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 Doctoral Candidate in the department of Statistics & Probability at Michigan State University, where I also earned my M.S. in Statistics en route to the Ph.D. 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 M.S. 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

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