A comprehensive toolkit for developing and benchmarking compression algorithms specifically designed for neural data streams in brain-computer interfaces (BCIs). This project provides efficient, real-time compression solutions that preserve the critical characteristics

Brain-Forge is an advanced brain-computer interface system that combines cutting-edge neuroimaging technologies to create comprehensive brain scanning, mapping, and simulation capabilities. The platform integrates multi-modal sensor fusion, real-time data processing, and neural simulation to enable unprecedented understanding and modeling of brain

This repository contains experimental quantum computing algorithms and simulations for cutting-edge research applications including medical genomics, cosmology, and quantum machine learning.

A project to build GPU acceleration for LLaMA models on local computers and AWS, leveraging GPU resources for efficient inference and training.

An AI-powered system for analyzing James Webb Space Telescope images to identify artificial structures, Dyson spheres, and objects that don't follow standard gravitational rules - potential indicators of intelligent extraterrestrial life.

A comprehensive collection of GPU kernel examples demonstrating essential parallel computing techniques for modern GPU programming. This project supports both NVIDIA CUDA and AMD ROCm platforms, focusing on the most in-demand GPU programming skills required in industry today.

GPU-Accelerated Brain Image Processing Pipeline for OpenNeuro Datasets

A high-performance C++ application for generating 3D point clouds from stereo camera images using GPU acceleration (CUDA for NVIDIA or HIP for AMD GPUs).

Production-ready scaffold for a spacecraft Vehicle Management System spanning real-time firmware (FreeRTOS), ROS 2 autonomy, and simulation.

QuantumForge is an open-source framework that revolutionizes quantum chemistry calculations by combining the power of GPU acceleration, deep learning, and density functional theory. Built for researchers who demand both accuracy and performance.

AdaAttn is a GPU-native attention mechanism that dynamically adapts both numerical precision and matrix rank at runtime, reducing memory bandwidth and computational overhead in large language models without sacrificing model quality. By aligning linear algebra operations with modern GPU hardware characteristics.

A comprehensive Python-based simulation environment for First Lego League competitions, featuring realistic robot physics, interactive game maps, and mission scenarios.

Robust, open-source pipeline to detect actionable mental states from EEG (consumer and research-grade). Train SOTA models (EEGNet, Shallow/Deep ConvNets, lightweight Transformers), leverage self-supervised pretraining, and run real-time

bridging quantum computing and neural networks to unlock computational capabilities impossible with classical systems alone. Built for researchers, developers, and enterprises seeking quantum advantage in machine learning.

A high-fidelity real-time simulation of a space launch system using QNX Neutrino RTOS, designed to emulate real-time conditions, subsystem communication, and fault-tolerant behavior for pre-launch and ascent operations.

A low-cost, open-source EEG acquisition and preprocessing system spanning circuit-level prototyping, simulation (Simscape), digital signal acquisition via an ADS1115 ADC and Raspberry Pi Zero V1.3, and software preprocessing using Python and MATLAB.

Python project to experiment with bounded spacecraft motion near the binary asteroid system Moshup-Squannit (1999 KW4), inspired by RF3BP pulsating-rotating formulations.

This repository contains examples of how to accelerate common Python data science libraries using NVIDIA GPUs. Each notebook demonstrates a different library and shows how to enable GPU (CUDA) acceleration with minimal code changes.

A high-performance neural signal simulator with real-time GPU-accelerated visualization for neuroscience research and development.

Laser Cut Vectorizer converts raster-like artwork into SVG contour paths that are easier to clean, organize, and prepare for laser cutting workflows. The tool focuses on predictable, scriptable preprocessing: thresholding, contour detection, geometric simplification, and physical-size-aware SVG output.