FEATURE

Hongcheng Liu, Ph.D.

Panos Pardalos, Ph.D.

UF FACULTY BRING AN INDUSTRIAL & SYSTEMS ENGINEERING APPROACH TO AI

Mostafa Reisi Gahrooei, Ph.D.

Many industrial and systems engineering faculty at the University of Florida have been conducting research in AI in the areas of data analytics and optimization methods and applications. There are currently five funded projects focused on AI for data fusion, system informatics, algorithms for AI model development, and deep learning applications. The projects address various domains such as agriculture, manufacturing, transportation and military systems, and healthcare.

Professor Hongcheng Liu, Ph.D., received funding from the National Science Foundation to support his research in developing algorithms to improve methods of radiation therapy used in cancer treatments by optimizing the treatment planning process. This new and improved algorithm is expected to be a fundamentally novel integration of derivative-free optimization, high-dimensional statistics, deep learning, and a sampling-based technique to evaluate a stochastic system known as (quasi-) Monte Carlo simulation. If successful, the outcomes of this project could accelerate solutions for RTP, free up time for the practitioners, reduce costs, and potentially allow more patients to be treated in a timely manner.

Distinguished Professor, Panos Pardalos, Ph.D., has received funding from both the U.S. Air Force Research Laboratory (AFRL) Munitions Directorate and the UF Informatics Institute in support of his many AI-related projects.

Dr. Pardalos’ first project, which is funded by AFRL, looks to develop deep learning navigation applications with synthetic aperture radar (SAR) image data used by unmanned aerial vehicles. This research will impact the future use of autonomous agents in GPS-denied environments. Not only will networks be capable of real-time inference and navigation using SAR image analysis but will also be more accurate than the technology that is currently available. This is possible by applying superresolution concepts that have been shown to improve the quality of SAR images, which can then be processed to improve navigation methods.

With support from the UF Informatics Institute, Dr. Pardalos and Assistant Professor Mostafa Reisi Gahrooei, Ph.D., plan to use small unmanned aerial vehicles with multiple sensors to collect data over vast crop fields. The team will develop multimodal-data-fusionbased AI models that will leverage data sets to accurately predict crop yields that will assist growers in crop health management and yield improvements.

Dr. Reisi is also working on an additional AI project in transportation. The research looks to provide a proactive, AI-based framework for monitoring road transportation networks during extreme events. Unlike current methods for monitoring road networks, this new framework will not only monitor real-time traffic data for early detection of changes in traffic before, during and after an extreme event, but will also predict any disruptions in the network that this event may cause. These predictions would be at a road segment level of granularity, which means that while it will consider the entire network, it will predict the exact road that is going to be disrupted.

This research will help transform current emergency management systems and will result in more efficient and successful rescue and recovery operations.

Assistant Professor Xiaochen Xian, Ph.D., has received funding from Cyber Florida in support of her research in using data analytics and system informatics enhanced anomaly detections and diagnosis for manufacturing infrastructure development. The project has three main goals: to develop stochastic models for network traffic data in order to assess the potential risk of cyber-attacks; integrate cyber and physical data to model the complex structure based on system informatics and; optimally balance between online data acquisition and quick anomaly detection.