Celebrating GGEB Graduates

Please join us in our celebration as we highlight our GGEB graduates.
The profiles are sectioned by degree type:


Doctor of Philosophy

Victoria Arthur

Victoria Arthur
Mentor: Jinbo Chen, PhD
Biostatistics Program

Thesis Title: Statistical Methods for Paired Transplant Genetic Data

Mackenzie Edmondson

Mackenzie Edmondson
Mentor: Yong Chen, PhD
Biostatistics Program

Thesis Title: Privacy-Preserving Distributed Regression Algorithms for Analysis of Multi-Site Real-World Data
Mentor Comment: Mac is an exceptional leader for team sciences. He has led several exciting national multi-institutional projects that involve developing novel federated learning algorithms and applying these algorithms to answer public health and biomedical problems. He is creative, passionate, and a persistent researcher with a high level of integrity. I want to wish him all the best in his new career at Merck!

Darcy Ellis

Darcy Ellis
Mentor: Sean Hennessy, PharmD, PhD
Epidemiology Program

Thesis Title: Neurologic and Metabolic Safety of Fluoroquinolones
Mentor Comment: Darcy is always remarkably enthusiastic, and displays an amazingly positive attitude. She is completely unflappable, which will make her a valued member of any team. Best of luck in your stellar career!

Joanna Harton

Joanna Harton
Mentors: Nandita Mitra, PhD; Rebecca A. Hubbard, PhD
Biostatistics Program

Thesis Title: Methods for Comparative Effectiveness Research with Real-World Data
Research Description: I was in two labs, Nandita Mitra’s and Rebecca Hubbard’s, where we focused on causal inference and electronic health record methods, respectively.
Mentor Comment: Joanna’s enthusiasm for collaborative research and data investigations made her an asset to her study teams, and we really enjoyed working with her as she solved these science and data puzzles. She always put the scientific question first and was a highly valued collaborator. We wish her all the best in her new position at Genesis Research!

Jian Hu

Jian Hu
Mentor: Mingyao Li, PhD
Biostatistics Program

Thesis Title: Machine Learning Methods for the Analysis of Single-Cell and Spatially Resolved Transcriptomics Data
Research Description: As a researcher in biostatistics at Penn, I am driven by my passion for solving complex statistical and computational challenges in biostatistics and data science. My dissertation focuses on methodology development and data analysis in genomics, seeking to impel significant advances and improvement in life science research. Under the mentorship of my advisor Prof. Mingyao Li, I take a multidisciplinary approach that integrates methods drawn from statistics, machine learning, bioinformatics, and computational biology.
Mentor Comment: I was fortunate to have the opportunity to work with Jian in the last few years and see him grow into an independent researcher. Jian has all the characteristics of being a great scientist – he is brilliant, creative, persistent, and highly motivated. I wish him all the best in his new endeavor as an Assistant Professor at Emory University!

Nick Illenberger

Nick Illenberger
Mentor: Nandita Mitra, PhD
Biostatistics Program

Thesis Title: Causal Inference Methods for Joint Censored Cost and Effectiveness Outcomes
Mentor Comment: Nick is an incredibly talented statistical methodologist, teacher, and collaborator. His enthusiasm and passion for causal inference made him a pleasure to work with. I have no doubt that will have a huge impact in our field. I wish him all the best at NYU as a newly minted Assistant Professor of Biostatistics.

Tara Klingner

Tara Klingner
Mentor: Anne McCarthy, PhD
Epidemiology Program

Thesis Title: Identifying Demographic, Clinical and Geographic Features of Cervical Cancer Patients Presenting to a Multidisciplinary Team (MDT) Clinic in Gaborone, Botswana
Mentor Comment: Tara was an outstanding trainee, who is passionate about global oncology and health equity. She worked diligently on her dissertation, continuing to make steady progress despite the many obstacles presented by the pandemic. Her work was innovative in its use of GIS to study the burden of cervical cancer in Botswana, and her findings provide valuable insights that will help in developing interventions to reduce cervical cancer mortality, a fully preventable outcome. I have no doubt that she will continue to produce impactful science as she moves forward in her career as an epidemiologist.

Justin Lakkis

Justin Lakkis
Mentor: Mingyao Li, PhD
Biostatistics Program

Thesis Title: Scalable Machine Learning Methods for the Analysis of Single-Cell Transcriptomics and Multiomics Data
Mentor Comment: It has been my great pleasure working with Justin in the last few years. His ability to focus and finish everything in the most efficient manner will make him succeed in whatever that he does. Justin has a very bright future ahead of him and I wish him all the best for his job as a quantitative researcher at Citadel!

Rong Ma

Rong Ma
Mentor: Hongzhe Li, PhD; Tony Cai, PhD
Biostatistics Program
Saul Winegrad Award for Outstanding Dissertation

Thesis Title: Problems in High-Dimensional Statistics with Applications in Genomics, Metabolomics, and Microbiomics

Arielle Marks-Anglin

Arielle Marks-Anglin
Mentor: Yong Chen, PhD
Biostatistics Program

Thesis Title: Methods for Bias Reduction in Evidence-Based Medicine
Mentor Comment: Arielle’s research is centered around evidence-based medicine. She is a deep thinker, a persistent researcher, and a thoughtful collaborator. Her research has led to important methods for bias reductions in areas of evidence synthesis and meta-analysis, analysis of real-world data, and health disparity. I want to wish her all the best in her new chapter of career at Mathematica.

