Roman Mezencev's research uses genomics and functional genomics data, such as transcriptomics, methylomics, miRNA-omics, proteomics, and metabolomics, to identify distinct molecular subtypes of cancer and predict their sensitivity to traditional and new targeted anticancer agents. A more precise classification of cancer and the identification of new molecular subtypes can improve therapy decision-making and provide more accurate prognostication for cancer patients. 

In addition, he utilizes functional genomics to determine the potential of specific chemicals to cause cancer. Analyzing omics data also allows for identifying the carcinogenic mode of action of these chemicals and deriving their carcinogenic potency, which is crucial for human health risk assessment and public health considerations. 

Furthermore, cancer also has a unique molecular and epidemiological association with neurodegenerative diseases like Alzheimer's disease (AD), which is currently the seventh leading cause of death in the U.S. Mezencev's research explores these connections to identify shared risk factors and molecular mechanisms involved in the development of cancer and AD for a better understanding of these complex diseases and cross-pollination between anticancer and anti-AD drug development.

Roman Mezencev is an adjunct associate professor in the School of Biological Sciences at Georgia Tech and a scientist at the U.S. EPA’s National Center of Public Health and Environmental Assessment. His areas of research interest include cancer biology, pharmacology, toxicogenomics, protein misfolding diseases, and public health. In cancer biology, his main research focuses on using omics data to identify new cancer subtypes through molecular profiling, which can help enhance their diagnosis and treatment. Additionally, Mezencev explores the use of omics data to predict and understand chemically-induced cancer and other adverse outcomes to protect public health. He is also investigating the intriguing epidemiological associations and mechanistic connections between cancer and Alzheimer’s disease (AD), as well as other protein-misfolding diseases. By understanding these associations, we can identify shared risk factors and molecular mechanisms that can lead to the development of new anti-cancer and anti-AD drugs and enhance our understanding of these complex diseases.
 

Josiah Hester works broadly in computer engineering, with a special focus on wearable devices, edge computing, and cyber-physical systems. His Ph.D. work focused on energy harvesting and battery-free devices that failed intermittentently. He now focuses on sustainable approaches to computing, via designing health wearables, interactive devices, and large-scale sensing for conservation. 
   
His work in health is focused on increasing accessibility and lowering the burden of getting preventive and acute healthcare. In both situations, he designs low-burden, high-fidelity wearable devices that monitor aspects of physiology and behavior, and use machine learning techniques to suggest or deliver adaptive and in-situ interventions ranging from pharmacological to behavioral. 
   
His work is supported by multiple grants from the NSF, NIH, and DARPA. He was named a Sloan Fellow in Computer Science and won his NSF CAREER in 2022. He was named one of Popular Science's Brilliant Ten, won the American Indian Science and Engineering Society Most Promising Scientist/Engineer Award, and the 3M Non-tenured Faculty Award in 2021. His work has been featured in the Wall Street Journal, Scientific American, BBC, Popular Science, Communications of the ACM, and the Guinness Book of World Records, among many others.

Saad Bhamla studies biomechanics across species to engineer knowledge and tools that inspire curiosity.

Saad Bhamla is an assistant professor of biomolecular engineering at Georgia Tech. A self-proclaimed "tinkerer," his lab is a trove of discoveries and inventions that span biology, physics and engineering. His current projects include studying the hydrodynamics of insect urine, worm blob locomotion and ultra-low-cost devices for global health. His work has appeared in the New York Times, the Economist, CNN, Wired, NPR, the Wall Street Journal and more.

Saad is a prolific inventor and his most notable inventions includes a 20-cent paper centrifuge, a 23-cent electroporator, and the 96-cent hearing aid. Saad's work is recognised by numerous awards including a NIH R35 Outstanding Investigator Award, NSF CAREER Award, CTL/BP Junior Faculty Teaching Excellence Award, and INDEX: Design to Improve Life Award. Saad is also a National Geographic Explorer and a TED speaker. Newsweek recognized Saad as 1 of 10 Innovators disrupting healthcare.

Saad is a co-founder of Piezo Therapeutics.

Outside of the lab, Saad loves to go hiking with his partner and two dogs (Ollie and Bella).

King Jordan is Professor in the School of Biological Sciences and Director of the Bioinformatics Graduate Program at the Georgia Institute of Technology. He has a computational laboratory and his group works on a wide variety of research and development projects related to: (1) human clinical & population genomics, (2) computational genomics for public health, and (3) computational approaches to functional genomics. He is particularly interested in the relationship between human genetic ancestry and health. His lab is also actively engaged in capacity building efforts in genomics and bioinformatics in Latin America. 

Grover’s research activities in process systems engineering focus on understanding macromolecular organization and the emergence of biological function. Discrete atoms and molecules interact to form macromolecules and even larger mesoscale assemblies, ultimately yielding macroscopic structures and properties. A quantitative relationship between the nanoscale discrete interactions and the macroscale properties is required to design, optimize, and control such systems; yet in many applications, predictive models do not exist or are computationally intractable.

The Grover group is dedicated to the development of tractable and practical approaches for the engineering of macroscale behavior via explicit consideration of molecular and atomic scale interactions. We focus on applications involving the kinetics of self-assembly, specifically those in which methods from non-equilibrium statistical mechanics do not provide closed form solutions. General approaches employed include stochastic modeling, model reduction, machine learning, experimental design, robust parameter design, and estimation.

Fedorov's background is in thermal/fluid sciences, chemical reaction engineering as well as in applied mathematics. His laboratory works at the intersection between mechanical and chemical engineering and solid state physics and analytical chemistry with the focus on portable/ distributed power generation with synergetic CO₂ capture; thermal management of high power dissipation devices and electronics cooling; special surfaces and nanostructured interfaces for catalysis, heat and moisture management; and development of novel bioanalytical instrumentation and chemical sensors. Fedorov joined Georgia Tech in 2000 as an assistant professor after finishing his postdoctoral work at Purdue University.

Sam Brown's lab studies the multi-scale dynamics of infectious disease. Their goal is to improve the treatment and control of infectious diseases through a multi-scale understanding of microbial interactions. Their approach is highly interdisciplinary, combining theory and experiment, evolution, ecology and molecular microbiology in order to understand and control the multi-scale dynamics of bacteria pathogens.