Selected Projects

Research-to-deployment projects across applied AI, decision intelligence, mobility analytics, retail/market modeling, and privacy-safe data science.

Atlas of Opportunity

AI/GIS decision-support platform for small business, public-sector, and market opportunity analysis.

Led and contributed to the design of an interactive platform integrating large-scale datasets, predictive analytics, GIS visualization, and scenario analysis to help decision-makers evaluate market opportunities and community-level patterns.

  • Integrated mobility, place, demographic, and business datasets into stakeholder-facing analytics workflows.
  • Translated research models into tools usable by public agencies and business advisors.
  • Supported versions and analyses for South Australia, New York, Brazil, and other regional contexts.

LLM-Enhanced Decision Intelligence

Flexible analytical workflows that connect AI models with structured business decision problems.

Designed LLM/NLP-enabled approaches for model-based business analysis, customer-flow reasoning, and decision-support workflows. The emphasis is on connecting AI systems with practical analytical models and responsible use of data.

  • Explored LLM-enhanced interfaces for querying, summarizing, and reasoning over decision models.
  • Connected AI assistance with structured analytics, recommendation, and scenario analysis workflows.
  • Focused on research-to-platform translation and stakeholder usability.

Retail, Market Potential, and Location Modeling

Data-driven models for customer-flow prediction, market share estimation, and store closure decisions.

Developed gravity, network, and machine learning models using transaction, mobility, and place data to estimate market potential, predict customer behavior, and support strategic retail decisions.

  • Improved customer-flow prediction accuracy by 48% over distance-based models in retail space allocation work.
  • Built models for market share, store closure, customer patronage, and new-market analysis.
  • Collaborated with retail, manufacturing, finance, telecom, and technology partners.

Privacy-Safe Merchant Forecasting

Predictive modeling and network-based features for business performance without exposing sensitive raw data.

Developed privacy-preserving and network-based approaches for forecasting merchant and SME performance, emphasizing responsible data use and practical decision support.

  • Designed features and models for predicting merchant future performance.
  • Used privacy-safe methods to enable information sharing without revealing sensitive underlying data.
  • Published related work in Scientific Reports and other venues.

Financial Behavior Prediction

Behavioral scoring and ML models for invoice payment and customer reliability prediction.

Built predictive models and behavioral scoring systems that estimated timely invoice payment and reliability, supporting financial and operational decision-making.

  • Achieved up to 98% prediction accuracy in customer payment reliability modeling.
  • Translated behavioral analytics into practical financial decision support.
  • Worked across industry-sponsored research contexts involving finance and customer behavior.