Contact Information
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School of Industrial Engineering Member of the Purdue Institute for Inflammation, Immunology, and Infectious Diseases Co-Director, Network Morphospace Lab Purdue University 315 N. Grant Street West Lafayette, IN 47907-2023 Email: mventresca (at) purdue (dot) edu Office: Grissom 292 |
Please DO NOT contact me concerning graduate student admission; they will be ignored. Thank You.
Research
My research focuses on computational aspects of two primary areas: operations research and complex systems. More specifically, I develop and apply computational methods for analyzing, modeling, predicting, designing, and controlling such systems in order to discover deeper scientific insight and achieve operational outcomes. I have a genuine interest in both theoretical and applied pursuits, typically gravitating toward those requiring expertise in at least one of:
- Approximation algorithms, which aim to efficiently solve difficult optimization problems, while also providing guarantees on solution quality and run-time performance.
- Automated design and inference, whereby robust algorithms are developed for the purpose of automatically designing complex systems, or to ascertain the underlying principles or rules of a given system.
- Biomedical science and computational epidemiology, which seeks to deepen our understanding of biological processes and disease spread with the intention of enhancing mitigation, diagnosis and treatment capabilities.
- Complexity engineering, where concepts from complexity science such as emergence and self-organization are applied to the design of complex systems.
- Data Science, which leverages computational power to statisticall analyze, or learn from large and/or complex data sets in order to develop intelligent systems.
- Discrete optimization, which is concerned with problems where we must select the best solution from a finite number of feasible solutions; encompassing areas such as linear programming, graph theory, scheduling and routing.
- Health and healthcare systems, which is concerned with understanding and improving individual and public health outcomes and policies.
- Nature-inspired computing, which seeks to develop algorithms based on concepts such as evolution and swarming intelligence to solve complex real-world problems.
- Network science, which focuses on understanding, controlling and predicting the structure and function of interconnected systems as well as processes acting upon them.
To find out more about my research please see my list of publications.