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
Thesis Title: Statistical Approaches to Reducing Bias and Improving Variance Estimation
Post PhD Plans: Principal Biostatistician, Memorial Sloan Kettering Cancer Center
Thesis Title: Novel Methods for Statistical Analysis of Covariance Structures
Mentor Comment: Andrew’s research during his PhD has revolutionized the way the imaging science world thinks about multi-center studies. He is an exceptionally creative and innovative biostatistician with a brilliant mind. We wish him all the best in his future endeavors!
Thesis Title: Statistical Methods for Modeling Complex Dependency Structures in Zero-inflated Metagenomic Sequencing Data
Post PhD Plans: Assistant Professor of Biostatistics at the University of Pittsburgh
Comment: It has been my great pleasure working with Rebecca Deek these past five years. As her advisor, I am very pleased to see her growth into an independent scientist with innovative ideas to analyze complex genomic and metagenomic data. Rebecca is highly motivated and is always interested in using statistics to solve real world problems. Rebecca has a very bright future ahead of her and I wish her all the best.
Thesis Title: Real-World Bleeding with Ibrutinib in B-Cell Malignancies
Post PhD Plans: Senior Principal Research Scientist, TriNetX
Mentor Comment: It has been an absolute privilege mentoring and collaborating with Dr. Neil Dhopeshwarkar over the course of his doctoral training in epidemiology. Neil consistently demonstrated innovation, motivation, and a deep passion for generating real-world evidence to improve the health of persons with blood cancer. I have no doubt that Neil will continue to excel in his endeavors, and I wish him all the best.
Thesis Title: Statistical Methods for Developing and Evaluating Risk Prediction Models Using Integrated Electronic Health Record Data
Post PhD Plans: Assistant Research Professor, Fox Chase Cancer Center
Thesis Title: Statistical methods for the identification, evaluation, and classification of non-monotone biomarkers in case-control studies
Post PhD Plans: Biostatistician, Academies of Sciences, Radiation Effects Research
Mentor Comment: It has been our pleasure to work with Hanna Lindner on her PhD thesis research. Hanna has developed into an outstanding biostatistician. She is devoted to using her expertise to improve medical knowledge. She has taken a position as a researcher at the Radiation Effects Research Foundation in Hiroshima, Japan. She has a shining future ahead of her and we know that she will have a big positive impact in all of her research. We wish her all the best in the future.
Thesis Title: Missing Data and Measurement Error Methods for Left-Truncated Survival Data
Mentor Comment: It has been a wonderful experience working with Hayley Locke. She is highly motivated, creative, and thoughtful. She has amazing skills in statistical theory and applications. She has made a significant impact on statistical method development for missing data and measurement error problems for left-truncated survival data. I am so proud of Hayley! Congratulations!
Thesis Title: Preserving Patient Privacy in Modeling Multi-Category Outcomes across Real-World Data Sources
Post PhD Plans: Principal Statistician, GSK
Mentor Comment: It has been my great pleasure working with Dr. Ken Locke over the past three years. Ken has all of the characteristics of both an outstanding academic and public health expert. He is extremely self-driven, hard-working, and persistent. He is incredibly sharp and can communicate complex technical ideas in simple terms. Ken is an excellent scientist, innovative, highly motivated and passionate with an intense devotion to rigorous methods and applications for clinical evidence generation. He has a bright future ahead of him and I wish him all the best.
Thesis Title: Statistical method development for analyzing neuroimaging data
Post PhD Plans: Biostatistician, Pfizer
Mentor Comment: Carolyn’s dissertation work on the analysis of biomedical imaging has made seminal contributions in multiple fields. She is a critical thinker who understands the clinical context and biology to ensure that the statistical methods she develops are highly impactful. We wish her all the best in her future endeavors!
Thesis Title: Statistical Methods for Neural Networks
Post PhD Plans: Mathematical Statistician, FDA
Mentor Comment: It has been an immense privilege to work alongside Francesca for the past four years. As an outstanding PhD graduate, she has consistently demonstrated excellence in her methodological research and interdisciplinary collaboration. Francesca's exceptional aptitude for mastering advanced statistical concepts, combined with her ability to effectively communicate these ideas to researchers across diverse disciplines, sets her apart. Francesca will be sorely missed, but her future is bright and I wish her all the best!
Thesis Title: Epidemiology and control of canine rabies in heterogeneous population
Post PhD Plans: Vet School
Mentor Comment: It has been my great pleasure working with Brinkley Raynor since she joined my lab in 2017. Brinkley is an exceptional epidemiologist and will be an outstanding public health expert. Her passion for understanding zoonotic diseases and improving disease control programs is inspiring. She has a very bright future ahead of her and I wholeheartedly wish her all the best.
Thesis Title: Statistical and Machine Learning Methods for Neuroimaging and Neurocognitive Data
Post PhD Plans: Data Scientist, Regeneron
Mentor Comment: Danni’s dissertation research focuses on several areas related to neuroscience and imaging statistics, and her work is truly remarkable. She is an outstanding problem solver, innovator, and an expert communicator who excels in all aspects of her work. We wish her all the best for her future career!
