Theoretical population geneticist, Peter Beerli, maintains and further develops software that he started to write around 2000.
Chen Huang, assistant professor in the Department of Scientific Computing, conducts research to develop new computational tools that can predict the properties of materials at a nanoscale based on computer simulations.
The ability to collect, store and analyze vast amounts of data is a major challenge in the field of oceanographic studies. Dr. Steve Morey, a physical oceanographer at the Florida State University Center for Ocean and Atmospheric Prediction Studies (COAPS), is very familiar with issues in conducting research at such a scale.
Assistant professor in the Department of Earth, Ocean and Atmospheric Science (EOAS), Allison Wing, conducts hurricane simulations to study how storms in the tropics are affected by and interact with climate. Dr. Wing and her team create and analyze computer models of tropical clouds, hurricanes and atmospheric processes to try to understand how hurricanes are formed. These models allow Dr. Wing and her team to simulate experiments unavailable in the real world.
Karen Oehme, director of the Institute for Family Violence Studies, has conducted social research work focused on a variety of target groups, ranging from U.S. criminal justice officers to parents who are undergoing a divorce.
Neda Yaghoobian, an assistant professor at the FAMU-FSU College of Engineering, has a keen interest in thermo-fluid dynamics. Through her research, she is examining the relationship between the ground and the atmosphere to better understand airflow and its effects on “where we live and what we experience.”
There is an undeniable stigma associated with poorer or more ethnically homogenous communities receiving unjust attention from government parties. Christopher Reenock decided to take a closer look and see which communities are facing greater risks. Furthermore, he wanted to find out what services government parties are providing for these neighborhoods.
Daniel Tompkins, an alumnus from the FSU College of Music, found a unique way to use machine learning to conduct music research. Using RCC resources, Daniel analyzed the harmonies and chords in hundreds of early music manuscripts. His goal was to create an approach that allows users to computationally distinguish and classify music from different eras and genres.