2022 T35 Recipients
Meet Our 2022 Cohort!
The BDHSC would like to congratulate the 2022 T35 Recipients. Read on to learn more about our recipients, their research interests, and their experience in the program:
Brendan Case (they/them)
University of Vermont
Mentored by: Dr. Melissa Nolan
Bren is a PhD student in Computer Science at the University of Vermont. They are interested in using geospatial statistics, mathematical modeling, and Bayesian inference for the study of epidemiology and ecology.
Charles Dowling II (he/him)
Claflin University
Mentored by: Dr. Susan Steck
I have always had an enthusiasm for science-based subjects, particularly those identifying with human biology. My interest in the world and the investigation of science urged me to enhance my comprehension by pursuing an M.D./Ph.D. in the field of biology. Ultimately, my professional goal is to become a physician-scientist to conduct biomedical research.
Shaelynn Frederick (she/her)
Claflin University
Mentored by: Dr. Swann Adams
I was very intrigued when I read about the T35 Research Traineeship Program that you are offering, as science has always been my forte, thus, the choice of biotechnology as my academic option. I am extremely excited when I consider the unlimited possibilities and contributions I can make to the healthcare field, as I relentlessly pursue this field as my career choice. My experience in academia made me realize my passion for the study of Cellular Immunology, finding and developing vaccines against diseases like SARs-CoV-2, cancer, HIV, as well as TB. It is my desire to further my knowledge and understanding of research and infectious diseases.
Joshua Miles (he/him)
University of Florida
Mentored by: Dr. Qian Wang
I am a 2nd-year graduate student in the Department of Statistics at the University of Florida. My current academic interests include statistical modeling, machine learning, and causal inference. In undergrad, I studied physics at the University of Missouri and worked on computer simulation of chemical systems for biophysical and carbon-capture technologies. In my free time, I enjoy reading, cooking, and managing an Airbnb rental on behalf of my family.
Hannah Shead (she/her)
Augusta University
Mentored by: Dr. Dezhi Wu
I am currently a first year graduate student working towards a Masters Degree in Biological and Computational Mathematics. In addition to math, my other interests include Computer Science and the use of artificial intelligence in cancer research.
Chelsea Spence
Clemson University
Mentored by: Dr. Benjamin Schooley
I’m a 4th year PhD student in Clemson’s industrial engineering department. My research interest is modeling the opioid overdose epidemic in the United States with a focus on how policies can reduce overdoses and deaths.
Jacob Stanley (he/him)
University of South Carolina
Mentored by: Dr. Chen Liang
I’m a PhD student that is interested in applying machine learning methods to judgement and decision-making research.
Jack Stavrakas (he/him)
University of South Carolina
Mentored by: Dr. Neset Hikmet
Jack is an Informatics PhD student at the University of South Carolina. He is interested in knowledge management, AI, and data analytics.
Quotes from the Cohort
The T35 program helps participants to learn about data science and machine learning as applied to infectious diseases. If this topic is interesting and new to you, the program provides a great introduction.
It’s useful to pick cohorts from different backgrounds, and the incoming people should know that they should read on Data Science and it’s importance before joining.
The BDHSC’s T35 program is stocked with caring faculty who are excited about the program and about working with students. The program gives many opportunities to study real-life use cases of data science in healthcare and to develop related research aims. On the side, USC and Columbia are exciting places to be, with lots of great history, food, and recreation nearby.
The usefulness and additional research experience gained from the mentor relationship.
The T35 program has a solid foundation of dedicated staff, interesting mentors, and a wide variety of practical exposures to infectious disease data science.
