Shaheen Azim Dewji, Ph.D., (she/her/hers) is an Assistant Professor in the Nuclear & Radiological Engineering and Medical Physics Programs at the Georgia Institute of Technology, where she leads the Radiological Engineering, Detection, and Dosimetry (RED²) research group. Dewji joined Georgia Tech following three years as faculty at Texas A&M University in the Department of Nuclear Engineering, and as a Faculty Fellow of the Center for Nuclear Security Science and Policy Initiatives (NSSPI). In her prior role at Oak Ridge National Laboratory, where she remained for almost 9 years, Dewji was Radiological Scientist in the Center for Radiation Protection Knowledge. Her research interests include development of dose coefficients, shielding design, and nuclear material detection assay using gamma-ray spectroscopy. Her recent work has focused on associated challenges in uncertainty quantification in dose estimation/reconstruction associated with the external exposure and internal uptake of radionuclides associated with applications of emergency response, defense, nuclear medicine, and occupational/public safety using Monte Carlo radiation transport codes and internal dose modeling. Dewji completed her Masters and Ph.D. degrees in Nuclear and Radiological Engineering at the Georgia Institute of Technology in Atlanta, GA and was a fellow of the Sam Nunn Security Program. She received her Bachelor of Science in Physics from the University of British Columbia. Dewji currently serves on the National Academies of Science, Engineering, and Medicine – Nuclear and Radiation Studies Board and is a member of the Board of Directors for both the American Nuclear Society and Health Physics Society.
   

The effortlessness of moving your body belies the lurking complexity driving it. We are trying to understand how the nervous system makes something so complicated as controlling a human body feel so natural. We use human subjects studies, animal experiments, mathematical biology, and artificial intelligence to understand neural control of movement. New theories and insight promise advances in physical therapy, human-machine collaboration, brain-computer interfaces, neural modulation of peripheral reflexes, and more.

Aditi Das did her BSc. (Hons.) Chemistry from St. Stephen's College Delhi, followed by M.S. (Chemistry) from I.I.T (Kanpur). She received her Ph.D. in Chemistry from Princeton University. She did post-doctoral work with Prof. Steve Sligar. She joined University of Illinois, Urbana-Champaign (UIUC) as a tenure track assistant professor in 2012. In 2019, she was promoted to associate professor with tenure. In 2022, she joined School of Chemistry and Biochemistry at Georgia Institute of Technology as an associate professor with tenure. Her research is in the area of enzymology of oxygenases that are involved lipid metabolism and cannabinoid metabolism.

Das is recipient of an American Heart Associate (AHA) career award and has been funded by National Institute of Health (NIH - NIGMS, NIDA and NCCIH), USDA, and National Multiple Sclerosis Society (NMSS). Her research was recognized by several National awards: Young Investigator award From Eicosanoid Research Foundation, Mary Swartz Rose Young Investigator Award and E.L.R. Stokstad award from American Society for Nutrition (ASN) for outstanding research on bioactive compounds for human health. She is also the recipient of Zoetis Research Excellence Award from her college. She was a co-organizer of the International Conference on Cytochrome P450. Recently her laboratory contributed several papers on cannabinoid metabolism by p450s. In recognition of this work, she was awarded El Sohly award from the ACS-Cannabis division for excellence in Cannabis research and is invited to give plenary lecture at ISSX meeting.  Das is also a standing study section member of BBM NIH study section. 

James Dahlman is a bioengineer / molecular engineer whose work lies at the interface of chemistry, nanotechnology, genomics, and gene editing. His lab focuses on targeted drug delivery, in vivo gene editing, Cas9 therapies, siRNA therapies, and developing new technologies to improve biomaterial design. 

The DahlmanLab is known for applying 'big data' technologies to nanomedicine. The lab is pioneering DNA barcoded nanoparticles; using DNA barcodes, >200 nanoparticles can be analyzed simultaneously in vivo. These nanoparticles are studied directly in vivo, and used to deliver targeted therapies like siRNA, mRNA, or Cas9. As a result of this work, James was named 1 of the 35 most innovative people under the age of 35 by MIT Technnology Review in 2018. James has won many national / international awards, and has published in Science, Nature Nanotechnology, Nature Biotechnology, Nature Cell Biology, Cell, Science Translational Medicine, PNAS, JACS, ACS Nano, Nano Letters, and other journals. James has also designed nanoparticles that efficiently deliver RNAs to the lung and heart. These nanoparticles can deliver 5 siRNAs at once in vivo, and are under consideration for clinical development. As a result, the lab has an interest in immunology and vascular biology. 

