Grad Student Summer Internship News 2023
Summer 2023 PhD Student Internships
A summer internship is an important way to gain valuable knowledge outside the college classroom. During Summer 2023, 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.”
Sikta Dasadhikari: Moderna Research and Development Statistics team
My responsibilities involved analyzing mRNA data and creating statistical models and workflows for various applications. I found the work environment to be enjoyable and informative, and I gained valuable insights about research in industry.
Pengfei He: Okinawa Institute of Science and Technology(OIST) Machine Learning and Data Science
There wasn’t a specific project there, and I could do research on my interested topics and collaborate with researchers there to develop some projects. I mainly worked on backdoor attacks.
Nian Liu: National Institute of Standards and Technology through the NSF MSGI program (National Science Foundation (NSF) Mathematical Sciences Graduate Internship (MSGI)
Projects I worked on were about edge detection of OCT images and hyperspectral image processing.
Sumegha Premchandar: Wells Fargo in their Quantitative Analytics Program.
I worked on feature engineering and development of statistical machine learning models with big data to predict consumer response to marketing incentives for CD products.
Ruxin Shi: Moderna – Biostatistics Department
I collaborated with my manager on the topic "On Stratified Confidence Interval Construction for Binary Endpoint in Super-Superiority Vaccine Efficacy Trials". Together, we proposed a novel method to handle stratified vaccine efficacy trials. We conducted extensive simulations to compare the performance of various methods. Additionally, we developed an R package related to our work, which facilitates both data analysis and experimental design.
Jianrui Zhang: Sarepta Therapeutics, Inc: Assessment of statistical analysis methods of the Loss
of Ambulation (LOA) data in Duchenne muscular dystrophy (DMD) in real world setting.
My job duties included the following: develop understanding of real data on key efficacy measurements, perform analysis of repeated measures data and time to event data; perform statistical simulations in R to assess different statistical methods/models and their performance on a variety of endpoints; and ad-hoc and exploratory statistical analyses, as needed.