2023 T35 Recipients
Meet Our 2023 Cohort!
The BDHSC would like to congratulate the 2024 T35 Recipients. Read on to learn more about the cohort and their research interests:
Katie Bond (she/her)
University of Denver
Mentor: Caroline Rudisill
I have always had a passion for human health and the impact or prevention of disease. Prior to my PhD I spent a few years working on the development of infectious disease diagnostics. In my current Biophysics program, I utilize computational methods to understand developmental biology. My research interests focus on the intersection of the two disciplines: using computational approaches such as data science or machine learning to understand infectious diseases and their impact on humans as individuals as well as population groups.
Eric Inman (he/him)
California Polytechnic State University
Mentor: Zhenlong Li
I am currently a graduate student finishing up a Master’s Degree in Computer Science at Cal Poly SLO. My academic interests include machine learning, deep learning, and their applications in healthcare. When I’m not at the computer, I enjoy baseball, reading, and good barbecue.
Giovanna Leone (she/her)
University of South Carolina
Mentor: Neset Hikmet
I am a PhD student in motor development and physical education at the University of South Carolina. I aim to use machine learning and AI to improve health-related outcomes. My other research interests include integrating holistic approaches to assess and improve physical health and performance and reduce obesity.
Giangvuthanh ("Giang") Nguyen (she/her)
Old Dominion University
Mentor: Dr. Dezhi Wu
I am a Ph.D. student in Applied Mathematics with a B.S in Applied Mathematics, a B.A. in Communication, and a minor in Chinese Studies. In 2022, I earned a Master’s degree in Applied Mathematics and kept pursuing a PhD in the same major. I have been a research assistant and teaching assistant in the Mathematics and Statistics Department at ODU since 2020. My research focuses on analyzing models of complex fluid flows described by partial differential equations in liquid crystal, and I am interested in the bioinformatics subtopic of protein structure prediction, and data science.
Yasmin Keyghobadi Nia (she/her)
Old Dominion University
Mentor: Dr. Forest Agostinelli
I’m first year PhD student in Old Dominion University. I study Applied Mathematics. I’m interested in the role Mathematics plays in data science.
Katheryn (“Kat”) Perea-Schmittle (she/her)
New Mexico Institute of Mining and Technology
Mentor: Qian Wang
I am a PhD candidate who started in the Biotechnology program in the summer of 2021. Within biology, I specialize in microbial community analysis, molecular biology, genomic and metagenomic analysis.
Areyona Wilson (she/her)
University of North Carolina
Mentor: Dr. Mufaro Kanyangarara
I graduated from UNC Charlotte with a B.S. in Biology. This past semester, I worked as a SARS-CoV-2 Surveillance Sequencer in a lab on campus in the Bioinformatics department which supported my decision to obtain a master’s in Bioinformatics. The field of study I am interested in is phage therapy, specifically in trying to make it an alternative to antibiotic treatment and decrease the knowledge gap on our information about phages.
Quotes from the Cohort
With the opportunities the T35 program offers, students can truly immerse themselves in learning about infectious diseases and data science, as well as have the chance to work on applicable research. Particularly for me, having an individually matched mentor was a great experience, as it allowed me to be guided through.
The T35 Program is a great introduction to data science applied to healthcare. The faculty are very caring, and they give you all the tools to learn and succeed.
I thoroughly enjoyed the T-35 traineeship and learned valuable machine learning techniques that I can utilize in my own research. The mentor match program and variety of classes prepared us for advanced Big Data analytical methods that will benefit our future research and help us make strides in the public health field. I would highly recommend this program if you are a motivated learner and are inclined to enhance your public health knowledge and analytical skills.
This is a very informative and helpful program to get a better understanding of Big Data Health Science. The program gives students opportunities to work on real-life problems. Mentorship is a good opportunity to develop my research paths.
The T35 Program has highly educated professors and mentors, super friendly and helpful staff. The program provides all the tools needed to carry out research.
Being able to apply mathematical techniques to such important issues in Public Health really gives the work a new meaning. I learned a lot and this internship massively influenced my career direction.
This program was a very enlightening experience! It exposes you to a side of research that always has the end result of helping those most at risk which I find very refreshing.
Welcome Party
