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Joseph Romano, PhD, MPhil, MA is an Assistant Professor of Informatics in the Department of Biostatistics, Epidemiology and Informatics, Senior Fellow in the Institute for Biomedical Informatics (IBI) and an investigator in the Center of Excellence in Environmental Toxicology (CEET).

Before joining Harvard University as an Assistant Professor of Biostatistics, Rui Duan, PhD, completed her PhD in Biostatistics at the University of Pennsylvania.

Edward Kennedy, PhD is a Penn alum through and through—prior to completing his PhD in Biostatistics in 2016, he earned his BA in Mathematics (2007) and MA in Statistics (2014) from the University.

Dr. Shen is a Professor and the Deputy Director of the Informatics Division in the Department of Biostatistics, Epidemiology and Informatics at the Perelman School of Medicine in the University […]

Dr. Tsui is an engineer, computer scientist, and biomedical informatician. His research focuses on three areas: 1) Developing methods using AI, machine learning, natural language processing, data science, data engineering, […]

Dr. Urbanowicz’s research focuses on the development, evaluation, and application of machine learning (ML) and artificial intelligence (AI) methods for the analysis of biomedical and clinical data. This work is […]

Dr. Ritchie is an expert in translational bioinformatics, with a focus on developing, applying, and disseminating algorithms, methods, and tools integrating electronic health records (EHR) with genomics. The mission of […]

Joseph D. Romano is an Assistant Professor of Informatics and Pharmacology in the University of Pennsylvania’s Perelman School of Medicine. He joined the faculty in 2023 after completing postdoctoral and […]

Dr. Long’s research purposefully includes novel statistical and machine learning research and impactful biomedical research, each of which reinforces the other. Its thrust is to develop statistical and machine learning […]

Dr. Danielle Mowery is a collaborative investigator that develops natural language processing (NLP) solutions for processing clinical texts – i.e., clinical notes, chatbots, and transcribed texts – to support clinical […]

Dr. Rebecca Hubbard’s lab focuses on the development, application, and evaluation of statistical methods for the analysis of real-world data (RWD) such as electronic health records (EHR) and medical claims […]

Kevin B. Johnson, MD, MS is the David L. Cohen University Professor of Biomedical Informatics, Computer and Information Science, Pediatrics, and Science Communication at the University of Pennsylvania, Vice President […]

Dr. Dokyoon Kim is an Associate Professor of Informatics and serves as the Director of the Center for AI-Driven Translational Informatics (CATI). He also holds the role of Associate Director […]

John H. Holmes, PhD, is Professor of Medical Informatics in Epidemiology at the University of Pennsylvania Perelman School of Medicine. He is the Associate Director for Medical Informatics at the […]

Dr. Yong Chen is Professor of Biostatistics at Department of Biostatistics, Epidemiology, and Informatics (DBEI), and a Senior Scholar at Center for Clinical Epidemiology & Biostatistics (CCEB) at the University […]

Dr. Demiris is the Mary Alice Bennett University Professor in the School of Nursing and Perelman School of Medicine, and Associate Dean for Research and Innovation in the School of […]

Dr. Mingyao Li's article in Nature Methods discusses how artificial intelligence is revolutionizing spatial omics, enhancing integration of diverse data and accelerating biological discoveries for improved health outcomes in biomedical research.

Kevin B. Johnson, MD, MS was awarded the NIH Director’s Pioneer Award under the “High-Risk, High-Reward Research” program funded by the National Institutes of Health Common Fund. Established in 2004, the NIH […]

A new research initiative “The Center for AI-Driven Translational Informatics (CATI) ” supported by the Penn Institute for Biomedical Informatics (IBI), the Department of Biostatistics, Epidemiology and Informatics (DBEI), and […]

Dr. Qi Long received a new U01 grant from NCI, entitled “Robust Privacy Preserving Distributed Analysis Platform for Cancer Research: Addressing Data Bias and Disparities.” This grant enables Dr. Long’s group […]

Dr. Qi Long’s lab in the CCDS partnered with Dr. Mayur Naik’s lab in Computer and Information Science to form a team, Team Penn, to participate in the NIH Long […]

Penn Medicine researchers will help lead the development of an algorithm to flag patients at risk of rare disease thanks to a $4.7 million NIH grant. This 4-year U01 will involve 10 […]

Our new paper “Assessing Fairness in the Presence of Missing Data” has been accepted for publication at NeurIPS 2021, a leading machine learning /artificial intelligence conference. Learn More

Our recent PNAS paper introduced the Layer-Peeled Model in deep learning that can: 1) predict a hitherto unknown phenomenon termed “Minority Collapse” in imbalanced training; and 2) explain neural collapse […]

A key factor in designing randomized clinical trials is the sample size required to achieve a particular level of power to detect the benefit of a treatment. Sample size calculations […]

A good clinician consultant should be able to explain why they arrived at a particular recommendation, and explainable artificial intelligence should also be possible, writes Jason Moore, PhD ”   […]

Jason Moore, PhD, shares his understanding of his field: Data science, at its heart, is about solving a problem with whatever tools you have at your disposal. Read the article […]

Artificial intelligence and machine learning can help us fight COVID-19, Jason Moore, PhD, told The Washington Post. But if you study only populations that are primarily Caucasian, that may not […]

A general approach to evaluating the bias of 2‐stage instrumental variable estimators Fei Wan, Dylan Small, and Nandita Mitra Unmeasured confounding is a common concern when researchers attempt to estimate […]