Research

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SimLab's research interests lie broadly under the umbrella of simulation modeling and optimization of large scale and dynamic systems via Dynamic-Data-Driven Application Systems (DDDAS), particle filtering and optimal computing budget allocation methodologies, and big data analytics. Our work focuses on distributed power networks (i.e., microgrids and smartgrids), solid waste management systems, and recenly on air traffic management systems.

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Smartgrids & Microgrids

A microgrid is an energy distribution system consisting of both renewable and conventional power generation sources along with some form of energy storage. A microgrid system is capable of operating both along side of a municipal power grid or as an “island” separate from the local utility grid. They hold out the promise of increased reliability and new services (e.g. dynamic pricing, distributed energy resource management, etc.) to customers by lowering the transmission within electric networks.

Particle Filtering & State Estimation

Particle filtering (also known as sequential Monte Carlo (SMC) methods) is a simulation-based estimation technique that is capable of handling massive datasets and diverse external factors. Our research focuses significantly on developing theoretical improvements to the particle filtering algorithm for real-world state estimation and optimization problems of large-scale systems using the advanced particle filters.

Epigenetics & Gene Clustering

Recent molecular and genetic studies have revealed the importance of DNA methylation, a key epigenetic mark, in regulating gene expression and the abnormal profiles of DNA methylation in various diseases including cancer. Here, we use unsupervised learning to extract useful information from high-dimensional genome wide methylation data to provide crucial insights for accurate early diagnosis and treatment of cancer.

Solid Waste Management

The SIMWASTE Project is a research project in the Department of Industrial Engineering at the University of Miami. The project is directed by Dr. Nurcin Celik, an assistant professor of Industrial Engineering, who has significant experience with large-scale system simulation and optimization. The project is sponsored by the Hinkley Center for Solid and Hazardous Waste Management.
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