Abid Amin Naeem is a researcher in Computational Science, Engineering, and Mathematics with a focus on Scientific Machine Learning, Mathematical Modeling, and Scientific Computing. I’m passionate about addressing complex real-world challenges through rigorous mathematical frameworks and data-driven approaches.

Currently pursuing my PhD in Aerospace & Mechanical Engineering at the University of Tennessee, Knoxville. I previously earned a master’s degree in Applied and Computational Mathematics from North Carolina State University, where I specialized in numerical methods, uncertainty quantification, and fluid dynamics.

I’ve had the opportunity to work on research projects involving uncertainty quantification, parametric simulations, and neural network-based solvers for partial differential equations (PDEs). My work focuses on connecting ideas from theoretical mathematics and applied machine learning to better understand and model complex systems, especially in situations where data is limited but accuracy still matters.

I’ve had the privilege of teaching undergraduate courses in optimization, fluid mechanics, and numerical analysis, and I continue to mentor and collaborate across academic and industrial domains.

Research Interests

• Optimization & Inverse Problems in Engineering: Focused on solving inverse and optimization problems in complex engineering systems, including model calibration and parameter estimation.
• Parametric PDEs & Uncertainty Quantification: Studying parametric partial differential equations with emphasis on sensitivity analysis and prediction under uncertainty.
• Scientific Machine Learning & Generative AI: Integrating machine learning with physical models to solve scientific problems, using neural operators and generative approaches.
• Numerical Analysis & High-Order Solvers: Developing efficient numerical algorithms and high-order methods for solving nonlinear systems and PDEs.

Let’s Connect

I’m passionate about collaboration, scientific outreach, and interdisciplinary research. Over the years, I’ve mentored students, contributed to research projects, and engaged with scientific communities to promote open knowledge.

Whether it’s co-authoring a paper, developing computational tools, or exploring new research directions. I’m always open to meaningful collaboration in areas like scientific machine learning, mathematical modeling, and simulation.