I am an engineer and neuroscientist focused on how the brain and body cooperate to allow us to move. Fundamental abilities like standing and walking appear effortless until we–or someone we love–loses that ability. Movement is impacted in a wide range of diseases because it involves almost all parts of the brain and body, and their interactions with the environment. How we move is also highly individualized, changing across our lifetimes as a function of our experiences, and adapting in different situations. As such, assessing and treating movement impairments remains highly challenging. My approach is to dissect the complexities of how we move in health and disease by bridging what may seem to be disparate fields across engineering, neuroscience, and physiology. Our current application areas are Parkinson’s disease, stroke, aging and cerebral palsy, and we are interested in extending our work toward mild cognitive impairment and concussion.

My lab uses robotics, computation, and artificial intelligence to identify new physiological principles of sensing and moving that are enabling researchers to personalize rehabilitation and medicine. Primarily, we study people in the lab, studying brain and muscle activity in relationship to the body’s biomechanics in standing and walking. We use and develop robotic devices for assessing and assisting human movement, while interpreting brain and muscle activity to personalize the interactions. Our novel computer simulations of muscle, neurons, and joints establish a virtual platform for predicting how movements change in disease and improve with interventions. Recently, we have demonstrated the critical role of cognitive function motor impairment that may increase fall risk, suggesting that how we move and how we think may be closely related. Current projects include developing physiologically-inspired controllers to enable exoskeletons to enhance user balance, identifing individual differences that predict response to gait rehabilitation in stroke survivors, and developing more precise and physiologically-based methods to interpret clinical motor test outcomes.

Nicoleta Serban is the Peterson Professor of Pediatric Research in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech.

Dr. Serban's most recent research focuses on model-based data mining for functional data, spatio-temporal data with applications to industrial economics with a focus on service distribution and nonparametric statistical methods motivated by recent applications from proteomics and genomics. 

She received her B.S. in Mathematics and an M.S. in Theoretical Statistics and Stochastic Processes from the University of Bucharest. She went on to earn her Ph.D. in Statistics at Carnegie Mellon University.

Dr. Serban's research interests on Health Analytics span various dimensions including large-scale data representation with a focus on processing patient-level health information into data features dictated by various considerations, such as data-generation process and data sparsity; machine learning and statistical modeling to acquire knowledge from a compilation of health-related datasets with a focus on geographic and temporal variations; and integration of statistical estIMaTes into informed decision making in healthcare delivery and into managing the complexity of the healthcare system.

Joe Lachance is an Assistant Professor in the School of Biological Sciences at Georgia Institute of Technology and a member of the Cell and Molecular Biology Research Program at Winship Cancer Institute.

Lachance received his Ph.D. in Genetics from Stony Brook University in Stony Brook, New York. He conducted his postdoctoral studies as a NIH Kirschstein postdoctoral fellow at the University of Pennsylvania.

Lachance's research is in the areas of human evolutionary genomics, population genetics, and health disparities. His lab integrates large genome-scale datasets with evolutionary theory and computer simulations. They have found evidence of ancient introgression in Africa, inferred that the leading edge of the out-of-Africa migration involved an excess of males, discovered that genetic risks of cancer have decreased over evolutionary time, and identified novel targets of positive selection.

Pinar Keskinocak is the H. Milton and Carolyn J. Stewart School Chair and Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. She is also co-founder and director of the Center for Health and Humanitarian Systems. Previously, she served as the College of Engineering ADVANCE Professor and as interim associate dean for faculty development and scholarship. Prior to joining Georgia Tech, she worked at IBM T.J. Watson Research Center. She received her Ph.D. in Operations Research from Carnegie Mellon University, and her M.S. and B.S. in Industrial Engineering from Bilkent University.

Keskinocak's research focuses on the applications of operations research and management science with societal impact, particularly health and humanitarian applications, supply chain management, and logistics/transportation. Her recent work has addressed infectious disease modeling (including Covid-19, malaria, Guinea worm, pandemic flu), evaluating intervention strategies, and resource allocation; catch-up scheduling for vaccinations; hospital operations management; disaster preparedness and response (e.g., prepositioning inventory); debris management; centralized and decentralized price and lead time decisions. She has worked on projects with companies, governmental and non-governmental organizations, and healthcare providers, including American Red Cross, CARE, Carter Center, CDC, Children’s Healthcare of Atlanta, Emory University, and Intel Corporation.

She is an INFORMS Fellow and currently serves as the president of INFORMS. Previously she served as the Secretary of INFORMS, a department editor for Operations Research (Policy Modeling and Public Sector area), associate editor for Manufacturing & Service Operations Management, and INFORMS Vice President of Membership and Professional Recognition. She is the co-founder and past-president of INFORMS Section on Public Programs, Service, and Needs, and the president of the INFORMS Health Applications Society.

Greeshma Agasthya (she/her/hers) is an Assistant Professor in the Nuclear & Radiological Engineering and Medical Physics Program at the George W. Woodruff School of Mechanical Engineering at Georgia Institute of Technology. She leads the Computational Medical Physics Laboratory, and her research interests are: (1) developing multiscale digital twins for personalized radiation dosimetry for imaging, therapy, and theranostics, (2) modeling and simulations to assess novel radiation protocols from cancer diagnosis to cancer treatment, and (3) developing AI frameworks to model patient trajectories for early intervention and treatment in oncology.