Erin Schnellinger

Erin Schnellinger
Mentor: Stephen Kimmel, MD, MSCE
Epidemiology Program

Thesis Title: Selection Bias in Lung Allocation: Influence on Lung Allocation Score and Physician Decision Making
Research and Lab Description: Erin worked with Dr. Stephen Kimmel on a variety of projects aimed at determining when and how to update clinical prediction models to ensure that their performance is maintained over time. The goal of Erin's dissertation was to improve the predictive accuracy of the Lung Allocation Score (LAS) by mitigating selection bias so that lungs are allocated to the appropriate patients in the appropriate order.

Amelia Van Pelt

Amelia Van Pelt
Mentor: Elizabeth Lowenthal, MD, MSCE
Epidemiology Program

Thesis Title: Preparing for Use of a Computerized Battery to Identify Neurocognitive Impairments Among Children and Adolescents Affected by the Human Immunodeficiency Virus in Botswana
Research and Lab Description: Under the mentorship of my advisor Liz Lowenthal, I had the privilege of convening an interdisciplinary dissertation team comprised of colleagues at Penn and a pediatric HIV clinic in Botswana. My dissertation research prepared for the use of a computerized neurocognitive battery among children affected by HIV in Botswana by examining measures of validity and engaging in pre-implementation inquiry.

Jianqiao Wang

Jianqiao Wang
Mentor: Hongzhe Li, PhD
Biostatistics Program

Thesis Title: Inference of shared genetic architecture with genome-wide association data
Research and Lab Description: In a Statistical Genetics and Genomics Laboratory, I researched statistical methods for investigating the shared genetic architecture between complex traits and disease.

Jing Zhang

Jing Zhang
Mentors: Jennifer Pinto-Martin, PhD, MPH; Maja Bucan, PhD
Epidemiology Program

Thesis Title: Exploring the Genetic Architecture of Autism Spectrum Disorder
Research and Lab Description: The Autism Spectrum Program of Excellence (ASPE) was established in 2017 to significantly improve the understanding of the genetic causes of ASD to energize the research and clinical community across the globe. I explored the genetic architecture of autism spectrum disorder (ASD) through evaluating the joint contributions of common and rare genetic variation to ASD.

Zihe Zheng

Zihe Zheng
Mentor: Harold Feldman, MD, MSCE
Epidemiology Program

Thesis Title: Subtyping Chronic Kidney Disease Patients and the Adiposity - Obesity Related Metabolomics Analyses: Findings from the Chronic Renal Insufficiency Cohort Study

Yaqian

Yaqian "Angela" Zhu
Mentors: Nandita Mitra, PhD; Jason Roy, PhD
Biostatistics Program

Thesis Title: Causal Inference Methods for Addressing Positivity Violations and Bias in Observational and Cluster-Randomized Studies
Mentor Comment: We really enjoyed working with Angela on developing novel methods for causal inference. Her enthusiasm and dedication to applications to improve human health made her an essential member of collaborative teams. We wish her all the best in her new position at Johnson & Johnson where we know she’ll have a great impact on clinical and basic science research.


Combined Degree, MD-PhD

Elle Lett

Elle Lett
Mentor: Nadia Dowshen, MD, MSHP
Biostatistics Program

Thesis Title: Centering the Multiply Marginalized: Using Intersectionality to Characterize Health Inequities Faced by Ethnoracial Minoritized Subpopulations within the Transgender Community
Mentor Comment: It has been a true honor and pleasure to be Elle’s dissertation advisor who I may have learned more from than she has from me. I’m extremely proud of her scholarship and productivity which has made a tremendous impact on our field of transgender health taking an essential intersectional approach. Her commitment to advancing policy and social justice with her scholarship, and to lifting up and mentoring others is inspiring. I look forward to watching her and her science making the world a better place for decades to come.


Master of Science

Sarah Elizabeth Hegarty

Sarah Elizabeth Hegarty
Mentor: Rui Feng, PhD
Biostatistics Program

Gary Hettinger

Gary Hettinger
Mentor: Qi Long, PhD; Ravi Parikh, MD, MPP, FACP
Biostatistics Program

Yuqing Lei

Yuqing Lei
Mentor: Yong Chen, PhD; Adam Naj, PhD
Biostatistics Program

Research Project Title: A Lossless One-Shot Federated Algorithm for Multi-Trait Analysis using Distributed Genetic Data

Sheila Pierson

Sheila Pierson
Mentor: Hongzhe Li, PhD
Biostatistics Program

Research Project Title: Predicting Treatment Response in Idiopathic Multicentric Castleman Disease (iMCD)

Jeremy Rubin

Jeremy Rubin
Mentor: Jarcy Zee, PhD; Laura Mariani, MD
Biostatistics Program
2022-23 CTL Graduate Fellow for Teaching Excellence

Bingyue Zhu

Bingyue Zhu
Mentors: Haochang Shou, PhD; Matthew Schindler, MD, PhD
Biostatistics Program