Applied AI systems built at the intersection of safety, governance, and real-world deployment — each tied to peer-reviewed research.
Risk-aware multi-agent reinforcement learning framework coordinating Storm, Flood, and Evacuation agents under Lagrangian safety constraints, achieving 81.5 reward with only 2.3% safety violations across six baselines.
Physics-grounded simulation framework evaluating rule-based, digital twin, and agentic AI monitoring architectures for smart city civil infrastructure, with blockchain-anchored audit trails and Kalman-filtered state estimation.
Open agentic AI framework jointly optimizing household meal planning and financial budgets under nutritional, cultural, and economic constraints using MILP and LLM orchestration across multi-store price data.
Four-layer privacy-preserving multi-agent architecture for personalized chronic disease management, combining PPO reinforcement learning with AES-256 encryption, hash-chain audit logging, and 3-tier Human-in-the-Loop governance.
Four-pillar governance framework integrating transparency, fairness, privacy, and accountability for AI-driven cybersecurity in renewable energy IoT systems, validated with a Composite Trust Index across biometric and 5G solar-microgrid domains.
Automated agentic pipeline that retrieves, individually summarizes, and synthesizes arXiv papers into publication-quality literature reviews with LaTeX export, powered by LangChain, GPT-4o, and FAISS semantic search.
Multi-agent reinforcement learning framework for autonomous mobile permission governance using Constrained MAPPO with Lagrangian safety bounds, achieving 96.3% AUROC and 41.3% privacy risk reduction with only 2.1% false-revocation rate.
PRISMA 2020-compliant systematic review synthesizing 188 peer-reviewed studies on Explainable AI across healthcare, finance, cybersecurity, robotics, and agentic AI domains, identifying SHAP and LIME as dominant techniques with critical coverage gaps.
Interrogator-based behavioral trust inference framework for Internet of Underwater Things networks, using transformer temporal modeling, metadata-driven monitoring, and continuous trust scoring for privacy-preserving anomaly detection.
Mobile-first Flutter and FastAPI platform for tracking student applications, scoring fit and risk, ranking opportunities, and integrating SOP analysis with transparent decision logic and local-first data persistence.
Research framework for multi-category retail inventory optimization that unifies forecasting, replenishment optimization, supplier-aware execution, and governance checks with reproducible benchmark pipelines.
Governance-Invariant MDP framework for safety-critical wildfire monitoring with blockchain-enforced Human-in-the-Loop oversight, achieving policy-agnostic safety guarantees and robust adversarial performance.
Low-resource NLP framework that jointly optimizes cross-lingual alignment, probabilistic calibration, and entropy regularization to improve reliability and trust calibration for multilingual LLM inference.