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I'm an autonomous vehicle researcher building in the intersection between computer vision and self-driving cars. Current: studying robotics @cmu, member @Masason Foundation, creating SLAM-based systems for long-term data association. updates coming soon! Prev slam research @ut austin and @tks.world where I worked with Shell, the United Nations, and Instacart. Also am one of the youngest certified self-driving car engineers in the world, was featured on Udacity for the work I'm doing. Email / Linkedin / Twitter / Github / Medium / CV / 2yr life update |
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My primary research interests are in the field of autonomous vehicles and robotics, more specifically towards computer vision for vision-based autonomy. You can find some of my projects in this space below. This is just an overview of the work I'm doing. For a full list, please check my Github. |
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October 2024 Github / Website Created state-of-the-art pre-trained computer vision models + greedy-based path planning algorithm to navigate indoor enviroments for the visually impaired. |
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October 2024 Github Used spectral analysis, landmark detection, mathematical modelling, and eye tracking to gain insights on debates and identify misinformation and bias. |
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February 2023 - May 2023 Github Leveraging CUDA + OpenCV + PyTorch's C++ API (LibTorch) using TorchScript to run semantic segmentation at the highest FPS possible |
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January 2022 - February 2022 RL Article / Tweet Leveraged Reinforcement Learning algorithms to help train a self-driving agent to drive in a highway environment [using discrete controls]. |
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November 2021 - January 2022 Research Proposal / Tweet Used Deep Convolutional Networks to control self-driving steering, read more than 60 papers in the space, and met some really smart people from the wayve.ai + comma.ai team! |
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September 2021 - October 2021 Medium article / Github Using DC-GANs to create synthetic data that can be used to train + validate the robustness of autonomous vehicles. End goal is to apply to extrapolate the data pool we have for adverse driving scenarios/any situations where limited data is available. |
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May 2021 Medium article / Certificate / Github Used my knowledge throughout the Udacity Self-Driving Nanodegree [from perception and sensor fusion of LiDAR and radar sensors to polynomial trajectory generation] to create my capstone project; an autonomous vehicle capable of driving in simulation (using waypoitns). I built trajectory algorithms, localization algorithnms, and kalman filters to name a few of the projects I built! |
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