Meet Our New PhD Students!
We’ll be featuring mini-profiles of our new PhD students over the next few weeks. We look forward to welcoming them into our community!
Shanta Murthy
Hi there! My name is Shanta Murthy. I am originally from the Maryland/DC area and have lived in Atlanta for the past two years. I obtained my Bachelor of Science in Mathematics in 2019 and a Master of Science in Systems Medicine in 2022, both from Georgetown University. During the interim, I worked as a post- baccalaureate researcher at the National Institutes of Dental and Craniofacial Research (NIDCR) at The National Institutes of Health (NIH). Since completing my Master’s, I have been working as a bioinformatics analyst at Emory University.
My research experiences have strengthened my passion for understanding personalized disease signatures. With the advent of new big data approaches, I recognize the importance of employing data science practices that ensure reproducibility. I am excited to train in statistical genetics, computational biology, and additional areas in biostatistics to improve methodology related to parsing high-dimensional data and multi-omics integration.
During my post-baccalaureate at NIH, I analyzed and integrated multiple -omics datasets to clarify the gene regulatory networks driving T cell differentiation. This experience offered me insight into the utility of different datasets, including transcriptomics and chromatin accessibility, in studying gene programs. I also recognized the importance of quality assessment and parameter selection when analyzing high- dimensional data.
As a Master’s student in Systems Medicine, I studied multiple topics pertaining to bioinformatics analyses of human data, including biostatistics, epigenetics, microbiomics, and genomics. In my research project, I applied this knowledge to study potential pathogenic variants in African American patients with aggressive prostate cancer. I probed the functions of these variants from whole-genome sequencing analysis by conducting experiments to determine aberrant RNA and protein levels of these targets. This experience gave me a lens into combining computational and wet-lab approaches.
In my current role as a bioinformatics analyst at Emory University, I am involved in multiple analysis projects, primarily investigating single-cell and spatial transcriptomic signatures in patients with relapsing or remitting Crohn’s disease. I have enjoyed integrating these datasets, and in secondary projects, I have also assessed links between DNA methylation signatures and environmental factors, as well as investigated rare variants and polygenic risk scores for patients with childhood-onset systemic lupus erythematosus (cSLE).
Outside of work, you’ll likely find me spending time in nature, dancing, or doing yoga. I love immersing myself in new experiences and look forward to exploring Boston and meeting people from diverse backgrounds. I can’t wait to meet everyone and begin this new chapter!
Pascale Nevins
Hi! My name is Pascale Nevins and I’m from Ottawa, Canada. I chose to stay in my hometown to do a BSc with a major in biochemistry and minor in statistics at the University of Ottawa. I discovered the field of biostatistics when I was looking for the intersection of what I enjoyed studying the most (math) and the applied subjects I was familiar with (the life sciences). In 2022, I began an MSc in biostatistics at the University of Western Ontario.
My introduction to applied biostatistical research was through an undergraduate research program, during which I completed a review of recruitment outcomes in pragmatic RCTs.
I was subsequently hired by my supervisor as a research assistant and have since contributed to several projects with diverse teams of researchers– primarily reviews of RCTs, but also working with survey data. In my time in this role, I’ve developed a keen interest in the design, analysis, and reporting of randomized controlled trials, especially for complex designs such as the stepped-wedge.
Knowing the world of biostatistics is much larger than RCTs and that I wanted to gain experience in methods development, I decided to pursue an MSc with a different focus. My master’s thesis considers extensions to the structural topic model (a machine learning method with roots in Bayesian hierarchical models) for the analysis of focus group transcripts. The methods that I worked on and their application to a pan-Canadian study on homelessness have opened my eyes to the breadth of available data leverageable for health and social research. I see potential for integrating my newfound interests in text as data, machine learning, and Bayesian statistics with my evergreen interest in RCTs, but I also hope I can explore new topics during my PhD.
Outside of my academic pursuits, I’m an avid language learner: I speak French and German, and I am teaching myself Japanese. I love to travel, so I look forward to living in Boston with its much larger international airport! I also like to go on hikes, experiment with cooking and baking, and read novels.
