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A list of all the posts and pages found on the site. For you robots out there, there is an XML version available for digesting as well.
Pages
Posts
photos
portfolio
Motion Gesture Sign Language Translation Model and Pipeline
My first end-to-end machine learning project. Building using Pytorch and Huggingface for model definition; Pytorch Lightning and Kubeflow for distributed model training; MLflow and ONNX for model monitoring and export; Docker and GitHub Actions for model deployment. Project GitHub
Scalable & Causally Consistent Sharded Key-Value Store
A sharded, scalable, distributed, containerized key-value store
Graphics Engine & Shading Pipeline
Built using WebGL, GLSL, Three.js
Slugmobile/Cruz Control
A 1/10th Scale test bench built to bridge the Sim2Real gap
Video Super Resolution (VSR) Benchmark
A benchmark exploring State-of-the-Art approaches to VSR. Final Project for CSE 244c. Github Repository
publications
Slug Mobile: Test-Bench for RL Testing
Published in BayLearn, 2024
Developing a testing framework for reinforcement learning algorithms.
Video Super-Resolution Benchmark: Evaluating Spatial Fidelity and Temporal Coherence Tradeoffs
Published in CSE 244C Advanced Computer Vision Course Project, 2025
Comprehensive benchmark evaluating the tradeoffs between spatial fidelity and temporal coherence in video super-resolution methods.
Recommended citation: Shah, D.K., Louie, D.J. (2025). Video Super-Resolution Benchmark: Evaluating Spatial Fidelity and Temporal Coherence Tradeoffs. CSE 244C Advanced Computer Vision Course Project.
Download Paper
Sparse-View CT Reconstruction via Neural Signed Distance Functions and Volumetric Attenuation Fields
Published in Senior Thesis (targeting medical imaging venues), 2026
Novel approach to sparse-view CT reconstruction using neural implicit representations for improved medical imaging with reduced radiation exposure.
Recommended citation: Shah, D.K., Nikolakakis, E., Marinescu, R. (2026). Sparse-View CT Reconstruction via Neural Signed Distance Functions and Volumetric Attenuation Fields. Senior Thesis [In Preparation].