Ehsan Kharazmi

Ehsan Kharazmi is a researcher in Mechanical Engineering whose work lies at the intersection of applied mathematics, scientific machine learning, and ocean engineering. He received a dual PhD in Mechanical Engineering and Computational Mathematics, and subsequently conducted postdoctoral research in scientific machine learning, where he pioneered variational formulations of physics-informed neural networks and advanced neural operator methods for complex dynamical systems.

His research focuses on physics-informed AI, fractional and distributed-order models, and AI-based digital twins for marine and energy systems, with applications including marine risers, offshore and ocean current energy systems, hydrodynamics, and manufacturing-aware design. He has led and contributed to multiple industry- and government-funded projects, successfully translating fundamental research into deployable engineering tools and sustaining long-term collaborations with industry partners.

Ehsan has published extensively in applied mathematics, mechanics, and scientific ML, and is a co-inventor on a patented underwater energy extraction system. Alongside his research, he is an experienced and dedicated educator with a strong commitment to modern, student-centered engineering education in an AI-rich era. His work bridges theory and practice, combining mathematical rigor with real-world engineering impact.