PRATIK PRIYANSHU

A research-grade framework for fair, controlled comparison of classical graph neural networks, variational quantum circuits, and hybrid classical–quantum architectures for molecular property prediction. Rather than assuming quantum advantage, the goal is to isolate architectural effects under consistent data preprocessing, batching, training, and evaluation protocols.

A research framework for building trustworthy legal AI systems, evaluated on 251,038 real German court decisions. It investigates how retrieval strategy — from dense embedding search to citation graph-augmented hybrid retrieval — affects the quality, faithfulness, and fairness of AI-assisted legal decision support.

Proposed cMSCI (calibrated Multimodal Semantic Coherence Index), a geometrically grounded, uncertainty-aware evaluation metric for tri-modal coherence. Extends GRAM (ICLR 2025) to heterogeneous embedding spaces (CLIP + CLAP) with probabilistic scoring via ProbVLM and contrastive calibration against domain-specific negative banks.

A multi-agent environmental monitoring system that predicts Harmful Algal Blooms (HABs) across German lakes by fusing satellite imagery, water quality sensors, weather data, and visual analysis through autonomous AI agents communicating via Google's Agent-to-Agent (A2A) protocol.

An LLM-powered multi-agent system for analyzing traffic accident liability under German traffic law (StVO). It orchestrates nine specialized agents through LangGraph — from YOLOv8 scene perception to CAN bus telemetry parsing to RAG-augmented legal reasoning — and compares three structurally distinct pipeline variants against 30 hand-authored ground-truth scenarios.

A research-grade, trust-aware Retrieval-Augmented Generation (RAG) system that integrates domain gating, hybrid retrieval, evidence clustering, contradiction detection, and confidence calibration to minimize hallucinations in high-stakes environments.

A modular ADAS perception and safety stack integrating camera, LiDAR, and radar fusion with interaction-aware prediction, explainable AI, safety diagnostics, and scenario validation, built to mirror German OEM architecture principles.