Alexander Dowling

Areas of Interest

Prof. Dowling’s research combines chemical engineering, computational optimization, machine learning, and data science organized in three research themes: (1) molecular-to-systems (multiscale) modeling and optimization, (2) optimal design of experiments and statistical inference, and (3) machine learning for bridging timescales.

Research applications domains include energy markets and infrastructure, integrated energy systems, carbon capture and sequestration, circular economies for refrigerants, sustainable hydrogen, critical minerals and materials, and advanced separations (e.g., membranes, ionic liquids).

Prof. Dowling teaches courses related to computational optimization, numerical methods, applied mathematics and statistics, data science, and advanced process controls.