James supports entirely new research students come up with independently. To this end, DahlmanLab students learn how to (i) generate new ideas, (ii) select the good ones, and (iii) efficiently test whether the good ideas will actually work. 

Dahlman Lab students learn how to design/characterize/administer nanoparticles, how to isolate different cell types in vivo, how to rationally design DNA to record information, Cas9 therapies, and deep sequencing. As a result, the lab is an interdisciplinary group with students that have backgrounds in medicinal chemistry, BME, bioinformatics, biochemistry, and other fields. The lab welcomes students with all types of scientific backgrounds. The lab firmly stands by students, independent of their personal beliefs, preferences, or backgrounds.

Ahmet Coskun is a Bernie-Marcus Early-Career Professor of Biomedical Engineering at Georgia Institute of Technology and Emory University. Coskun is a systems biotechnologist and bioengineer, working at the nexus of multiplexed cell imaging and quantitative tissue biology. He directs an interdisciplinary research team at the Single Cell Biotechnology and Spatial Omics Laboratory, an interdisciplinary program strategically positioned for multiparameter imaging one cell at a time by spatial context and function. Coskun holds five issued patents and is also the co-author of more than 50 peer-reviewed publications in major scientific journals. He is a recipient of the NSF CAREER Award 2024, NIH R35 MIRA Award 2023, Sigma Xi Young Faculty Award 2025, CMBE Young Innovator Award 2024, BMES-CMBE Rising Star Award 2023, American Lung Association Innovation Award 2022, Burroughs Welcome Fund CASI Award 2016, and Student Recognition of Excellence in Teaching: Class of 1934 CIOS Award, among other research and teaching awards. Previously, Coskun was an instructor at Stanford University. He received his postdoctoral training from the California Institute of Technology. He holds a Ph.D. from the University of California, Los Angeles. His research has been supported by federal and private grants, including the National Institutes of Health (NIGMS, NIA, NIAID, NCI, NIDCR, OD, and ORIP), Wellcome LEAP, Burroughs Wellcome Fund (CASI), NSF CMaT, American Cancer Society IRG, Multi-cellular engineered living systems (M-CELS), and Regenerative Medicine Center. In addition, he leads outreach programs to engage K-12 students and undergraduate students through BioCrowd Studio, an innovative crowd-sourcing program bringing together interactive virtual media, distributed biokits, and collaborative spatial discovery.

Lily Cheung got her research start as a sophomore at Rutgers University, where she graduated Summa Cum Laude with a B.S. in Chemical Engineering in 2008. She then earned her Ph.D. in Chemical Engineering from Princeton University in 2013. Under the supervision of Stanislav Shvartsman, she characterized gene regulatory networks controlling the development of the model organism Drosophila melanogaster, using a combination of molecular biology, genetics, and reaction-diffusion modeling.

During her postdoctoral training with Wolf Frommer at the Carnegie Institution for Science, she designed biomolecular sensors to quantify sugar transport in plants. Her current interests include the use of high-throughput quantitative techniques and mathematical modeling to advance our understanding of how metabolic and gene regulatory networks interact to control plant growth.

Lily is the recipient of a NSF NPGI Postdoctoral Fellowship in Biology, a NSF CAREER Award, and a Human Frontier Science Program Early Career Award.

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.

Dr. Borodovsky and his group develop machine learning algorithms for computational analysis of biological sequences: DNA, RNA and proteins. Our primary focus is on prediction of protein-coding genes and regulatory sites in genomic DNA. Probabilistic models play an important role in the algorithm framework, given the probabilistic nature of biological sequence evolution.

Guy Benian is a professor of cell biology and pathology in the Department of Pathology and Laboratory Medicine at Emory University School of Medicine. His research focus is on myofibril assembly and maintenance in the model genetic system, Caenorhabditis elegans; focus on the functions and structures of giant multi-domain proteins, and the mechanism by which myofibrils are attached to the muscle cell membrane and transmit force.