Mentors & Instructors

Liz Pirraglia, PhD

In April 2025, Liz Pirraglia successfully defended her PhD in Biostatistics at the NYU Vilcek Institute of Graduate Biomedical Sciences. Her dissertation, titled “Statistical Approaches to Heterogeneity in Alzheimer’s Disease and Related Dementias,” focused on advancing methods to better understand variations in brain neuropathology and dementia risk factors. Prior to beginning her doctoral studies, she worked as a Research Assistant in the NYU Division of Biostatistics and at the Center for Brain Health, part of the NYU Alzheimer’s Disease Research Center. She looks forward to continuing her work as a Research Scientist at NYU Langone Health, where she will contribute to projects investigating cognitive and brain aging, including research involving the World Trade Center Survivor’s Cohort.

Liz will support Dr. Shao for Summer 2025.  

 Kofi Agyabeng

Kofi Agyabeng is a doctoral student in Biostatistics at the New York University School of Global Health. He holds a Bachelor of Arts degree in Economics and Statistics (Combined Major) from the University of Ghana, a Master of Statistics and Data Science (Biometric track) from KU Leuven, Belgium, and a Master of Public Health (Epidemiology track) from the University of Ghana. Kofi has worked with several public and private institutions as a Biostatistician, Data Analyst, and Data Manager. Kofi has an interest in modelling maternal and child health-related issues.

Kofi will suport Dr. Dahlen for Summer 2025. 

 Cindy Patippe, MS

Cindy Patippe is a PhD student in biostatistics with a keen interest in utilizing public health data to analyze and address health disparities. She holds a BS in Biology from Howard University and an MS in Biostatistics from New York Medical College. Her research focuses on developing statistical models to understand the underlying factors between discrimination and racial inequities. By leveraging large-scale public health datasets, she aims to identify and mitigate the systemic issues that lead to unequal health outcomes, ultimately contributing to more equitable healthcare solutions.

Cindy will support Dr. Odemugwu for Summer 2025.  

Danning Tian

Danning Tian is a PhD student in Social Behavioral Sciences at the School of Global Public Health, New York University. Danning holds a Bachelor’s degree in Biomedical Engineering with a minor in Architecture from the University of Minnesota, Twin Cities. Building on this foundation, Danning pursued a Master of Science in Biostatistics at NYU.

Danning's research spans multiple domains, with a significant focus on cancer screening disparities among HIV-positive individuals and analyzing tobacco use patterns and their health impacts. Danning also has a keen research interest in the health challenges faced by marginalized communities. Skilled in data analysis using advanced machine learning strategies, Danning has effectively utilized these techniques across various research projects to uncover complex patterns and trends in large datasets. Moreover, Danning's commitment to public health initiatives extends across the globe, from leading response efforts to a syphilis outbreak in Japan to spearheading tobacco control projects that influenced public health policies in China.

Danning will support Dr. Spitzer for Summer 2025.  

Adrian Harris, MS

Adrian earned his Bachelor's of Business Administration in Statistics and Quantitative Modeling from Baruch College and a Masters of Applied Statistics in Social Research from NYU. He is interested in topics such as Causal inference and AI/ML Ethics. In his current role he supports NYU AI Hub at McSilver as a Research Data Scientist. Adrian's work consists of conducting machine learning and statistical analyses for research topics that aim to reduce suicide risk along with the demographic disparities.

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Adrian will teach the Introduction to Biostatistics course for Summer 2025.   

 Zoé Haskill-Craig, B.Sc., B.A.

Zoé's research interests include equity and environmental exposure, particularly focused on air pollution and heat. Her thesis work deals with challenges in working with particulate matter exposure: assessing equity in data collection, incorporating complex survey design in models for the distribution of extreme values, and  modifying environmental epi models to include considerations of measurement error. Her areas of statistical expertise include hierarchical/mixed-effects models, spatial statistics, extreme value analysis, bayesian statistics, and machine learning. She previously received a B.Sc. in physics and a B.A. in social and political history from Carnegie Mellon University. 

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Zoé will teach the Introduction to Statistical Computing course for Summer 2025. 

 Lingzi Luo, MSW/MPH

Lingzi Luo is an intervention scientist and a doctoral student in the Social and Behavioral Sciences concentration. Her research interests are broadly in leveraging intervention optimization and implementation science methods to improve routine social and health services for vulnerable populations, especially those with chronic illnesses or mental health challenges. The ultimate goal of her research is to build learning service systems that are person-centered, efficient, and equitable. She had practice exposure in diverse settings such as community mental health centers, psychiatric inpatient units, non-profit organizations, local governments, and the World Health Organization headquarters. Prior to joining NYU, she worked for several years at Washington University School of Medicine on a national implementation science consortium to improve care for patients with sickle cell disease. Lingzi holds a B.S. in Psychology from Wuhan University and a dual-degree Master's in Social Work and Master's in Public Health with an individualized concentration in Integrated Health for Disadvantaged Populations from Washington University in St. Louis.

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Lingzi will teach the Epidemiology course for Summer 2025. 

Social Mentor will be announced soon!