Path to public health: Vice Dean Jeanine Buchanich
Jeanine Buchanich, PhD, MPH, MEd, started her journey as an undergraduate at the University of Pittsburgh, where she traversed a winding path to her new role as the vice dean of Pitt Public Health.
Making a Difference with Data
With an undergraduate degree in neuroscience, Kayleigh Adamson (BIOST ‘20) has always been fascinated by the intersection of health research and statistics, but it wasn't until she came to Pitt that she developed her true passion for biostatistics. It was a good fit with her heavy science background.
Hu Publishes in Nature Communications
PhD student Haoran Hu has made a significant contribution to the field of single-cell research with the publication of a paper titled "A unified model-based framework for doublet or multiplet detection in single-cell multiomics data" in the top research journal Nature Communications.
Innovating biostatistics education at Pitt
Assistant Professor Haley Grant, PhD, has been a faculty member in the Department of Biostatistics and Health Data Science since 2023.
Department renamed at Pitt’s School of Public Health
The Department of Biostatistics will become the Department of Biostatistics and Health Data Science to reflect the increasing growth of complex data and biotechnology now being employed in the field of public health.
Runjia Li, PhD student, wins scholarship
Runjia Li (PhD '24) has been selected as one of the prestigious American Statistical Association's Biopharmaceutical Section Scholarship Award winners.
The Biostatistics Department welcomes three new faculty members
Welcoming Pedro Baldoni, Soumik Purkayastha and Qiong Wu.
Wang treads path from student to faculty member
Xinjun Wang (PhD, BIOST ’22) found his groove developing new statistical models for single-cell muti-omics data during graduate studies at the University of Pittsburgh.
Advocates listen and learn, celebrate and plan at first Environmental Justice Summit
May 9-11 was Pittsburgh’s first Environmental Justice Summit with the theme Reflections, Connections, and Collaborative Action.
Biostatistics alum reflects on his journey
Craig Parzynski (MS ’11) discovered a love for problem solving at the University of Pittsburgh. He earned his master’s degree in biostatistics and gained a solid foundation for a career in medical research. However, his path to biostatistics was not straightforward.
Ma and Tang propose smart data augmentation to address imbalances in data
Department of Biostatistics Chair Yan Ma is the corresponding author on “Smart data augmentation: One equation is all you need," recently published in Statistical Analysis and Data Mining: The ASA Data Science Journal. The paper’s co-authors include Lu Tang, vice chair for education in the Department of Biostatistics.
Cai publishes in Communications Biology
PhD student Manqi Cai’s article “scMD facilitates cell type deconvolution using single-cell DNA methylation references” was published in the Communications Biology Journal.
Tseng publishes in Translational Psychiatry and Computational Biology
Dr. George Tseng has two new recently published papers. The first is titled "Glucose dysregulation in antipsychotic-naïve first episode psychosis: in silico exploration of gene expression signatures." This study investigates the link between first-episode psychosis patients not yet treated with antipsychotics and early metabolic issues like insulin resistance.
Bo wins ASA HPSS Student Paper Award
Professor Ying Ding's student Na Bo has been selected as one of the Health Policy Statistics Section Student Paper Competition winners. She will travel to the 2024 Joint Statistical Meetings in Portland, Oregon this summer to present her work titled "A meta-learner-based framework to analyze treatment heterogeneity in survival outcomes: application to pediatric asthma care under COVID-19 disruption".
Zhang wins ASA Bayesian Statistical Science Award
PhD student Gehui Zhang has been selected as the winner of the 2024 SBSS student paper competition. Zhang will travel to the 2024 Joint Statistical Meetings in Portland, Oregon to present research titled Stochastic Volatility with Informative Missingness. The paper pioneer's statistical methodology for stochastic volatility models with non-random missing data. Introducing a novel imputation method based on Tukey's representation, combined with conditional particle filtering, the approach overcomes limitations in existing methods.