Jairo Maldonado-Contreras

Robotics PhD Candidate at Georgia Tech

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Hi! My name is Jairo, and I’m a Robotics PhD candidate at the Georgia Institute of Technology, working under the mentorship of Aaron Young. My research focuses on human intent recognition and the development of deep learning models to enhance lower-limb prosthetic control.

Before joining Georgia Tech, I completed my B.S. in Mechanical Engineering at CSU Long Beach, where I received the College of Engineering’s 2019 Outstanding Graduate Award. During my studies, I gained valuable experience through internships at renowned institutions, including NASA JPL, MIT, MIT Lincoln Laboratory, and the Shirley Ryan Ability Lab, working on cutting-edge robotics and assistive technologies.

I have extensive experience in deploying real-time deep neural networks, incremental learning frameworks, domain adaptation techniques, probabilistic inference and optimization, visual perception systems, and autonomous robotic navigation. Additionally, I specialize in the design, fabrication, and control of complex multi-degree-of-freedom mechanisms.

I am currently seeking full-time opportunities in physical AI, where I can integrate artificial intelligence with physical systems to create intelligent machines capable of interacting with the real world. I am driven by the potential of AI to improve the human experience. My extensive background in robotics and AI has prepared me to tackle complex challenges in this space.

publications

  1. Transfer Learning for Walking Speed Estimation Across Novel Prosthetic Devices and Populations
    J. Maldonado-Contreras, C. Johnson, I. Knight, A. Sawant, S. Zhou, H. Kim, K. R. Herrin, and A. J. Young
    Under Review @ ICRA
  2. Real-time Adaptation of Deep Learning Walking Speed Estimators Enables Biomimetic Assistance Modulation in an Open-Source Bionic Leg
    J. Maldonado-Contreras, C. Johnson, S. Zhou, H. Kim, I. Knight, K. R. Herrin, and A. J. Young
    Under Review @ TMRB
    PDF
  3. Continuous-Context, User-Independent, Real-Time Intent Recognition for Powered Lower-Limb Prostheses
    K. Bhakta, J. Maldonado-Contreras, J. Camargo, S. Zhou, W. Compton, K. Herrin, and A. J. Young
    Under Review @ ASME
    Website
  4. Accelerating Constrained Continual Learning with Dynamic Active Learning: A Study in Adaptive Speed Estimation for Lower-Limb Prostheses
    C. Johnson, J. Maldonado-Contreras, and A. J. Young
    International Symposium on Medical Robotics (ISMR), 2024
    PDF
  5. User- and Speed-Independent Slope Estimation for Lower-Extremity Wearable Robots (Open-source Dataset)
    J. Maldonado-Contreras, K. Bhakta, J. Camargo, P. Kunapuli, and A. J. Young
    Annals of Biomedical Engineering (ABME), 2023
    PDF
  6. Adaptive Lower-Limb Prosthetic Control: Towards Personalized Intent Recognition & Context Estimation
    C. Johnson, J. Cho, S. Chaluvadi, J. Maldonado-Contreras, and A. J. Young
    Journal of Medical Robotics Research (JMRR), 2023
    PDF
  7. OpenSim Model for Biomechanical Analysis with the Open-Source Bionic Leg
    J. Camargo, K. Bhakta, J. Maldonado-Contreras, S. Zhou, K. Herrin, and A. J. Young
    International Symposium on Medical Robotics (ISMR), 2021
    PDF
  8. NeBula: TEAM CoSTAR's Robotic Autonomy Solution that Won Phase II of DARPA Subterranean Challenge
    A. Agha, K. Otsu, B. Morrell, …, J. Maldonado-Contreras, …, and J. Burdick
    Field Robotics, 2022
    PDF
  9. Nebula: Quest for robotic autonomy in challenging environments; team costar at the darpa subterranean challenge
    A. Agha, K. Otsu, B. Morrell, …, J. Maldonado-Contreras, …, and J. Burdick
    Continuous-Discrete Reinforcement Learning for Hybrid Control in Robotics (CoRR), 2021
    PDF
  10. Proprioceptive Improvements of Lower-Limb Amputees under Training with a Vibrotactile Device - A Pilot Study
    J. Maldonado-Contreras, P. Marayong, I.H. Khoo, R. Rivera, B. Ruhe, and W. Wu
    IEEE Health Care Innovations and Point of Care Technologies Conference (HI-POCT), 2017
    PDF

Mauna Loa