Dimitrios Fafalis
Senior Lecturer in the Department of Mechanical Engineering
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Google ScholarBeyond the classroom, Professor Fafalis is committed to mentoring student engineering organizations and building partnerships with industry and government. These collaborations bring authentic datasets, technical challenges, and professional perspectives into the educational experience while giving students opportunities to work on problems with practical and societal relevance.
Before joining Columbia, Professor Fafalis taught undergraduate and graduate courses at Drexel University, where he held significant leadership responsibilities in undergraduate education and curriculum development. He chaired undergraduate affairs and curriculum committees, led a comprehensive redesign of the mechanical engineering curriculum, and served as faculty advisor to the Drexel Formula SAE team. He also developed collaborations with industry and government partners in industrial predictive analytics, machine learning-based condition monitoring, and autonomous transportation systems.
Professor Fafalis earned his Ph.D. in Computational Mechanics from Columbia University and subsequently completed a postdoctoral fellowship in Mechanical Engineering at Columbia under Professor Jeffrey Kysar. His postdoctoral research advanced the mechanical characterization and constitutive modeling of the round window membrane and contributed to computational models of therapeutic-agent delivery to the inner ear.
He holds a B.S. in Mechanical Engineering and Aeronautics from the University of Patras and three M.S. degrees from the National Technical University of Athens in Computational Mechanics, Automation Systems, and Technology Management.
His broader scholarly work encompasses computational continuum mechanics, heterogeneous materials, biomedical mechanics, micromechanical theories, autonomous systems, and resilience engineering. Across these fields, his work is unified by an interest in using computational models, data, and intelligent engineering systems to understand complex physical behavior and improve the design and operation of mechanical and aerospace systems.
