Joseph Daniel Romano, PhD, MPhil, MA

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Assistant Professor of Biostatistics and Epidemiology
CEET Investigator, Center of Excellence in Environmental Toxicology
Faculty member, Institute for Translational Medicine and Therapeutics
Senior Fellow, Penn Institute for Biomedical Informatics
Associate Director, Biomedical Informatics Educational Programs, Penn Institute for Biomedical Informatics
Chair, Community Affairs and Professional Development Committee, Department of Biostatistics, Epidemiology and Informatics
Department: Biostatistics and Epidemiology
Graduate Group Affiliations

Contact information
403 Blockley Hall
423 Guardian Drive
Philadelphia, PA 19104
Office: 215-573-5571
Education:
B.S. (Molecular Genetics)
University of Vermont, 2014.
M.A. (Biomedical Informatics)
Columbia University, 2016.
MPhil (Biomedical Informatics)
Columbia University, 2018.
PhD (Biomedical Informatics)
Columbia University, 2019.
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Description of Research Expertise

Joseph D. Romano is an Assistant Professor of Informatics and Pharmacology at the University of Pennsylvania. He earned a BS degree in Molecular Genetics from the University of Vermont, followed by MA, MPhil, and PhD degrees in Biomedical Informatics from Columbia University.

The Romano Lab conducts original research at the interface of clinical/translational informatics and environmental health, with particular focus on developing new artificial intelligence (AI) models that explain the biology underlying environmental risk factors and mechanisms of disease. Other areas of research interest include autoimmune-related adverse events, maternal environmental health, and natural products drug discovery. Dr. Romano leads the development of several major biomedical knowledge bases, including ComptoxAI, VenomKB, and the Alzheimer’s Knowledge Base.

Selected Publications

Donnelly HK, Ashcraft LE, Romano JD, Daniels S, and Mowery D: Using Topic Modeling to Understand Implementation Science in the Biomedical Literature. AMIA 2025 Informatics Summit March 2025.

Nguyen TA & Romano JD: Uterine Leiomyoma Prediction using Geometric Deep Learning and Freely Available Electronic Health Record Data. AMIA 2025 Informatics Summit March 2025.

Pan IT, & Romano JD: Enhancing Molecular Representation Learning through the Combination of 3D and 2D Graph Machine Learning. The 39th Annual AAAI Conference on Artificial Intelligence 39, February 2025 Notes: (accepted; in press).

Kumar R, Romano JD, & Ritchie MD: CASTER-DTA: Equivariant Graph Neural Networks for Predicting Drug-Target Affinity. bioRxiv Nov 2024 Notes: (bioRxiv preprint ahead of publication).

Li R, Romano JD, Chen Y, & Moore JH: Centralized and Federated Models for the Analysis of Clinical Data. Annual Review of Biomedical Data Science 7: 179-199, August 2024.

Albi G, Dagliati A, Vavassori C, Pisani L, Bellazzi R, Romano JD, & Colombo GI: Classification of Coronary Artery Disease Severity by Combining Clinical and Gene Expression Variables. 22nd International Conference on Artificial Intelligence in Medicine 22, July 2024.

Romano JD, Truong V, Kumar R, Venkatesan M, Graham BE, Hao Y, Matsumoto N, Li X, Wang Z, Ritchie M, Shen L, & Moore JH: The Alzheimer's Knowledge Base: A Knowledge Graph for Alzheimer Disease Research. Journal of Medical Internet Research 26: e46777, April 2024.

Paris CF, Morales E, & Romano JD: Knowledge-driven artificial intelligence enables mechanistic computational toxicology. NIEHS Environmental Health Sciences Core Centers Annual Meeting October 2023.

Hao Y, Romano JD, & Moore JH: Knowledge Graph Aids Comprehensive Explanation of Drug and Chemical Toxicity. CPT: Pharmacometrics & Systems Pharmacology. Wiley, 12(8): 1072-1079, August 2023.

Romano JD, Li H, Napolitano T, Realubit R, Karan C, Holford M, & Tatonetti NP: Discovering venom-derived drug candidates using differential gene expression. Toxins. MDPI, 15(7): 451, July 2023.

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Last updated: 11/29/2024
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