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

(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.

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

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

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

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

Lightweight, extensible Brownian dynamics toolkit for nanoparticles and proto-nanorobotics NanoSimLab provides accessible tools for simulating and analyzing nanoparticle systems using Brownian dynamics, with a focus on nanorobotics research and development. The toolkit runs out-of-the-box with NumPy/SciPy and offers seamless integration.

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.

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.

A specialized compression and interface layer that enables Apple's BCI HID technology to work more efficiently with existing BCI compression algorithms, focusing on low latency and high signal quality.

GPU-Accelerated Brain Image Processing Pipeline for OpenNeuro Datasets

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 Brain-Computer Interface (BCI) system that visualizes memory formation patterns in real-time, helping users optimize learning and recall through neurofeedback.

WACV 2026 RWS Challenge: Building object detectors that maintain consistent performance across seasons, weather patterns, and day-night cycles in thermal imagery.

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

This project provides Python scripts for visualizing temperature and earthquake data using matplotlib, pandas, and numpy. It includes tools for data conversion, plotting, and basic testing, aimed at scientific analysis and educational use.

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.