c
2
12
18
28
12
12
1a
14
e
12
16
a
a
2
2
a
20
32
1a
2a
19
Faculty
61 16
19
1
49
2
2
1a
32
34
1b
1d
18
49
5a
1d
2 29
1d
25
Joseph Daniel Romano, PhD, MPhil, MA, FAMIA
78
5a
Assistant Professor of Biostatistics and Epidemiology
7
75
Department: Biostatistics and Epidemiology
4
1
23
1f
Graduate Group Affiliations
8
a
b
1d
46
Contact information
44
4
3
3
1d
44
3600 Civic Center Blvd
2b 5E 300-A
Philadelphia, PA 19104
26
2b 5E 300-A
Philadelphia, PA 19104
2e
Office: 215-573-5571
30
a9
12
30
18
Publications
23 a
3
2
4
b
1f
23 a
13
Education:
21 9 B.S. 1f (Molecular Genetics) c
2e University of Vermont, 2014.
21 9 M.A. 23 (Biomedical Informatics) c
2c Columbia University, 2016.
21 a MPhil 23 (Biomedical Informatics) c
2c Columbia University, 2018.
21 8 PhD 23 (Biomedical Informatics) c
2c Columbia University, 2019.
c
3
27
21 9 B.S. 1f (Molecular Genetics) c
2e University of Vermont, 2014.
21 9 M.A. 23 (Biomedical Informatics) c
2c Columbia University, 2016.
21 a MPhil 23 (Biomedical Informatics) c
2c Columbia University, 2018.
21 8 PhD 23 (Biomedical Informatics) c
2c Columbia University, 2019.
c
Links
b7 Search PubMed for articles
5d Joseph D. Romano - Personal Website
6f The Romano Lab at the University of Pennsylvania
94 Joseph D. Romano - Google Scholar profile
c
5
3
3
92
Permanent linkb7 Search PubMed for articles
5d Joseph D. Romano - Personal Website
6f The Romano Lab at the University of Pennsylvania
94 Joseph D. Romano - Google Scholar profile
c
2 29
21
1e
1d
24
76
8
249 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.
e 29
27
Description of Research Expertise
126 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.8
249 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.
e 29
23
107 Kumar R, Romano JD, & Ritchie MD: Learnable Protein Representations in Computational Biology for Predicting Drug-Target Affinity. Journal of Cheminformatics 2026 Notes: (accepted; in press).
e1 Kumar R, Romano JD, & Ritchie MD: Network-based analyses of multiomics data in biomedicine. BioData Mining 18: 37, May 2025 Notes: (accepted; in-press).
ed Romano JD: Ista: An Ontology-Driven Toolkit for Biomedical Knowledge Base Assembly. Studies in Health Technology and Informatics May 2025 Notes: Accepted; in-press.
107 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.
f7 Nguyen TA & Romano JD: Uterine Leiomyoma Prediction using Geometric Deep Learning and Freely Available Electronic Health Record Data. AMIA 2025 Informatics Summit March 2025.
130 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).
147 Haredasht FN, Kim D, Romano JD, Tison G, Daneshjou R, & Chen JH: Session Introduction: AI and Machine Learning in Clinical Medicine: Generative and Interactive Systems at the Human-Machine Interface. Pacific Symposium on Biocomputing 30: 33-39, Jan 2025.
fb Kumar R, Romano JD, & Ritchie MD: CASTER-DTA: Equivariant Graph Neural Networks for Predicting Drug-Target Affinity. Briefings in Bioinformatics 2025 Notes: (Accepted; in-press).
10d Aldeia GSI, Romano JD, de Franca FO, Herman DS, & La Cava WG: Towards symbolic regression for interpretable clinical decision scores. Philosophical Transactions A 2025 Notes: (Accepted: In-press).
2c
7
1d
1f
Selected Publications
22d Rajagopalan A, Nguyen TA, Guare LA, Garao Rico AL, Venkatesh R, Caruth L, Regeneron Genetics Center, Penn Medicine BioBank, Verma A, Ritchie MD, Hall MA, Setia-Verma S, & Romano JD: DRIVE-KG: Enhancing variant-phenotype association discovery in understudied complex diseases using heterogeneous knowledge graphs. 2026 Pacific Symposium on Biocomputing 2026, Jan 2026 Notes: (Accepted; In-press. Drs. Romano and Setia-Verma are co-corresponding/co-senior authors on this publication.).107 Kumar R, Romano JD, & Ritchie MD: Learnable Protein Representations in Computational Biology for Predicting Drug-Target Affinity. Journal of Cheminformatics 2026 Notes: (accepted; in press).
e1 Kumar R, Romano JD, & Ritchie MD: Network-based analyses of multiomics data in biomedicine. BioData Mining 18: 37, May 2025 Notes: (accepted; in-press).
ed Romano JD: Ista: An Ontology-Driven Toolkit for Biomedical Knowledge Base Assembly. Studies in Health Technology and Informatics May 2025 Notes: Accepted; in-press.
107 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.
f7 Nguyen TA & Romano JD: Uterine Leiomyoma Prediction using Geometric Deep Learning and Freely Available Electronic Health Record Data. AMIA 2025 Informatics Summit March 2025.
130 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).
147 Haredasht FN, Kim D, Romano JD, Tison G, Daneshjou R, & Chen JH: Session Introduction: AI and Machine Learning in Clinical Medicine: Generative and Interactive Systems at the Human-Machine Interface. Pacific Symposium on Biocomputing 30: 33-39, Jan 2025.
fb Kumar R, Romano JD, & Ritchie MD: CASTER-DTA: Equivariant Graph Neural Networks for Predicting Drug-Target Affinity. Briefings in Bioinformatics 2025 Notes: (Accepted; in-press).
10d Aldeia GSI, Romano JD, de Franca FO, Herman DS, & La Cava WG: Towards symbolic regression for interpretable clinical decision scores. Philosophical Transactions A 2025 Notes: (Accepted: In-press).
2c
4d
22
22
7
10
a
a
2
2
19
18
10
22
10
11
c
5b © The Trustees of the University of Pennsylvania | Site best viewed a in a supported browser. | Site Design: 57 PMACS Web Team. 3 22
10