Benjamin Osafo Agyare

Benjamin Osafo Agyare

PhD Student in Statistics

University of Michigan

About Me

I am a third-year PhD student in the Statistics program at the University of Michigan, Ann Arbor. I come from Mpraeso, a beautiful small town in the Okwahu plains in the eastern region of Ghana. I obtained my MS degree in Statistics & Data Science at the University of Nevada, Reno. Before that, I received my BS in Actuarial Science from Kwame Nkrumah University of Science and Technology.

I am working under the supervision of Prof. Kerby Shedden on Generalized Expectile Estimating Equations (GEEE) applied to Longitudinal Genetics Data.

When I have some time to spare, I enjoy listening to music, spending time with my friends and family and watching soccer (I’m a staunch fan of Manchester United).

Interests
  • Statistical Modeling
  • Longitudinal Data Analysis
  • Quantile and Expectile Regression
  • Statistical Machine Learning
  • Computational Statistics
Education
  • PhD in Statistics, 2026 (Expected)

    University of Michigan

  • MS in Statistics & Data Science, 2021

    University of Nevada, Reno

  • BS in Actuarial Science, 2017

    Kwame Nkrumah University of Science & Tech.

Teaching

Graduate Student Instructor, University of Michigan, Ann Arbor

  • STATS 401 - Applied Statistical Methods II (Undergrad level Regression and ANOVA)   ||   Winter 2024 & Fall 2023
  • STATS 513 - Regression and Data Analysis (Graduate Level ~ 51 students)   ||   Winter 2023
  • STATS 501 - Applied Statistics II (GLMs, Mixed Models & Semi-Parametric Models)   ||   Winter 2023
  • STATS 306 - Introduction to Statistical Computing (∼40 students)   ||   Winter & Fall 2022
  • STATS 406 - Computational Methods in Statistics and Data Science (∼75 students)   ||   Fall 2021

Graduate Teaching Assistant, University of Nevada, Reno

  • MATH 127 - Pre-Calculus II (∼70 students)   ||   Spring 2021
  • MATH 181 - Calculus I (∼90 students)   ||   Fall 2020
  • MATH 126 - Pre-Calculus I (∼140 students)   ||   Fall 2019

Teaching Assistant, University of Ghana

  • STAT 224 - Introductory Probability II (∼60 students)   ||   Spring 2018
  • STAT 222 - Data Analysis I (∼95 students)   ||   Spring 2018
  • STAT 221 - Introductory Probability I (∼60 students)   ||   Fall 2017
  • ACTU 409 - Introduction to Actuarial Mathematics (∼40 students)   ||   Fall 2017

Working Experience

 
 
 
 
 
University of Nevada, Reno
Instructor
Jul 2021 – Aug 2021 Nevada
 
 
 
 
 
CAS Student Central
Summer Actuarial Intern
Jun 2021 – Aug 2021

Casualty Actuarial Society P&C training in:

  • Ratemaking
  • Reserving
  • Predictive Modeling
  • Data Visualization
 
 
 
 
 
Employers Insurance Group
Predictive Modeling Intern
May 2020 – Aug 2020 Nevada
  • Performed Territorial Analysis on claim frequencies using Spatially Constrained Clustering Algorithms and Generalized Additive Models to re-cluster rating territories for refining pricing models.
  • Built Loss Development Models to estimate future losses using Elastic-Net Poisson GLM.
  • Built Pure Premium models using GLMs and Zero-Inflated Models to predict future loss costs.
 
 
 
 
 
International Community School
Math Instructor
Aug 2018 – Jun 2019 Ghana
  • Taught Cambridge O and A Level Mathematics to prepare students for the IGCSE exams.
  • Rated distinction in teaching within first 3 months into the job.

Honors & Awards

Department of Statistics, University of Michigan, Ann Arbor
1st Place, Capstone Project Competition in Statistical Learning
Department of Mathematics & Statistics, University of Nevada, Reno
1st Place, Capstone Project Competition in Bayesian Statistics
Department of Mathematics & Statistics, University of Nevada, Reno
1st Place, Capstone Project Competition in Statistical Computing
Actuarial Science Students' Association, KNUST
1st Place, KNUST Actuarial Club Annual Interclass Quiz Competition
Mpraeso High School (WASSCE 2013 sitting)
Overall Best Student
Best student award for the West African Senior School Certificate Examination (Out of over 1,000 candidates at Mpraeso High School in 2013)

Software

*
DistGD

DistGD

A Distributed Optimization Package in R using Gradient Descent.

Service & Extra-curricular

 
 
 
 
 
Dept. of Statistics, Michigan
Member, Computing Committee
Sep 2023 – Present Michigan
 
 
 
 
 
Dept. of Statistics, Michigan
Member, Recruitment & Admissions Committee
Jan 2022 – Present Michigan
 
 
 
 
 
Dept. of Statistics, Michigan
Member, Curriculum Committee
Sep 2023 – Present Michigan
 
 
 
 
 
Actuarial Science Students Association, KNUST
Vice President
Aug 2015 – May 2016

Contact