Contact Information
|
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 falls in the general area of computational science and engineering, which focuses on the design, analysis and application of computational and mathematical approaches for solving challenging real-world problems, as well as for understanding real and artificial complex systems. I have a genuine interest in different application domains and scientific endeavors, however, most projects I gravitate towards fall under 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.
- 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.
- Machine learning, which leverages computational power to learn from large and/or complex data sets in order to develop intelligent systems.
- 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.