Biography

Short bio: Mohammad Fereydounian received his Ph.D. from the University of Pennsylvania’s Electrical and Systems Engineering (ESE) Department in December 2023. He also earned a Master’s degree in Statistics from The Wharton School, University of Pennsylvania, in December 2021. Before joining Penn, he completed an M.Sc. in Pure Mathematics in 2016 and two B.Sc. degrees, one in Pure Mathematics and one in Electrical Engineering, in 2014, all from the Sharif University of Technology in Tehran, Iran. He is interested in leveraging the power of deep core mathematics to address real-world problems in various practical domains, including economics, machine learning, optimization, and communications. He has also gained experience in teaching through several roles as a guest lecturer and teaching assistant over the years, which have been recognized with teaching awards and certificates.

A perspective on my academic journey: I am deeply passionate about mathematics and have devoted my academic life to its exploration. During my undergraduate and graduate years, I had the privilege of studying a broad spectrum of mathematical disciplines at an advanced level, including:

• Abstract Algebra: Group, Ring, Field, Module, and Galois Theory
• Operator Theory and Linear Algebra
• Fourier, Complex, Mathematical, and Functional Analysis
• Probability and Measure Theory
• Manifolds and Differential Geometry
• Ordinary and Partial Differential Equations
• Logic, Set Theory, and Foundations of Mathematics
• Topology
• Number Theory
• Graph Theory
• Combinatorics
• Mathematical Statistics and Statistical Inference
• Mathematical Optimization
• Information and Coding Theory

Throughout my long academic journey, I came to realize that many real-world challenges in practical domains like machine learning can be addressed by harnessing the power of pure mathematical knowledge. However, a significant gap exists between the grounded, practical world of practitioners and the abstract, transcendent realm of pure mathematicians. It felt like having a massive engine and a powerful power plant, yet leaving them disconnected. Bridging this gap is no trivial task—it requires the construction of substantial intermediate theoretical frameworks.

Motivated to take steps toward bridging this gap, I chose to apply my years of expertise in pure mathematics to solving real-world problems rather than focusing solely on abstract mathematical questions. This transition led me to explore diverse fields, including Economic Models, Artificial Intelligence, Network Communications, Information and Coding Theory, and Optimization, where I have made meaningful contributions.

And the journey continues…