Research Projects

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  Eyecandy Robotics RL Pipeline

  reinforcement learning effort for Eyecandy Robotics, building and iterating policies in Isaac Lab, validating transfer through sim-2-sim workflows, and integrating control with Feetech actuators for reliable behavior across the stack.

  Reinforcement Learning Isaac Lab Sim-2-Sim Feetech Actuators
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  Auto-Bot

  Half-scale autonomous robot model featuring full kinematic simulation and embedded control systems.

  Robotics C++ & ROS Embedded Systems
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  Image Convolution on FPGA

  Hardware accelerated image processing pipeline with custom memory controllers.

  Verilog Image Processing FPGA
• 
  MuJoCo Simulation

  Advanced physics simulation environment for testing robotic control algorithms and reinforcement learning agents.

  Python MuJoCo Robotics
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  NVFP4 Implementation

  Implementation of NVIDIA's quantization paper for optimized deep learning inference on edge devices.

  PyTorch Deep Learning Quantization
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  Hyperspectral Anomaly Detection

  Machine learning algorithms to detect anomalies in hyperspectral imaging data for remote sensing.

  Python Machine Learning Scikit-Learn