Manuel D. Rossetti Data-verified
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
University Professor
faculty
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Biography and Research Information
OverviewAI-generated summary
Manuel D. Rossetti's research focuses on the development and application of simulation methodologies, particularly within healthcare systems. His work has involved creating new simulation libraries, such as the Kotlin Simulation Library (KSL), to facilitate the design and analysis of complex systems. He has explored enabling massively parallel exploration of simulation model design spaces within serverless computing environments, aiming to improve the efficiency and scalability of simulation studies.
Rossetti has also contributed to interdisciplinary education, including the creation of a multi-college Bachelor of Science program in Data Science. His research interests, as indicated by MeSH terms, include robotics, computer simulation, cost-benefit analysis, and hospital distribution systems, suggesting an application of simulation techniques to optimize healthcare operations and resource allocation. His scholarship metrics include an h-index of 21, 136 total publications, and 1,614 total citations, with recent activity noted in 2025.
Metrics
- h-index: 22
- Publications: 137
- Citations: 1,663
Selected Publications
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A Tutorial on Resource Modeling Using the Kotlin Simulation Library (2025)
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Input Distribution Modeling Using the Kotlin Simulation Library (2024)
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An Introductory Tutorial for the Kotlin Simulation Library (2024)
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A multicriteria model for assessing item importance and risk using operational data from military supply chains (2024)
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Enabling massively parallel, ad hoc exploration of the design space for simulation models within a serverless environment (2024)
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An Overview of the Multi-Disciplinary Data Science (MDaS) S-STEM Scholarship Program (2024)
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Introducing the Kotlin Simulation Library (KSL) (2023)
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Creating a Multi-College Interdisciplinary B.S. Data Science Program with Concentrations (2021)
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Measuring the Impact of Data Standards in an Internal Hospital Supply System (2021)
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Introducing the Multi-Disciplinary Data Science (MDaS) S-STEM Scholarship Program (2021)
Collaboration Network
Top Collaborators
- Introducing the Multi-Disciplinary Data Science (MDaS) S-STEM Scholarship Program
- Measuring the Impact of Data Standards in an Internal Hospital Supply System
- An Overview of the Multi-Disciplinary Data Science (MDaS) S-STEM Scholarship Program
- Automated Input Distribution Fitting Based on Multiple Criteria for the Kotlin Simulation Library
- Input Distribution Modeling Using the Kotlin Simulation Library
- Automated input distribution fitting based on multiple criteria for the Kotlin Simulation Library
- Introducing the Multi-Disciplinary Data Science (MDaS) S-STEM Scholarship Program
- An Overview of the Multi-Disciplinary Data Science (MDaS) S-STEM Scholarship Program
- Introducing the Multi-Disciplinary Data Science (MDaS) S-STEM Scholarship Program
- An Overview of the Multi-Disciplinary Data Science (MDaS) S-STEM Scholarship Program
- Introducing the Multi-Disciplinary Data Science (MDaS) S-STEM Scholarship Program
- An Overview of the Multi-Disciplinary Data Science (MDaS) S-STEM Scholarship Program
- Introducing the Multi-Disciplinary Data Science (MDaS) S-STEM Scholarship Program
- An Overview of the Multi-Disciplinary Data Science (MDaS) S-STEM Scholarship Program
- Automated Input Distribution Fitting Based on Multiple Criteria for the Kotlin Simulation Library
- Automated input distribution fitting based on multiple criteria for the Kotlin Simulation Library
- Measuring the Impact of Data Standards in an Internal Hospital Supply System
- Measuring the Impact of Data Standards in an Internal Hospital Supply System
- Creating a Multi-College Interdisciplinary B.S. Data Science Program with Concentrations
- An Overview of the Multi-Disciplinary Data Science (MDaS) S-STEM Scholarship Program
- Enabling massively parallel, ad hoc exploration of the design space for simulation models within a serverless environment
- A multicriteria model for assessing item importance and risk using operational data from military supply chains
- A multicriteria model for assessing item importance and risk using operational data from military supply chains
- A multicriteria model for assessing item importance and risk using operational data from military supply chains
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