Hee Cheol Cho is the Urowsky-Sahr Scholar in Pediatric Bioengineering and Associate Professor in the Department of Biomedical Engineering and Pediatrics. He received his PhD in Physiology from the University of Toronto in 2003.

Dr. Gregory S. Sawicki is an Associate Professor at Georgia Tech with appointments in the George W. Woodruff School of Mechanical Engineering and the School of Biological Sciences. He holds a B.S. from Cornell University ('99) and a M.S. in Mechanical Engineering from University of California-Davis ('01). Dr. Sawicki completed his Ph.D. in Human Neuromechanics at the University of Michigan, Ann-Arbor ('07) and was an NIH-funded Post-Doctoral Fellow in Integrative Biology at Brown University ('07-'09). Dr. Sawicki was a faculty member in the Joint Department of Biomedical Engineering at NC State and UNC Chapel Hill from 2009-2017. In summer of 2017, he joined the faculty at Georgia Tech with appointments in Mechanical Engineering 3/4 and Biological Sciences 1/4.

After studying ecology as a biology major at Swarthmore College, Annalise Paaby learned fly pushing as a technician for Steve DiNardo and then discovered evolutionary genetics as a tech for Paul Schmidt. She joined Paul’s lab as a graduate student and earned her Ph.D. from the University of Pennsylvania in 2009. In 2015, Paaby completed her postdoctoral training with Matt Rockman at New York University and began her appointment at Georgia Tech.

Patrick McGrath's research group is interested in understanding the genetic basis of heritable behavioral variation. In the current age, it has become cheap and easy to catalog the set of genetic differences between two individuals. But which genetic differences are responsible for generating differences in innate behaviors, including liability to neurological diseases such as autism, bipolar disease, and schizophrenia? How do these causative genetic variants modify a nervous system? Besides their role in disease, genetic variation is the substrate for natural selection. To understand how behavior evolves, we must understand how it varies.

Brian Hammer's lab studies molecular mechanisms important for microbial interactions. Bacteria are genetically encoded with regulatory networks to integrate external information that tailors gene expression to particular niches. Bacteria use chemical signals to orchestrate behaviors that facilitate both cooperation and conflict with members of the communities they inhabit. The group uses genetics and genomics, biochemistry, bioinformatics, and ecological approaches with a focus on the waterborne pathogen Vibrio cholerae.

Our work focuses on how the brain decides which action to perform at each moment in time – that is, action selection. We are interested in the cortical and subcortical circuits that mediate this process, and how they go awry in neurological disorders such as Parkinson’s disease. Specifically, we perform measurements of large-populations of neural activity in freely behaving mice using imaging and physiology, and distill their behavior in real-time using 3D cameras and probabilistic approaches to machine learning. Additionally, we are pursuing new methods to control activity in these circuits using precision closed-loop deep brain stimulation.

Education

Masters of Science, Computer Science, Georgia Institute of Technology, 2022

Bachelors of Science, Mechanical Engineering, Georgia Institute of Technology, 2020

Research Expertise

Robot Planning and Control, Embodied Artificial Intelligence, Laboratory Automation, Software Engineering

Selected Publications

Bowles-Welch, A., Byrnes, W., Kanwar, B., Wang, B., Joffe, B., Casteleiro Costa, P., Armenta, M., Xu, J., Damen, N., Zhang, C., Mazumdar, A., Robles, F., Yeago, C., Roy, K., Balakirsky, S. (2021). Artificial Intelligence Enabled Biomanufacturing of Cell Therapies. Georgia Tech Research Institute Internal Research and Development (IRAD) Journal

Byrnes, W., Ahlin, K., Rains, G., & McMurray, G. (2019). Methodology for Stress Identification in Crop Fields Using 4D Height Data. IFAC-PapersOnLine, 52(30), 336–341. https://doi.org/10.1016/j.ifacol.2019.12.562

Byrnes, W., Kanwar, B., Damen, N., Wang, B., Bowles-Welch, A. C., Roy, K., & Balakirsky, S. (2023). Process Development and Manufacturing: A NEEDLE-BASED AUTOSAMPLER FOR BIOREACTOR CELL MEDIA COLLECTION. Cytotherapy, 25(6), S172.

Wang, B., Kanwar, B., Byrnes, W., Costa, P. C., Filan, C., Bowles-Welch, A. C., ... & Roy, K. (2023). Process Development and Manufacturing: DIGITAL TWIN-ENABLED FEEDBACK-CONTROLLED AUTOMATION WITH INTEGRATED PROCESS ANALYTICS FOR BIOMANUFACTURING OF CELL THERAPIES. Cytotherapy, 25(6), S206-S207.

Professional Activities

STEM@GTRI Program Mentor

IEEE Member

Vince Calhoun, Ph.D., is the founding director of the tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) where he holds appointments at Georgia State, Georgia Tech and Emory. He is the author of more than 900 full journal articles. His work includes the development of flexible methods to analyze neuroimaging data including blind source separation, deep learning, multimodal fusion and genomics, neuroinformatics tools. Calhoun is a fellow of the Institute of Electrical and Electronic Engineers, The American Association for the Advancement of Science, The American Institute of Biomedical and Medical Engineers, The American College of Neuropsychopharmacology, The Organization for Human Brain Mapping (OHBM) and the International Society of Magnetic Resonance in Medicine. He currently serves on the IEEE BISP Technical Committee and is also a member of IEEE Data Science Initiative Steering Committee as well as the IEEE Brain Technical Committee.

Ahmet Coskun is a systems biotechnologist and bioengineer, working at the nexus of multiplex imaging and quantitative cell biology.

Single Cell Biotechnology Lab is strategically positioned for imaging one cell at a time for spatial context. We are multi-disciplinary researchers interested in photons, ions, and electrons and their interactions with cells and tissues.  Using large-scale experiments and computational analysis, we address fundamental challenges in cancers, immunology, and pediatric diseases. Variability of single cell profiles can be used to understand differences in therapeutic response, as well as satisfy our curiosity on understanding how cells are spatially organized in nature.

Our lab aims to deliver biotechnologies for spatial multi-omics profiling vision at the single cell level.

1) Spatial genomics: Our lab was part of an early efforts to demonstrate spatially resolved RNA profiling in single cells using a sequential FISH method. We will continue leveraging seqFISH and correlation FISH (another computational RNA imaging method) for exploring spatial dynamics of cellular societies.

2) Spatial proteomics: Our lab develops expertise on antibody-oligonucleotide based barcoding for multiplex protein imaging using CODEX technology. We combine CODEX with super-resolution and 3D imaging to visualize and quantify subcellular epigenetic states of immune and cancer cells.

3) Spatial metabolomics: Our lab works on computational and isotope barcoding approaches for small molecule profiling using MIBI (Multiplexed ion beam imaging). 3D and subcellular metabolic state of individual cells are used to model functional modes of cellular decision making in health and disease.

We also develop machine learning and deep learning algorithms to make sense of imaging based single cell big data.

In a nutshell, we create image-based ‘omic technologies to reveal spatial nature of biological systems. We benefit from enabler tools:  Super-resolution bioimaging, barcoded biochemical reagents, advanced algorithms and automated microfludics. Topical interests include Spatial Biology, Liquid Biopsy, and Global Oncology.

Ahmet Coskun trained at Stanford (Postdoc/Instructor with Garry Nolan), Caltech (Postdoc with Long Cai) and UCLA (PhD with Aydogan Ozcan). His lab is currently funded by NIH K25, BWF CASI, Georgia Tech & Emory.