Jacob I. Monroe
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Assistant Professor - Engineering
Also affiliated: National Institute of Standards and Technology (2020–2023); University of California, Santa Barbara (2016–2022); University of Victoria (2022–2024); Integrated Systems Solutions (United States) (2025); University of Virginia (2013–2014); Virginia Tech (2012)
Faculty Researcher
Research Areas
Biomedical Subjects
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Biography and Research Information
OverviewAI-generated summary
Jacob I. Monroe, an Assistant Professor at the University of Arkansas at Fayetteville, directs research focused on molecular dynamics simulations, thermodynamics, and the application of machine learning to complex scientific problems. His work investigates the fundamental principles governing molecular behavior and their implications across various scientific domains.
Monroe's research has been supported by federal grants, including a National Science Foundation CAREER award totaling $563,155 for his project on uncertainty-aware thermodynamic equations of state derived from molecular simulation and experimental data. His recent publications explore topics such as interfacial hydration in mesoporous organosilicas, the development of efficient Monte Carlo moves using variational autoencoders, and the quantification of polypeptoid conformational landscapes. He also contributes to research on energy systems, including the integration of renewable energy sources and the use of agent-based modeling for evaluating electricity markets and enhancing power outage resilience.
His scholarship metrics include an h-index of 14, with 39 publications and over 1,000 citations. Monroe collaborates with several researchers at the University of Arkansas at Fayetteville, including Ranil Wickramasinghe, Chidambaram Thamaraiselvan, Xianghong Qian, and Edgar C. Clausen. He maintains an active laboratory website to disseminate his research activities.
Metrics
- h-index: 14
- Publications: 39
- Citations: 1,028
Selected Publications
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Techno‐Economic Analysis of Membrane‐Based Purification Platforms for AAV Vector Production (2025)
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Reweighting configurations generated by transferable, machine learned models for protein sidechain backmapping (2025)
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JCTC Early Career Board Selects (2024)
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Grand challenges in membrane transport, modeling and simulation (2024)
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Classification and authentication of materials using prompt gamma ray activation analysis (2023)
Federal Grants 1 $563,155 total
Collaboration Network
Top Collaborators
- Grand challenges in membrane transport, modeling and simulation
- Techno‐Economic Analysis of Membrane‐Based Purification Platforms for AAV Vector Production
- Classification and authentication of materials using prompt gamma ray activation analysis
- Classification and authentication of materials using prompt gamma ray activation analysis
- Classification and authentication of materials using prompt gamma ray activation analysis
- Classification and authentication of materials using prompt gamma ray activation analysis
- Classification and authentication of materials using prompt gamma ray activation analysis
- Grand challenges in membrane transport, modeling and simulation
- Techno‐Economic Analysis of Membrane‐Based Purification Platforms for AAV Vector Production
- Techno‐Economic Analysis of Membrane‐Based Purification Platforms for AAV Vector Production
- Techno‐Economic Analysis of Membrane‐Based Purification Platforms for AAV Vector Production
- Techno‐Economic Analysis of Membrane‐Based Purification Platforms for AAV Vector Production
- Techno‐Economic Analysis of Membrane‐Based Purification Platforms for AAV Vector Production
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