End-to-End Python implementation of Semantic Divergence Metrics (SDM) for LLM hallucination detection. Uses ensemble paraphrasing, joint embedding clustering, and information-theoretic measures (JSD, KL divergence, Wasserstein distance) to quantify prompt-response semantic consistency. Based on Halperin (2025).

Fine-tune with TEA

Multimodal deepfake detection with explainable AI, robustness validation, and calibrated trust scoring for real-world media.

Machine learning pipeline for kidney stone risk prediction, featuring calibrated models, interpretability (Permutation Importance + PDPs), and a clean modular architecture for clinical decision support.

Truncated Hisotry Framework for Synthetic Control Approaches Code

Robust spatiotemporal traffic forecasting on METR-LA & PEMS-BAY with GRU + graph-temporal models, strict time splits, robustness tests, and conformal uncertainty.

End-to-End Python replication of Camara & Aublin's (2025) monetary spillover analysis methodology. Implements rotational-angle decomposition, Bayesian VAR with Normal-Wishart priors, sign restrictions for shock identification, and a full robustness suite for international macroeconomic analysis.

End-to-End quantitative (Python) decision support system for optimizing economic resilience against disasters. Implements updated MRIA model using multi-regional supply-use tables, three-step optimization algorithm, and comprehensive impact assessment to identify vulnerabilities from production concentration and logistical constraints.