Summer 2024 Doctoral Student Internships

A summer internship is an important way to gain valuable knowledge outside the college classroom. During Summer 2024, some of our STT PhD candidates served as interns with organizations and companies across the country.

“Internships are a great opportunity for students to gain hands-on experience and develop professional connections beneficial to their career,” said Dr. Yuehua Cui, Director of Graduate Programs for the Department of Statistics and Probability.  “It is a good time to test drive their career plans: going to industry or academia. More importantly, it gives students the chance to build their CV profile to impress their future employer and improve their chance of being recruited. We have had senior students who secured their job offers in the same company they did their interns right after they finished the interns. All in all, students are encouraged to find summer intern opportunities.”

Andrews Boahen: Sandia National Laboratories in Albuquerque, New Mexico
I applied through the Sustainable Research Pathways (SRP) program designed by the Sustainable Horizons Institute (SHI) to connect students and faculty working with underrepresented groups with U.S. Department of Energy (DOE) National Laboratory scientists.

I worked on "In-Situ Machine Learning (ISML) for intelligent data capture and even detection." The project mainly involved building a generalizable, unsupervised, low overhead and online (able to make predictions with minimal retention of data from prior timesteps) anomaly detection algorithm.

Romain Boutelet: National Renewable Energy Laboratory
I heard about the internship from my summer supervisor (Dr. Julie Bessac) who came to MSU for the STT Colloquium more than a year ago.

I worked with Dr. Bessac on the spatial verification of weather forecasts produced by the FourCastNet model. This work was focused on developing a metric for extreme values that takes into spatial coherences in the output of the forecast.

Arash Yunesi: FDA Center for Drug Evaluation and Research
I worked on developing a Bayesian Pipeline using R/R Studio and STAN for in-vivo in-vitro correlations in their drug studies.

Jianrui Zhang: Sarepta Therapeutics, Inc.
My job duties included estimating a multi-state disease progression model that describes a rare disease starting from an ambulatory state through other states such as non-ambulant and non-ambulant with ventilation use and building a risk prediction calculator using the estimated model. The other project was investigating the performance of super learner on estimation of causal effect in rare disease setting.