Applied AI Research Scientist focused on decision intelligence, LLM-enhanced analytics, geospatial/mobility data science, privacy-safe machine learning, and research-to-platform translation.
I am currently a Research Scientist at MIT, where my work has focused on building applied AI, machine learning, statistical, and geospatial decision-support systems using large-scale behavioral, mobility, transaction, and business data. My work connects research with real-world applications across finance, retail, telecom, public sector, healthcare, and urban systems.
- Applied AI and decision intelligence
- LLM-enhanced analytical systems
- Agentic AI and AI-assisted decision workflows
- Geospatial analytics and mobility modeling
- Retail, market potential, and customer behavior modeling
- Privacy-safe analytics and responsible data use
- Research-to-deployment systems using Python, SQL, Azure, and web applications
AI/GIS-based decision-support platform integrating large-scale data, predictive models, visualization, and scenario analysis for small businesses, public agencies, and decision-makers.
Network-based analytics for predicting merchant performance using privacy-safe features and large-scale behavioral/transaction data.
Gravity, network, and geospatial models for market share estimation, customer patronage, retail location decisions, and store closure analysis.
Applied AI workflows that use LLMs, structured reasoning, and model-based analytics to support business and location decision-making.
Python · SQL · R · Pandas · NumPy · scikit-learn · PyTorch · TensorFlow/Keras · Azure · Azure OpenAI · Azure SQL · Git · Flask · JavaScript · GIS Analytics



