Faculty Achievements

2021 | 2020 | 2018-19 | 2017 | 2016 |

Michael DeGiorgio

Dr. Michael DeGiorgio

Assistant Professor, Department of Computer & Electrical Engineering and Computer Science

Researcher Introduces Innovations in Evolutionary Genomics

Understanding the evolutionary processes that shape the distribution of genetic variation among individuals, populations, and species, is central to the study of evolutionary and population genomics.

Dr. Michael DeGiorgio, associate professor in the Department of Computer & Electrical Engineering and Computer Science at the FAU College of Engineering and Computer Science, is conducting groundbreaking research in this field, as he works to develop methods and software tools for understanding biological data, particularly when the data sets are large and complex.

Dr. DeGiorgio runs a data science research group at FAU that focuses on three major areas: statistical population genomics, human evolutionary genomics, and mathematical and algorithmic phylogenomics. His research program has attracted over $2.4 million in private and federal funding as sole principal investigator, and close to $1.8 million in additional awards through collaborative efforts.

“We work in human evolutionary genomics by employing information from ancient and modern DNA samples to elucidate the evolutionary history of populations in the Americas,” Dr. DeGiorgio explained. “We also develop statistical and machine learning methods for identifying genomic regions undergoing natural selection. In addition, we design and theoretically assess algorithms for inferring phylogenies when genomic signals conflict.”

Dr. DeGiorgio’s research has the potential to have significant impacts on public health as it relates to natural selection, which is an important evolutionary force that enables humans to adapt to new environments and fight disease-causing pathogens. However, the unique footprints of natural selection in the human genome can be buried beneath those left by other evolutionary forces. “By leveraging information about multiple evolutionary forces, we can identify signatures of natural selection in the human genome, and ultimately determine its role in human adaptation and disease,” said Dr. DeGiorgio.

To support his research in this area, Dr. DeGiorgio received the highly competitive National Institutes of Health Maximizing Investigators' Research Award (MIRA) for early-stage investigators. This award is funding a $1.8 million project to develop statistical and machine learning methods for population genomics to identify signals of adaptation from genetic data.

Dr. DeGiorgio also received a $255,000 grant from the National Science Foundation (NSF) to use advanced DNA sequencing technology and population genomics to elucidate the demographic and adaptive history of the indigenous people of North America. Results are shared with participants from seven indigenous nations and will be highlighted during the annual Summer internship for INdigenous peoples in Genomics (SING) workshops.

“The SING outreach program is particularly significant, since it aims to introduce individuals from Native American communities – regardless of their educational background – to what scientists can currently do with an individual’s genomic data, and as well as the ethical, legal, and social issues associated with genomics research,” said Dr. DeGiorgio. “The project also seeks to directly engage indigenous communities in bioinformatics and genomics research. Our hope is to recruit future SING participants who are interested in a scientific career to start a PhD program and drive the research studies from this award.”

In addition, Dr. DeGiorgio is co-PI for a collaborative NSF RAPID grant focused on using genetic data to learn about the evolutionary process affecting coronavirus. The project team is being led by Dr. Xingquan (Hill) Zhu, professor in the Department of Computer & Electrical Engineering and Computer Science. Dr. Massimo Caputi, professor at FAU’s Charles E. Schmidt College of Medicine, is co-PI.

In 2017, Dr. DeGiorgio received the prestigious Alfred P. Sloan Award, for which he completed a research fellowship in computational and evolutionary molecular biology. In 2020, he was appointed Associate Editor for IEEE/ACM Transactions on Computational Biology and Bioinformatics. 

Looking ahead, Dr. DeGiorgio plans to work with Dr. Raquel Assis, assistant professor in the Department of Computer & Electrical Engineering and Computer Science, to develop new machine learning and statistical approaches to uncover the evolutionary processes that affect different traits across species. Dr. Assis received a seed grant from the College of Engineering and the Institute for Sensing and Embedded Network Systems Engineering (I-SENSE) for a project related to sequencing several species of monkey to learn about their evolutionary history. The co-PI team includes Dr. DeGiorgio and Dr. Kate Detwiler, associate professor at FAU’s Dorothy F. Schmidt College of Arts and Letters, and the three of them are working on a proposal to submit to the National Science Foundation for additional funding.

Prior to joining FAU in 2019, Dr. DeGiorgio was an associate professor at Pennsylvania State University. “One of the reasons I came to FAU was because I was looking for a place where students had the quantitative skills in AI, machine learning, and bioengineering, to develop the computational tools for the biological questions we’re pursuing,” he said.

At FAU, he teaches Introduction to Data Science and Computational Foundations of Artificial Intelligence, and he enjoys the opportunity to collaborate with faculty and students on interdisciplinary research projects. “There is a lot of potential for collaboration with the College of Medicine and the College of Science, particularly in the field of bioinformatics, and I am looking forward to further pursuing those opportunities for collaboration,” he added.

Dr. Jinwoo Jang

Dr. Jinwoo Jang

Assistant Professor, Department of Civil, Environmental and Geomatics Engineering and faculty fellow at the Institute for Sensing and Embedded Network Systems Engineering (I-SENSE)

Researcher Develops New Algorithms for Smart Onboard Data Processing in Sensor Technologies

By 2030, nearly 146 million connected vehicles will be in operation in the U.S, and each vehicle will generate 25 gigabytes of data per hour. However, traditional data analytics systems are not capable of handling this high amount of data. A researcher at the FAU College of Engineering and Computer Science is using novel data science tools to create new data mining algorithms embedded at the vehicle level that can collect and process streams of data in a highly efficient and scalable way.