Thesis Title: Statistical Methods for Extracting and Comparing Patterns in Multimodal Neuroimaging Studies
Mentor Comment: Sarah’s contributions to multimodal image analysis over the past five years have been incredibly impactful. She is an exceptional scientist with all the qualities of an outstanding academic. We are confident that she will continue to make a significant impact in her field, and we wish her all the best in her future endeavors!
Thesis Title: Capturing complex patterns of association in genetic data: a rule-based machine learning approach to survival analysis
Post PhD Plans: Partnership and Strategy at Optum Clinicogenomics
Mentor Comment: It has been my great pleasure working with Alexa Woodward these past several years. She brought new research ideas to the lab and was able to work at the interface of epidemiology, genomics, and artificial intelligence to advance our understanding of disease heterogeneity. I am confident her multidisciplinary skills and knowledge will serve her well throughout her career.
Thesis Title: Transfer Learning in Classification and Regression with Summary Statistics
Post PhD Plans: Senior Biostatistician, Vertex Pharmaceuticals
Mentor Comment: I have truly enjoyed working with Haotian Zheng on developing machine learning methods for analysis of large-scale genomics, proteomics data and lipidomics data. Haotian is always passionate about applying the modern statistical learning methods to improve genomics-based risk prediction and classification. I wish him all the best in his future endeavors.
Combined Degree, MD-PhD
Thesis Title: Missingness and Equity of Clinical Model Predictive Performance: Considering the Social Construction of EHR Data
Post PhD Plans: Med School
Mentor Comment: I cannot be more proud to have been able to work with Dr. Stephanie Teeple for the past several years. To be able to mentor her and watch her grow has been a unique privilege. Dr. Teeple was brilliant long before we met, and she has now added maturity, composure, and well-earned confidence to her natural intelligence. In doing so, she is remarkably well-positioned to become a leading academic authority working to improve health for all, and particularly for those who face structural barriers to its attainment and sustenance. I greatly look forward to watching her career continue to blossom, and to witnessing the impact she will have on patients, the public, and her own mentees.
Master of Science
Research Project Title: The Probability of Causation: Evaluating Respiratory Health and Indoor Air Pollution
Post MS Plans: Pursuing PhD
Mentor Comment: It has been a pleasure working with Dane Isenberg these past two years while he worked on his MS thesis. Dane is a deep and innovative thinker whose enthusiasm for causal inference is infectious. His methodological developments are always rigorously thought out and he has a real passion for applying complex causal approaches to real world public health problems. I very much look forward to continuing to work with him as he begins his PhD dissertation work here at Penn.
Research Project Title: Unbiased Estimation of Disease Probabilities Using Machine-learning Algorithms on EHR Data
Research Project Title: Comparisons of Methods for Multi-sample Single-Cell RNA-seq Data of Ulcerative Colitis Patients and Healthy Controls
Post MS Plans: Pursuing PhD
Mentor Comment: It has been my great pleasure working with Ruolan Li in the last two years. As a master student, Ruolan has done an outstanding job in generating useful preliminary results for analysis of population-level single cell genomics data. I wish you good luck in your PhD study. I am sure you’ll achieve everything you work towards. Best wishes and good luck!
Research Project Title: Feature Selection and Prediction to Identify Multilevel Predictors of Forced Sex among South African Adolescents
Post MS Plans:
Mentor Comment: Working with Junning Liang has been a great experience. Junning demonstrated great determination in tackling the new areas of feature selection and prediction in multilevel data. With her curiosity, insightfulness, and compassion Junning will be an asset to any team she joins.
Research Project Title: Automated Methods for Segmentation of Multiple Sclerosis Brain Lesions using Spatial Information
Post MS Plans: Pursuing PhD
Mentor Comment: It has been my great pleasure to work with Ashika Mani over the last year. Ashika is creative scientist with a passion for working on brain imaging methods in multiple sclerosis. Ashika has a very bright future ahead and I wish her all the best.
Research Project Title: Evaluation Of Creatinine-based GFR Estimating Equations in Glomerular Disease
Post MS Plans: Biostatistician, CHOP
Mentor Comment: Working with Antara this past year has been a rewarding and enjoyable experience. She is a proactive and independent learner who has demonstrated great fortitude and diligence in her work. Despite several challenges, including holding a full-time job while completing her master’s degree requirements, she produced excellent and important research in kidney disease. I look forward to her continued success in the future.
Research Project Title: Evaluating a facility-profiling metric based on survival probability: Application to U.S. transplant centers
Post MS Plans: Data Scientist, Genentech
Mentor Comment: It has been my great pleasure to work with Amelia Tran these past two years. Amelia has done an outstanding job on a wide variety of Biostatistical analyses, through which she demonstrated all the qualities of a future star in the field of biostatistics: thoughfulness, preserverance, and a desire to understand the science well beyond the analysis. I thank Amelia for her dedicated effort and wish her only the best in her career.
Research Project Title: Clustering for Defining Pediatric Acute Respiratory Distress Syndrome (ARDS) Endotypes
Post MS Plans:
Mentor Comment: It has been an absolute pleasure working with Kebin over the past year. As a student, Kebin has consistently showed persistence and attentiveness to our project. Kebin also demonstrated exceptional resilience in the face of challenges and stress during their job search and research endeavors. I have no doubt that Kebin will continue to overcome any obstacles in her life and achieve great things in the future. Keep up the excellent work, Kebin!