WiFi-Radar uses commodity WiFi routers to capture Channel State Information (CSI) data, which contains phase and amplitude information of WiFi signals. By analyzing how these signals reflect off human bodies, our system can detect human presence, estimate poses, and track movements - even through walls.

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

EEG-RAG is a Retrieval-Augmented Generation (RAG) system specifically designed for electroencephalography (EEG) research. It enables researchers, clinicians, and data scientists to ask natural language questions about EEG literature and receive evidence-based answers with proper citations.

(NeurIPS 2025), Compact CNNs for EEG decoding: response time prediction and behavioral assessment using competition starter kit infrastructure with custom normalization and training strategies using the Healthy Brain Network (HBN) EEG dataset

This project demonstrates a comprehensive machine learning pipeline with examples of supervised, unsupervised, and semi-supervised learning approaches. It serves as a template and learning resource for ML practitioners.

This project implements a deep learning pipeline for tumor detection and segmentation in medical images (MRI/CT) using the MONAI framework and PyTorch.

An optimized implementation of the Kimi Linear architecture - a hybrid linear attention mechanism outperforming traditional full attention.

A comprehensive industrial automation platform demonstrating integration between machine vision systems, industrial robots, PLCs, and quality control systems for modern manufacturing applications.

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

A comprehensive Simultaneous Localization and Mapping (SLAM) implementation in Python with advanced ROS 2 integration, PX4 flight control, and containerized deployment capabilities. This project provides a complete SLAM framework with advanced computer vision techniques and integration capabilities for autonomous navigation applications.

Detects when a cat walks on your keyboard desktop notification, optional screen lock.

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

The Internet of Space Things (IoST) is a revolutionary platform that brings Internet of Things (IoT) concepts to space exploration, specifically designed to support human spaceflight missions. This project creates an intelligent, interconnected ecosystem of sensors, communication systems, and AI-driven analytics to ensure crew safety,

Script to capture numeric humidity and temperature output from DHT22

Source-level patches for AMD ROCm to fix critical memory coherency issues on RDNA1/2 consumer GPUs

A comprehensive Python-based machine learning platform for real-time seismic event detection, analysis, and classification. This system integrates with authoritative seismic data sources (USGS and IRIS) to provide intelligent earthquake monitoring and analysis capabilities.

This project is designed to enhance workflows and optimize processes through GitHub Actions, AI-powered tools, and intelligent automation.

GPU-Accelerated Brain Image Processing Pipeline for OpenNeuro Datasets

Verification-first test infrastructure for secure, dependency-aware Java to Python translation services.

A comprehensive collection of common programming questions, solutions, and best practices covering various topics from coding challenges to security concepts.