Dr. Jinwoo Jang, assistant professor in the Department of Civil, Environmental and Geomatics Engineering and faculty fellow at the Institute for Sensing and Embedded Network Systems Engineering (I-SENSE) is using sensor network applications and robust data analytics for more efficient data sampling. In his Smart and Livable Cities research group at FAU, Dr. Jang’s work focuses on the development of state-of-the-art data science approaches to advance physical and cyber components of civil infrastructure. With expertise in sensor networks and data science, he analyzes in-vehicle data to understand the conditions of the driver, and also specializes in working on sensors and condition monitoring over an extended period of time to understand the conditions of structures.

“Over the past decades, developments in sensing technology and wireless communication have provided cities and communities with increasingly-important sensor data to create more reliable and livable urban environments,” he said. “The ultimate goal of my research is to harness sensor data, integrated with novel artificial intelligence, to better inform, design, manage, and understand our city-scale civil infrastructure systems.”

Dr. Jang has received external funding for several projects that allow him to apply his unique multidisciplinary expertise in both structural and transformation engineering, as well as in the fields of data science and artificial intelligence. After creating accelerometers and GPS sensors to attach to a building and a bridge, he then develops an algorithm to use the sensor data to understand the condition of a structure and how it might be impacted by operational factors such as traffic, or environmental factors such as wind and humidity. A similar type of sensor can be installed in a vehicle to monitor, collect, and process the data to understand traffic flows, driver behavior, and street asset conditions. This work can have significant impacts on the transportation industry and the future of smart cities.

Dr. Jang is a co-PI for a five-year, $5.3 million grant from the National Institutes of Health to formulate the first in-vehicle sensing system to detect cognitive change in older drivers. He is part of an interdisciplinary research team led by Dr. Ruth Tappen, professor and Christine E. Lynn Eminent Scholar in FAU’s Christine E. Lynn College of Nursing, that will test and evaluate an unobtrusive, low-cost, in-vehicle sensing system to understand older drivers’ cognitive and physical functions. Dr. Jang is leading the engineering team by developing unobtrusive in-vehicle sensors to detect cognitive changes that are early indicators of dementia, and he is using AI to process the different types of data. He is developing and managing 750 devices and sensors, including hardware and software, for the 750 people expected to participate in the study.

“The current trend in medicine is to put sensors on things that monitor people in daily life, without the person having to go to the hospital,” he explained. “Since we want to understand a person’s mental health through a normal, daily driving situation, we are working together with nursing and neuroscience experts to develop new technology to monitor the patient’s physical health. As people get older, they have certain driving patterns that are going to change, and we are trying to analyze the trajectory of that change. We are designing the hardware and sensors to detect all changes in cognitive function, as well as collect and analyze all possible data to help us understand those changes.”

With a $170,000 grant from the National Science Foundation, Dr. Jang is working on vehicle sensing by using Internet of Things (IOT) technology and data science to harness in-vehicle sensors as a means of mobile sensing platforms to obtain city-scale traffic and road safety data. “As we look to the future, when we will have a lot of connected vehicles, our goal is to develop a new algorithm that can enable more efficient onboard data processing,” he explained. “This algorithm will be a new approach, which is more computer science-based, to produce a better way of defining vehicle data that can easily integrate with the map data so that massive in-vehicle data can be simply visualized on the map.”

When Dr. Jang was pursuing his Ph.D. degree at Columbia University from 2013-2016, the field of data science and sensors was just starting to take off and was expanding to include infrastructure and transportation. When his thesis advisor was named chair of the university’s Smart City in Data Science Institute, Dr. Jang found himself at the forefront of this up-and-coming field. During his Ph.D. studies, he focused on system identification based on data, and there was a significant amount of overlap with robotics since he also wanted to monitor the conditions of the structure based on real data.

“It was a very new field for civil engineering back then, and it was fascinating to work on sensors and analyze real-time data, combining my interests in sensing, IOT, and AI,” Dr. Jang recalled. During that time, he developed a wireless vibration monitoring system for the Metropolitan Museum of New York, to monitor vibration levels of the building to ensure that valuable paintings and other exhibits weren’t vibrating excessively during times of construction.

Dr. Jang also has extensive previous experience with telematics data. While working as a research intern at Philips Research North America, he developed hardware and in-vehicle sensors, using Raspberry PIs, to investigate low-cost solutions for city asset managements, while incorporating AI algorithms into his research. During a postdoctoral fellowship at Data Science Institute at Columbia University, he worked with the New York State Department of Transportation on Vision Zero-related road safety research using telematics data to learn driver behaviors correlated with crashes and how road infrastructure impacts those behaviors.

As an expert in data science and analytics for data monitoring systems, Dr. Jang is among the senior personnel for a $2.4 million grant from the National Science Foundation to train graduate students in data science technologies and applications. Led by Dr. Borko Furht, professor in the Department of Computer and Electrical Engineering and Computer Science and director of the NSF Industry/University Cooperative Research Center for Advanced Knowledge Enablement (CAKE), the project team includes other researchers from the College of Engineering, as well as from FAU’s College of Medicine, College of Nursing, and College of Science. Although scientists and engineers are well trained in their own areas of specialty, there is a lack of integrative knowledge needed for new scientific discoveries and industry applications made possible by data science and analytics.

At the College of Engineering, Dr. Jang trains his students in these areas as well. “In my course on Structural Health Monitoring, students learn how to how to use sensing technology and data to understand the condition of a structure in its daily state,” he said. “In my Structural Dynamics course, I teach students his students learn how to analyze time-sensitive data and vibration data, as well as how they can design structures to withstand conditions such as hurricanes or tornados. I also teach an Analysis of Structures course, a fundamental course in structural engineering, where my students learn about structures and reinforced concrete design.”