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Guining Pertin
M.S Robotics, KAIST
Senior Engineer, Enphase Energy
B.Tech ECE, IIT Guwahati
Hello There!
Welcome to my portfolio site,
I recently graduated as a Masters student in The Robotics Program from KAIST, South Korea where I also worked as a Graduate Research Assistant at Control Lab under Professor Dong Eui Chang. I completed my B.Tech in Electronics and Communication Engineering from IIT Guwahati, India in 2021, and was a Senior Engineer at Enphase Energy, India before I joined graduate studies.
My interests lie primarily in nonlinear systems, reinforcement learning, data-driven control and developing simulation models for the same. Other than research and engineering, I love teaching, reading, music, badminton and video games. If you want to search for specific keywords through all my projects, please use this big ol' search bar:
Recent Updates
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August 2026: My first authored paper G. Pertin, D. E. Chang, “NST-RL: Residual Reinforcement Learning with Approximate Optimal Regulation for Robust Drone Control,” has been accepted for publication in IEEE Robotics and Automation Letters (Q1 Robotics). Link: https://ieeexplore.ieee.org/document/11673302
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July 2026: My first authored paper G. Pertin, D. E. Chang, “Disturbance-Aware RL-PID with LLM Guidance for Robust Manipulator Control,” has been accepted for publication at International Conference on Control, Automation, and Systems 2026.
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February 2026: I completed my MS at KAIST.
Featured Projects
Master's Thesis: Foundations
This project explores and designs different approaches to involve physical knowledge (or model-based designs) into purely learning-based paradigms to improve sample efficiency and robustness for both drones and manipulators.
Master's Thesis: Differentiable Simulations
This section of my Master's thesis considers a relatively new approach for accelerated policy learning by directly backpropagating gradients through the simulation steps, using the new Nvidia Newton physics engine.
SleeperAgent: Dreaming from a third perspective
This project considers a new approach to utilize wrist-only (or ego) images from manipulators to predict the 3rd person views through novel view synthesis to improve performance along with Dreamer-V3 world-model based RL.
Bachelor's Thesis: Multi-agent multi-objective optimization using deep Q-learning
My BTech thesis on exploring multi-agent reinforcement learning by combining classical path planning and coordinated learning for the agents through a novel state representation with branched DDQN algorithm.
MoPAT Mk. V: Motion Planning Algorithms Testbed
A ROS2 based open-source, low-cost robot with 2D motion capture platform. The original version used ArUco tags for an inter-hostel competition I hosted, but the final version uses RGB LED patterns to localize and track multiple robots.
Project Zenith: Multi-UAV search and rescue
An event hosted by the Defence Research and Development Organisation for autonomous search-and-rescue missions using multi-UAV swarm for accurate detection and GPS localization of targets. Our team won SILVER.