Biography

I joined the Integrated Applied Mathematics Ph.D. program at the University of New Hampshire in Fall 2023. I earned a B.S. in Mathematics from the University of Ilorin, Nigeria (2016), an M.Sc. in Mathematics from the same institution (2022), and in 2023 completed a double master’s: Mathematics in Finance and Economics (University of Silesia, Poland) and Mathematical Engineering (University of L’Aquila, Italy). I have served as a teaching assistant across Fall and Spring semesters for Reinforcement Learning, Mathematical Optimization, Introduction to Machine Learning, and Introduction to Engineering Computing (MATLAB), supporting lectures, grading, and student office hours. Currently, I work with my advisor, Professor Marek Petrik, on reinforcement learning, machine learning, and mathematical optimization, with a focus on optimal decision-making in stochastic environments.

Academic Status

PhD Student - 3rd

Research Area/Department

Machine Learning/AI

Major/Specialty

Applied Mathematics and Computer Science

Degrees Earned or in Progress

University of New Hampshire, USA Aug 2023 – Present • Ph.D. Integrated Applied Mathematics University of Silesia, Katowice, Poland Oct 2022 – Oct 2023 • M.Sc. Financial Mathematics and Economics University of L’Aquila, L’Aquila, Italy Sept 2021 – Oct 2023 • M.Sc. Mathematical Engineering University of Ilorin, Ilorin, Nigeria Oct 2018 – Jan 2022 • M.Sc. Mathematics University of Ilorin, Ilorin, Nigeria Oct 2012 – Sept 2016 • Bachelor of Science in Mathematics

Academic Preparation

Reinforcement Learning Advanced Machine Learning Mathematical Optimization Numerical Linear Algebra Numerical Partial Differential Equation Partial Differential Equation Applied Functional Analysis

Research/Publications

Media Article: Ahmed Senior Ismail, (SoHPC2022_final_reports). Optimization of Neural Networks to Predict Results of Mechanical Models. https://summerofhpc.prace-ri.eu/wp-content/uploads/2022/10/SoHPC2022_final_reports.pdf https://youtu.be/v0QTRhuCGMY?si=3dGN8UrOL3WIeFg0

Research/Academic Interests

My research targets the intersection of reinforcement learning, machine learning, optimization, and operations research for data-driven decision-making under uncertainty. I focus on risk measures and distributional RL (e.g., VaR/CVaR), stochastic control, and policy optimization with theoretical guarantees.

Computational and Data Science Areas

Applied Mathematics; Artificial Intelligence and Intelligent Systems

Motivation

I am motivated to participate in the Sustainable Research Pathways program because it directly aligns with both my research and personal interests. As a Ph.D. student in Integrated Applied Mathematics at the University of New Hampshire, working under the tutelage of Professor Marek Petrik on reinforcement learning, machine learning, and optimization for decision-making under uncertainty, I am eager to apply and contribute my skills to meaningful projects at the intersection of mathematics, computing, and societal impact. Beyond research, I am attracted to the program’s commitment to building inclusive, sustainable communities of scientists and engineers. Having studied and worked across multiple countries and educational systems, I deeply value diversity in perspectives and experiences, and I believe that collaboration across backgrounds is essential for robust, innovative science. I see this program as a unique opportunity to not only advance my technical expertise but also to contribute actively to a community where everyone is respected, valued, and successful I strongly believe that the summer project experience will allow me to gain exposure to cutting-edge applications of artificial intelligence and optimization while strengthening my ability to put theoretical knowledge into practice. At the same time, I look forward to engaging in the program’s career development and mentorship activities, where I can both learn from established researchers and share experiences with peers. Most importantly, I hope to build lasting professional relationships and a collaborative network that extends beyond the program. Thank you.

Lightning Talk Title

Risk-Sensitive Reinforcement Learning and Optimization for Decision-Making

Keywords (Maximum 20 words)

Reinforcement Learning; Risk-Sensitive; Decision Making; Optimization; Value-at-Risk (VaR).