Dissertation Award - Electrical Engineering from the BU ECE Department
January 2020
💼 Started a postdoc at Stanford in the Computational Imaging Lab
🎓 Officially graduated with my PhD in Electrical Engineering from Boston University
July 2019
📄 Excited to have two papers published in the same issue of IEEE Transactions on Signal Processing: Estimation From Quantized Gaussian Measurements: When and How to Use Dither and Dead Time Compensation for High-Flux Ranging
October 2018
🏆 Won a Best Student Paper Award at ICIP 2018 for a paper on dither in lidar systems
September 2017
📄 Paper on single-photon lidar in high ambient light published in IEEE Transactions on Computational Imaging: A Few Photons Among Many: Unmixing Signal and Noise for Photon-Efficient Active Imaging
Education & Training
Stanford University
Postdoctoral Researcher, Electrical Engineering
2020 - 2021
Boston University
Ph.D., Electrical Engineering
Dissertation: Probabilistic Modeling for Single-Photon Lidar
2014 - 2020
Tufts University
B.S., Electrical Engineering
2010 - 2014
Press
Feb. 2022: Joshua Rapp wins 2021 IEEE Signal Processing Society Best Ph.D. Dissertation Award, BU Center for Information & Systems Engineering
Dec. 2021: Joshua Rapp wins Best Dissertation Award from the IEEE Signal Processing Society, MERL News
Feb. 2021: Success in a Major Key, Tufts School of Engineering
Jan. 2021: New Frontiers in Self-Driving Cars, BU Center for Information & Systems Engineering
Dec. 2020: Joshua Rapp wins the 2020 IEEE SPS Young Author Best Paper Award, BU Center for Information & Systems Engineering
Dec. 2020: New imaging technique uses corners to see around corners, BU College of Engineering
Oct. 2018: The Depth of Depth Measurement, BU College of Engineering