·         Automated Pavement Distress Detection
Leveraging image processing and machine learning to develop automated systems for detecting and classifying cracks and surface damage in pavements. This work reduces reliance on manual inspection and improves maintenance planning for transportation agencies.

·         Machine Learning in Financial Markets
Designing predictive algorithms to analyze trends in U.S. stock data, detect patterns, and support strategic decision-making in algorithmic trading and portfolio optimization.

·         AI for Agricultural Sustainability
Applying AI models to evaluate the effects of agricultural practices on the environment, particularly predicting CO₂ emissions to support sustainable farming and climate policy.

·         Customer and Market Behavior Prediction
Using data science to predict customer churn in the insurance sector and analyze vehicle auction data to forecast "kicked cars" — vehicles likely to be rejected post-sale — providing actionable insights for business optimization.

·         Supply Chain Delay Modeling
Developing and validating machine learning models that forecast shipment delays based on dynamic supply chain data, enabling better logistics planning and risk mitigation.

·         Sports Analytics and Forecasting
Combining data analytics and machine learning to forecast NBA game outcomes and betting scenarios, exploring the use of predictive modeling in recreational and competitive sports environments.