Engineering Portfolio
Building sophisticated software systems with a focus on machine learning, algorithmic optimization, and real-time processing. Specialized in developing efficient solutions for complex computational challenges.
Advanced Multi-Agent Pathfinding System
A multi-agent pathfinding system that simulates complex urban mobility scenarios with dynamic obstacles, terrain types, traffic management, and weather conditions.
DeepTraject: Multi-Model Trajectory Prediction
A trajectory prediction framework that evaluates three different prediction approaches (Kalman Filter, LSTM, and Ensemble) across three distinct movement patterns: circular paths, figure-eight patterns, and lane-change maneuvers. This comprehensive evaluation demonstrates the strengths and limitations of each prediction method in different real-world scenarios.
Elastic Mesh Pathfinding System
An innovative multi-agent pathfinding system that treats drone paths as an interconnected elastic mesh, enabling dynamic path optimization, collision avoidance, and adaptive routing based on environmental conditions.
Emergent Flocking with Intent
A flocking system that combines natural swarm behaviors with goal-directed navigation, creating emergent traffic patterns and self-organizing flow structures for different mission types including delivery, surveillance, and emergency response.
Intention Broadcasting Networks
A novel approach to multi-agent coordination using real-time intention broadcasting and collective path optimization through mesh network communication. The system handles different priority levels (emergency, medical, express, standard, flexible) and generates adaptive emergency routes for conflict resolution.
Probability Shadow Pathfinding
An advanced pathfinding system using probabilistic future state prediction to enable preemptive collision avoidance and optimal path planning in dynamic environments. The system employs shadow points with uncertainty growth and dynamic rerouting based on real-time collision risk assessment.
Legal Reasoning System with Evidence Analysis
A legal reasoning system that combines probabilistic analysis, evidence evaluation, and legal standards to assist in case analysis and decision-making. The system models complex legal concepts including evidence reliability, witness credibility, chain of custody, and precedent application.
Federated Learning Sensor Network
A privacy-preserving federated learning system for distributed temperature sensors that enables collaborative pattern detection while maintaining data privacy. The system handles multiple sensor types (factory, office, outdoor) with unique event patterns and real-time visualization of both sensor data and privacy metrics.
Adaptive Swarm Formation Control
A swarm control system implementing multiple formation patterns with dynamic adaptation, obstacle avoidance, and emergent behavior optimization.
Enhanced Consensus Protocol Network
A distributed consensus system implementing leader election and fault tolerance mechanisms with support for multiple network topologies (mesh, ring, small-world) and real-time visualization of network states and vote distributions.
Cascading Confidence Ensemble (CCE*)
A multi-level classification system that cascades through increasingly complex models based on confidence thresholds. The system combines Logistic Regression, Random Forest, and XGBoost in a hierarchical ensemble that optimizes both accuracy and processing efficiency.
Temporal Ensemble Network (TEN)
A time-series prediction system that combines multiple temporal scales (hourly, daily, weekly) using ensemble learning techniques. The system leverages stacked regression with XGBoost models to handle complex temporal patterns and seasonal variations.