Currently, I am an Assistant Professor in the Civil and Systems Engineering Department at Johns Hopkins University. My research is centered around scientific machine learning with a main focus on developing efficient machine-learning approaches for solving high-dimensional physics-based systems in the domains of computational mechanics and biomechanics.

• Previously, I have been a Research Assistant Professor (2022-2023) and Postdoctoral Research Associate (2021-2022) in the Division of Applied Mathematics, at Brown University, where I was advised by Prof. George Karniadakis.

• I completed my Ph.D. in 2020 at Bauhaus University, Germany under the supervision of Prof. Timon Rabczuk. My Ph.D. thesis is titled “Phase field based modeling of fracture with isogeometric analysis and machine learning methods”.

• Here is a recent copy of my CV.

• My research interests are on scientific machine learning and its applications on computational mechanics and biomechanics. In particular, I have been actively involved in the design of learning machines that leverage the underlying physical laws and/or governing equations to extract patterns from high-dimensional data generated from experiments.