Mohammad Wahla

Background

About Mohammad Wahla

I have always found myself being drawn towards solving complex problems and thinking critically. The excitement when taking on a new challenge, analyzing the problem, exploring new ideas and gaining valuable insights in the process, finding optimal solutions and then testing them is absolutely exhilarating to me. To put it simply: I really like data and math! My interests primarily lie in the intersection of modern statistics, advanced optimization techniques, and the mathematical underpinnings of these two. Over the past decade or two, statistics and optimization methods have come to dominate the fields of data science and machine learning. However, despite sharing a significant overlap, there persists a disconnect between the two communities when it comes to cutting-edge research since optimization is categorized under the umbrella of Operations Research instead. My goal is to make use of my interdisciplinary background and help bring the two fields closer, accelerating the diffusion of novel ideas between them and further fueling the recent technological breakthroughs in data science. I received my Bachelor's in Mathematics from Rutgers University, New Brunswick in Summer 2024 and am currently taking doctoral-level statistics and optimization classes here at Rutgers. As such, I have the privilege to taking a deep-dive into the theoretical aspects of my interests under the mentorship of some of the most prominent figures in the fields of statistics and operations research. Additionally, having been a part of multiple research groups on campus, I have garnered a diverse set of technical skills over the past several years in order to bridge the gap between theory and application. This includes becoming proficient in R and MATLAB, writing complex programs in Java and Python, employing machine learning, numerical, and optimization algorithms, making use of auxiliary programs/languages such as SQL, SAS, Tableau, Power BI, Excel, and VBA, etc. My absolute go-to has of course been Python and its various libraries including NumPy, Pandas, Matplotlib, Scikit-learn, PyTorch, SymPy, and others. I am guilty of being a Pythonista! Feel free to reach out and connect if we share any interests or if you would like to potentially collaborate on something together :)