Dare Badejo | Applied Scientist & AI Researcher¶
AI-Driven Decision Systems · Stochastic Optimization · Sustainability (LCA/TEA)¶
Designing decision systems for resilient, efficient, and sustainable industrial operations.
With a PhD in Chemical Engineering from the University of Delaware and hands-on industry experience at Dow, I bring together advanced optimization, stochastic modeling, agent-based systems, and sustainability analysis (LCA/TEA) to solve complex industrial challenges. My work bridges the gap between rigorous academic research and practical, high-impact solutions.
AI & Decision Systems¶
Building intelligent decision frameworks that combine optimization, machine learning, and domain expertise to drive operational excellence in industrial settings.
Optimization Under Uncertainty¶
Developing stochastic and mixed-integer models that account for real-world disruptions, enabling robust planning and scheduling for supply chains and manufacturing.
Sustainability & LCA/TEA¶
Quantifying environmental and economic trade-offs using Life Cycle Assessment and Techno-Economic Analysis to guide strategic decisions toward sustainable industrial operations.
Bridging Research & Industry¶
Translating cutting-edge academic research into actionable solutions with measurable business and societal impact at organizations like Dow.
Technical Skills¶
| Category | Technologies & Methods |
|---|---|
| Programming & Modeling | Python, GAMS, Pyomo, MATLAB, SQL, R |
| Optimization | Mixed-Integer Programming (MIP), Stochastic Programming, Multi-Objective Optimization |
| AI & Machine Learning | Predictive Analytics, Interpretable ML, Agent-Based Modeling |
| Sustainability | Life Cycle Assessment (LCA), Techno-Economic Analysis (TEA), AWARE Water Footprint |
| Data & Visualization | Pandas, NumPy, Matplotlib, Tableau, Power BI |
| Tools & Platforms | Git, Docker, Linux, HPC Clusters, Jupyter |