Machine Learning and Autonomy for Diverse Domains (MADD) at
Harvey Mudd
We design algorithms for safe perception and localization for autonomous vehicles across ground, air, and space. We use machine learning techniques to enable reliable and adaptive autonomy in diverse and challenging environments.
We design algorithms for safe perception and localization for autonomous vehicles across ground, air, and space. We use machine learning techniques to enable reliable and adaptive autonomy in diverse and challenging environments.
If you are interested in collaborating with us, please email admohanty@g.hmc.edu with a brief description of your interests and why you are interested in working with us!
News
News
Feb 2025:
Feb 2025:
- Prof. Mohanty has a paper accepted at the ICRA 2025 conference to be held in Atlanta.
Dec 2024
Dec 2024
- Bryce Tu Chi and Sammy Tribble submit a paper to the MIT Complex Adaptive Systems (CAS) conference.
Nov 2024
Nov 2024
- Bob Zheng and Huaze Liu 's abstracts are accepted at the ION PLANS conference.
- Prof. Mohanty receives the OCAC Faculty Mentoring and Collaborative Research Award at Mudd.
- A team of students led by Bob Zheng and Huaze Liu receive the Shanahan funding for their successful proposal on Aquadia, the pool cleaning robot.
Sept 2024
Sept 2024
- Prof. Mohanty receives 'Outstanding Reviewer Award' and presents her paper on Self-Supervised Tight Coupling of GNSS with Neural Radiance Fields for UAV Navigation at the ION GNSS+ 2023 conference in Baltimore, Maryland.