Sri Anumakonda

I'm really interested in how we can use vision to make cars (and robots!) interact with the real world.

Current: working on sim2real training for dexterous manipulation @LEAP Lab, studying CS and Robotics at CMU. Previously spent time working vision-based end2end systems for autonomous vehicles, building GANs, and messing around with SLAM.

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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. For a full list, please check my Github.

Created state-of-the-art pre-trained computer vision models + greedy-based path planning algorithm to navigate indoor enviroments for the visually impaired.

Used spectral analysis, landmark detection, mathematical modelling, and eye tracking to gain insights on debates and identify misinformation and bias.

Leveraging CUDA + OpenCV + PyTorch's C++ API (LibTorch) using TorchScript to run semantic segmentation at the highest FPS possible

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!

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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