T. Richard Nichols received the B.S. degree in biology from Brown University, Providence, RI, USA, in 1969, and the Ph.D. degree in physiology from Harvard University, Cambridge, MA, USA, in 1974. He is currently a Professor in the School of Biological Sciences at the Georgia Institute of Technology.,He is currently a Professor in the School of Biological Sciences at the Georgia Institute of Technology, Atlanta, GA, USA.

Overview:
Our brain not only processes sensory signals but also makes predictions about the world. Generating and updating predictions are essential for our survival in a rapidly changing environment. Multiple brain regions including the cerebellum and the cortex are thought to be involved in the processing of prediction signals (aka predictive processing). However, it is not clear what circuit mechanisms and computations underlie predictive processing in each region, and how the cortical and cerebellar prediction signals interact to support cognitive and sensorimotor behavior. Our lab is interested in figuring out these questions by using advanced experimental and computational techniques in systems neuroscience.

David’s varied interests have fueled an unusual educational background that fuses engineering, microsystem design, biology, and clinical research. David received his PhD in mechanical engineering from the University of California at Berkeley, under the tutelage of one of the early microsystems pioneers, Albert P. Pisano, PhD. Driven by a desire to see new types of sensors in the clinic, David undertook a postdoctoral fellowship in biomedical and clinical research with Wilbur A. Lam, MD, PhD, in the Wallace H. Coulter Department of Biomedical Engineering at Emory University and the Georgia Institute of Technology. Working at the intersection of these fields, David has authored or contributed to publications in Nature Materials, Nature Communications, PNAS, and Blood. 

Ratan is an Assistant Professor of Cognition and Brain Science in the School of Psychology at Georgia Tech, and the Director of the Murty Lab (murtylab.com). He obtained his PhD from Indian Institute of Science (IISc) Bangalore and was a postdoctoral researcher in the Kanwisher and DiCarlo labs at MIT before moving to Georgia Tech. Research in the Murty Lab aims to uncover the neural codes and algorithms that enable us to see. The central theme of the lab's work is to integrate biological vision with artificial models of vision. The lab combines the benefits of closed-loop experimental testing (using 3T/7T human functional-MRI) with cutting-edge computational methods (like deep neural networks, generative algorithms, and AI interpretability) toward a new computationally precise understanding of human vision. This research also guides the development of neurally mechanistic biologically constrained models aimed to uncover a better understanding of the neurobiological changes that underlie perceptual abnormalities such as agnosias.

Dr. Cassie S. Mitchell is a research engineer, elite athlete, and mentor. She is a current member of the USA Paralympic team and research faculty in the Wallace H. Coulter Department of Biomedical Engineering at Georgia Institute of Technology and Emory University. At age 18 Cassie was afflicted with Devics Neuromyelitis Optica, leaving her as a quadriplegic and with visual impairments. Her faith and philosophy on life has helped her to overcome the resulting challenges. She graduated with a B.S. in Chemical Engineering from Oklahoma State University and a Ph.D. in Biomedical Engineering from GT/Emory. She enjoys mentoring high school and college students as well as new spinal cord injury patients at Shepherd Center Brain and Spinal Cord Rehabilitiation Hospital, Atlanta, Georgia.

Svjetlana Miocinovic is a board-certified neurologist specializing in Parkinson’s disease, dystonia, tremor and other movement disorders. She graduated from medical school in 2009 at Case Western Reserve University (Cleveland, Ohio) where she also obtained a PhD in biomedical engineering. She completed neurology residency and clinical movement disorders fellowship at University of Texas Southwestern Medical Center (Dallas, Texas). Her post-doctoral training and clinical research fellowship were at the University of California San Francisco Movement Disorder and Neuromodulation Center. In 2016, she joined the Department of Neurology at Emory University (Atlanta, Georgia). Her clinical focus is on using deep brain stimulations (DBS) to treat movement disorders. She also directs an NIH-funded human electrophysiology laboratory and is an investigator with Emory's Udall Parkinson's Disease Research Center of Excellence. The research focus of her laboratory is on electrophysiology of human motor and non-motor circuits, and development of new device-based therapies. 

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.
 

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.