Continual learning architecture achieving 98.50% accuracy with 0.86% forgetting on Split-MNIST, outperforming EWC (97.35%, 2.29% forgetting) by 62% less forgetting and 1.15 points higher accuracy. Combines morphogenic attention, plasticity-gated MLPs, architecture genome vectors, cognitive budget allocation, and slow-pathway consolidation for dynamic capacity allocation. Validated with comprehensive multi-seed benchmarking and detailed ablation studies. Full research paper and reproducible implementation available.

A cross-platform AI sidebar that operates continuously in the background, providing real-time contextual assistance by analyzing your current screen and work context. Built with Electron for desktop integration, React for responsive UI, and FastAPI backend for intelligent processing. Seamlessly understands the application, document, or task you're currently working on, enabling context-aware suggestions, summaries, and assistance without requiring manual input or switching applications. Perfect for developers, writers, and knowledge workers.

An intelligent agricultural decision-support platform that leverages machine learning to optimize farming outcomes. Provides data-driven crop recommendations based on soil conditions, weather patterns, and historical yields. Implements fertilizer optimization algorithms to reduce costs while maintaining productivity. Includes computer vision-based leaf disease detection for early intervention. Exposes all capabilities through a production-ready REST API with explainable AI outputs showing reasoning behind recommendations, complete audit trail for compliance, and persistent history tracking. Currently deployed with live demonstrations.

A self-regulating continual learning framework that autonomously expands neural network capacity only when necessary, preventing both catastrophic forgetting and unnecessary over-parameterization. Uses novelty detection signals to identify when existing model capacity is insufficient for new tasks. Employs learnable meta-parameters to control capacity growth dynamically. Integrates gated knowledge memory mechanisms to selectively consolidate and retrieve learned information. Particularly effective for scenarios with streaming data and non-stationary task distributions. Research-grade implementation with full reproducibility.

Advanced version of the student-to-mentor platform connecting college students with qualified advisors for personalized admissions guidance and career mentorship. Features intelligent ML-based mentor discovery and matching algorithms, bookable one-on-one sessions, direct messaging for ongoing communication, integrated in-app video conferencing, university-specific feeds for institutional insights, and AI-powered college admissions analysis. Built with production-grade full-stack architecture including real-time capabilities via Agora, secure payment processing through Stripe, and user authentication via Clerk.

Evolved mentor-student connectivity platform with enhanced features for college admissions support. This iteration builds upon the original concept with refined mentor matching powered by machine learning algorithms, seamless session booking and scheduling, real-time communication tools including video calls, university-specific content feeds providing targeted institutional information, and intelligent AI-assisted college admissions analysis. Demonstrates production-ready software engineering with secure payment integration, robust authentication systems, scalable architecture, and focus on user experience.

The original prototype of what became LinkU. This version established the core concept of connecting college students with mentors for admissions guidance and career support. Implemented fundamental features including mentor discovery, session scheduling, direct messaging, and university-specific feeds. This hackathon submission validated the market need and demonstrated the viability of the platform concept, leading to its evolution into the more feature-rich LinkU platform with additional capabilities like ML-powered matching, in-app video, payment processing, and AI-assisted analysis.