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Aaron Young

Graduate Student
Massachusetts Institute of Technology (MIT)
aryoung at mit dot edu

I’m a Mechanical Engineering Masters student in the MIT Media Lab and am advised by Ramesh Raskar. Before arriving at MIT, I received my Bachelor’s Degree in Mechanical Engineering and Computer Sciences at the University of Wisconsin - Madison. under the direction of Prof. Dan Negrut. My research interests include robotics, simulation, and deep learning.

2023 - Present

Massachusetts Institute of Technology

I've joined the Camera Culture group in the MIT Media Lab advised by Ramesh Raskar.

2018 - 2022

University of Wisconsin - Madison

I double majored in Mechanical Engineering and Computer Science. Following my freshman year, I joined the Simulation-Based Engineering Laboratory, led by Prof. Dan Negrut, where I helped develop the simulation engine Chrono. I also served as a member and president of Wisconsin Autonomous, a student organization that competed in the SAE AutoDrive Challenge, a three-year competition to develop a self-driving car.

selected publications

  1. robospad.jpg
    Enhancing Autonomous Navigation by Imaging Hidden Objects using Single-Photon LiDAR
    Aaron Young, Nevindu M. Batagoda, Harry Zhang, and 4 more authors
    In ArXiv, 2024
    Under Review
  2. iris.png
    IRIS: Inter-planetary Rendering for Imaging and Sensors
    Carolina Aiazzi, Abhinandan Jain, Aaron Gaut, and 2 more authors
    In AIAA SciTech Forum, 2022
    HTML Supp
  3. gator.jpg
    End-to-end learning for off-road, deformable terrain navigation using the Chrono open-source simulation platform
    Simone Benatti, Aaron Young, Asher Elmquist, and 4 more authors
    In IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021
    HTML Supp Code
  4. enabling-ai-studies.png
    Enabling Artificial Intelligence Studies in Off-Road Mobility Through Physics-Based Simulation of Multi-Agent Scenarios
    Aaron Young, Jay Taves, Asher Elmquist, and 3 more authors
    In International Conference on Multibody Systems, Nonlinear Dynamics, and Control, 2021
    Best Paper Award
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  5. synchrono.png
    Synchrono: A Scalable, Physics-Based Simulation Platform for Testing Groups of Autonomous Vehicles And/or Robots
    Jay Taves, Asher Elmquist, Aaron Young, and 2 more authors
    In IEEE/RSJ In-ternational Conference on Intelligent Robots and Systems, 2020
    HTML Supp Code