Projects most directly connected to my research in computational economics, statistical validation, and quantitative modeling.
Accepted paper at MARS @ ETAPS 2026. Reproduces and extends Fagiolo & Dosi (2003) Island Model using MultiVeStA for statistical model checking, with formal convergence guarantees …
Novel PFSE estimator achieves 25% breakdown point with 32× computational speedup over MCD. Out-of-sample Sharpe 1.87 on S&P 500 (2015–2025), 29% lower drawdown during COVID-19. …
Financial machine learning project combining dynamic correlation networks, graph neural networks, and trading backtests to detect systemic risk in U.S. equity markets.
Technical implementation of the JADT paper pipeline, integrating multilingual preprocessing, topic modeling, correspondence analysis, semantic spaces, sentiment modules, and …
Projects built under competitive constraints, with strong emphasis on demos, iteration speed, and working prototypes.
Event-driven multi-agent coordination system for auction-based procurement, inventory allocation, and real-time fulfillment under demand uncertainty.
Multi-agent systemic risk simulator for financial contagion analysis on 210 S&P 500 stocks, built for Microsoft AI Dev Days Hackathon 2026 and deployed as an interactive Streamlit …
Second-place hackathon project for gas leak risk prediction using geospatial-temporal features, synthetic data augmentation, and SHAP-based interpretability.
Smaller, exploratory, or more personal builds where I experiment with interfaces, AI systems, and ideas outside my main research line.
Personal side project that merges my long-standing love for Pokémon with graph visualization, interactive systems, and Python prototyping.
Learning-to-rank recommender system for next-best-action prediction, combining Bayesian optimization and ensemble ranking to improve NDCG@5 by 36%.
Autonomous AI agent for property-market analysis, price estimation, and natural-language interaction built on predictive models and LLM orchestration.
Parameter-efficient fine-tuning pipeline using LoRA to adapt DistilBERT for sentiment analysis while training less than 1% of the model parameters.
Second-place hackathon project for gas leak risk prediction using geospatial-temporal features, synthetic data augmentation, and SHAP-based interpretability.
Computer vision and generative AI pipeline combining SAM and SDXL for interactive object segmentation and photorealistic image editing.
Retrieval-augmented chatbot that combines semantic search, custom embeddings, and LLM prompting for grounded domain-specific conversations.