Previously, she was a research scientist at Oak Ridge National Laboratory in the Advanced Computing for Health Sciences section. Agasthya received her doctorate in Biomedical Engineering from Duke University and completed her postdoctoral training at Emory University's Winship Cancer Institute. She has experience in medical imaging research, modeling and simulation for radiation dosimetry, and AI and Machine learning for healthcare. Agasthya has developed and used multi-scale modeling and simulations of the human body for virtual clinical trials, radiation dosimetry, and optimization of medical imaging systems for cancer applications. She has worked on artificial intelligence (AI) for cancer surveillance, predicting disease outcomes, and clinical decision support. She has collaborated with experts in medical physics, radiology, cardiology, computer engineering, and statistics to tackle interdisciplinary challenges in medical physics and biomedical engineering. She has worked on imaging modalities including neutron imaging, x-ray radiography, computed tomography (CT), and tomosynthesis systems for cancer applications.

Alexander Vlahos is an Assistant Professor in the Wallace H. Coulter Department of Biomedical Engineering at Georgia Tech and Emory University. Alexander received his B.S. in Biochemistry from McMaster University and his Ph.D. from the University of Toronto under the supervision of Professor Michael Sefton. His Ph.D. work focused on developing an injectable bioartificial pancreas that could be delivered underneath the skin. He then transitioned to mammalian synthetic biology, where he conducted his postdoctoral work as an HFSP long-term fellow at Stanford University with Professor Xiaojing Gao.

His research integrates principles from synthetic biology, protein engineering, and tissue engineering to develop synthetic protein circuits for mammalian cellular engineering. The Vlahos lab synergizes synthetic biology and tissue engineering to create programmable gene and cell therapies for biomedical applications in regenerative medicine, cancer, and autoimmune disease. His lab has three main research themes, including 1) generating protein sensors to sense changes in internal cell states or the external microenvironment, 2) programming engineered cells to model cell-to-cell communication and elucidate the dynamics and expression of key signals that govern fibrosis and immune rejection, and 3) applying synthetic protein circuits to modulate the immune system and improve cell transplantation.

Justin Kim is an Associate Professor in the School of Chemistry and Biochemistry. He received his A.B. in Chemistry and Physics and an A.M. in Chemistry from Harvard College in 2003 then received his Ph.D. in Organic Chemistry from the Massachusetts Institute of Technology in 2013. After a postdoctoral fellowship as a Miller Institute Fellow at UC Berkeley and at Stanford University, he joined the faculty of the Department of Cancer Biology at Dana-Farber Cancer Institute and the Department of Biological Chemistry and Molecular Pharmacology at Harvard Medical School in 2016 as an Assistant Professor. He later joined the faculty at Georgia Tech in 2024. He is the recipient of the NIH Director’s New Innovator Award (2018), Thieme Chemistry Journal Award (2021), and the NSF CAREER Award (2023). Professor Kim’s research program is defined by the development of biologically relevant reactions for use in chemistry, biology, and materials science. His primary research interests are in expanding the functional repertoire of bioorthogonal chemistry, specifically exploring new bond-forming and breaking methods that enable platforms for discovering and targeting small molecule-protein and protein-protein interactions as well as for creating functionally dynamic biomaterials.

Dr. Jacob Berchuck is a Medical Oncologist at the Winship Cancer Institute and Assistant Professor in the Department of Hematology and Medical Oncology at Emory University School of Medicine. Prior to joining Emory, Dr. Berchuck was an Assistant Professor of Medicine at Harvard Medical School and a Medical Oncologist at the Dana-Farber Cancer Institute. In addition to caring for patients, Dr. Berchuck leads a translational research lab focused on utilizing "liquid biopsy" tools that enable multi-omic profiling of tumor-derived cell-free DNA circulating in the bloodstream to pioneer advances that transform how we manage and treat individuals living with cancer. The core research objectives of the Berchuck Lab include include developing biomarkers to guide treatment decisions, working towards a future where a simple blood draw can enable real-time insights to choose the right treatment for the right patient at the right time, and studying mechanisms of therapeutic resistance. Dr. Berchuck’s research has been published in several high-impact journals, including Nature Medicine, Cancer Cell, Annals of Oncology, JAMA Oncology, Clinical Cancer Research, and others.

Dr. Rahnev received his Ph.D. in Psychology from Columbia University in 2012. After completing a 3-year post-doctoral fellowship at UC Berkeley, he joined Georgia Tech in 2015 where he is currently Blanchard Early Career professor. His research focuses on perceptual decision making – the process of internally representing the available sensory information and making decisions on it. Dr. Rahnev uses a wide variety of methods such as functional magnetic resonance imaging (fMRI), transcranial magnetic stimulation (TMS), psychophysics, computational modeling, and deep neural networks (DNNs). Dr. Rahnev’s work appears in high-impact journals such as Behavioral and Brain Sciences, PNAS, Nature Communications, and Nature Human Behavior. He has received over $3.5M in funding, including PI grants from NIH, NSF, and the Office of Naval Research.

Anna (Anya) Ivanova is an Assistant Professor of Psychology at Georgia Institute of Technology. She got her Ph.D. from MIT’s Department of Brain and Cognitive Science and carried out her postdoctoral training at MIT Quest for Intelligence. In her research, Anya is examining the language-thought relationship in humans and in large language models using a synergistic combination of human brain imaging, behavioral studies, and computational modeling.