(May 14, 2026) — History was made during the 2026 Graduation Celebration for the Milken Institute School of Public Health (Milken Institute SPH). Amid a sea of new graduates, the Department of Biostatistics and Bioinformatics reached a monumental milestone. For the very first time in the department's history, a cohort of brilliant scholars walked across the stage to receive their Doctor of Philosophy (PhD) degrees.
Department Chair Scott Evans called this trailblazing group the department’s “George Washingtons” — a nod to their role as the program’s founding graduates and the high standard they have set for future cohorts.
These individuals have spent years at the intersection of biostatistics, bioinformatics, mathematics, computational biology, and artificial intelligence, answering some of the most complex public health questions, turning data into knowledge, and developing robust and efficient approaches to the design and analyses of public health studies. Let’s celebrate the history-making cohort from the Health and Biomedical Data Science program, their dedicated faculty advisors, and the revolutionary research that earned them their doctoral hoods:
🎓 Dr. Mahdi Baghbanzadeh
- Dissertation Title: Machine Learning Approaches For Genomic Sequence Analysis: From Variant-based Prediction To Genomic Language Models
- The Impact: Dr. Baghbanzadeh’s work leverages advanced AI and machine learning to decode genomic sequences, transitioning standard data analysis into complex "genomic language models" that can help predict genomic variants and accelerate personalized medicine.
- Next Step: AI Engineer, HHMI Janelia Research Campus
🎓 Dr. Ranojoy Chatterjee
- Dissertation Title: Advanced Computational Methods for Single Cell and Spatial Transcriptomics Analysis: From Automated Pipelines to Spatial Deconvolution
- The Impact: Dr. Chatterjee’s research addresses a crucial frontier in molecular biology—computational pipelines for cell dynamics and spatial transcriptomics in single-cell resolution. His work builds automated frameworks to help scientists see exactly where and how genes are expressed within cellular structures, bridging data science and cellular precision.
- Next Step: Research Fellow, Children’s National Hospital Research & Innovation Campus
🎓 Dr. Yijie He
- Dissertation Title: Design and Analysis of Clinical Trials with the Desirability of Outcome Ranking Methodology
- The Impact: The Desirability of Outcome Ranking (DOOR) methodology is a paradigm for the design, analysis, monitoring, and interpretation of clinical trials, rooted in patient-centric benefit-risk evaluation. Dr. He’s research bridges theory and practice by establishing a rigorous and reliable statistical analysis framework that enables the seamless implementation of DOOR in complex clinical research settings. He developed and translated this framework into publicly available statistical software to enable seamless adoption by the broader research community.
- Next Step: Fellow, Endpoint Strategy Selection and Statistical Analysis Plan for Non-Malignant Hematologic Disease, Food and Drug Administration
🎓 Dr. Erika Hubbard
- Dissertation Title: Contemporary Use of Transcriptomics to Facilitate Precision Medicine in Systemic Lupus Erythematosus (SLE)
- The Impact: SLE is notoriously difficult to treat due to its variable nature. Dr. Hubbard's pioneering work combines transcriptomics with clinical data to open new doors for precision medicine, giving clinicians data-driven pathways to tailor treatments specifically to the biological profile of individual lupus patients.
- Next Step: Computational Scientist, The Translational Genomics Institute (Tgen)
🎓 Dr. Shiyu (Richard) Shu
- Dissertation Title: Recent Advances in Desirability of Outcome Ranking (DOOR) Analyses
- The Impact: In clinical trials, balancing the benefits of a treatment against its potential adverse side effects is highly complex. Dr. Shu’s research advances Desirability of Outcome Ranking (DOOR) analyses—an innovative biostatistical framework that ranks comprehensive patient outcomes, making clinical data interpretation more precise, patient-centered, and actionable.
- Next Step: Statistical Methodology Data Scientist, Genentech
🎓 Dr. Xinyang Zhang
- Dissertation Title: Computational Discovery and Characterization of Microbial Functions in Health and Disease
- The Impact: The human microbiome plays an integral role in our overall health. Dr. Zhang developed and utilized cutting-edge computational discovery tools to characterize microbial functions, mapping out exactly how microscopic communities keep us healthy or contribute to disease, providing vital insights for future therapeutics.
- Next Step: Research Fellow, Artificial Intelligences-Enabled Precision in Liver Pathology Lab, Mayo Clinic
Forging a New Era of Public Health Data
By mastering biostatistical methodologies and applications, algorithms and computational frameworks that interpret today's massive biological data streams, these five trailblazers have perfectly embodied the Milken Institute SPH mission: translating rigorous science into direct, meaningful public health action.
They came to the university as candidates, but they leave as the foundational architecture of the department's doctoral history. Congratulations to the inaugural class of Health Data Science PhD “George Washingtons.” As pioneers of the program, these graduates are poised to help shape the future of public health and biomedical research through scientific rigor and data-driven leadership.