About me
“We are a sum total of what we have learned from all who have taught us, both great and small.”~ Dr. Myles munroe
Hi! I am Andrews Boahen, a Ph.D. Candidate in the department of Statistics & Probability at Michigan State University. I am privileged to explore and develop novel methods in computer model calibration, active learning and bayesian optimization under the wonderful guidance of Dr. Chih-Li Sung. My research interests span the topics of Uncertainty quantification, Bayesian inverse problems, Monte carlo inference, active learning and optimization under uncertainty with application areas from computer experiments and engineering sciences to digital twins and mission-critical physical systems.
Prior to my current position, I obtained a MSc. in Mathematical Sciences with distinction from the African Institute for Mathematical Sciences (AIMS-GHANA) and graduated with a first class in BSc. Actuarial Science from the department of Statistics & Actuarial Science at the University of Ghana. At AIMS-GHANA, my research involved establishing large deviation principles for telecommunication systems under the boolean model in the $\tau$-topology, whereas my honors project at the university of Ghana consisted in pricing European put options via genetic algorithm. Both research were conducted under the expert supervision of Prof. kwabena Doku-Amponsah
News
[Mar 2026] I am delighted to have been selected as a finalist for the Institute of Mathematical and Statistical Innovation (IMSI) Summer Graduate Student Internship program, and I will be participating in the two-week Spring Coding and Data Science Bootcamp.
[Mar 2026] I will be giving a talk at SIAM UQ’26 in the Deep Gaussian Process Surrogates Session.
[Feb 2026] I am honored to receive the Michigan State University Graduate School Travel Fellowship to present at SIAM UQ’26.
[Aug 2025] I am pleased to have been selected as the Graduate Student Instructional Leader in the Department of Statistics & Probability at Michigan State University for Fall 2025.
[Jul 2025] I will be presenting our ongoing work “Active Learning for Nonlinear Calibration” in the special session Statistical Design of Experiments at MCM 2025.
[Jun 2025] Honored to receive the JMP-P&G Student-Early Career Travel Award to present at SRC 2025.
[Jun 2025] I will be presenting our ongoing work “Active Learning for Nonlinear Calibration” in the session “Variable Selection and Active Learning” at the Spring Research Conference (SRC) 2025.
[May 2025] The paper “Large deviations for spatial telecommunication systems: The Boolean model” published in the Journal of Information and Optimization Sciences.
[Dec 2024] The technical report “In Situ Machine Learning For Intelligent Data Capture And Event Detection” appeared in CSRI Summer Proceedings 2024.
[Jun 2024] I am deeply honored to have been selected as a Summer 2024 Sustainable Research Pathways (SRP) Fellow for an internship at Sandia National Laboratories.