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Mintæ Kim

Current Position

  • Ph.D. Student in Robotics at Hybrid Robotics Lab, BAIR, Department of Mechanical Engineering, UC Berkeley
  • Focusing on application of machine learning (mainly RL) and optimization to Robot Intelligence and Dynamical Systems (RIDS).
  • My interest spans multiple areas, including control of dynamical systems, learning-based robust locomotion control and planning, and biomimicry.

Previous Positions

  • Co-Founder and CTO of RIMES LABS
  • Leading Research Scientist at Samsung Electronics x ADOS Machine Learning Team

High Level Research Interests

Machine Learning, Robotics, Reinforcement Learning, Nonlinear Control Systems, Computer Vision, Generative Models

Resume

Here is my Resume (Will be updated soon)

Website

Here is my Website

Mintæ Kim's Projects

aooc icon aooc

Adversarial One Class Classification

drake icon drake

Model-based design and verification for robotics.

finite_element_networks icon finite_element_networks

Reference implementation of Finite Element Networks as proposed in "Learning the Dynamics of Physical Systems from Sparse Observations with Finite Element Networks" at ICLR 2022

flappy-purdue icon flappy-purdue

An open source dynamic simulation for flapping wing robots and animals

gym-pybullet-drones icon gym-pybullet-drones

PyBullet Gym environments for single and multi-agent reinforcement learning of quadcopter control

learning_reinforcement_learning icon learning_reinforcement_learning

Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.

mec231a_f23 icon mec231a_f23

UC Berkeley - MEC231A: Experimental Advanced Control Design I - Fall 2023

mec232_f23 icon mec232_f23

UC Berkeley - MEC232: Advanced Control Systems I - Fall 2023

neural-fly icon neural-fly

Training scripts, training data, and experimental data for Neural Fly

osaad icon osaad

Official Implementation of "Open Set Action Anomaly Detection"

pinns icon pinns

Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations

quadcopter-sac icon quadcopter-sac

Controlling a Rigidbody Quadcopter using Control Theory and Reinforcement Learning

reinmav-gym icon reinmav-gym

Reinforcement Learning framework for MAVs using the OpenAI Gym environment

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