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.
The Single Cell Biotechnology Lab aims to study spatial biology in health and disease. Our research lies at the nexus of multiplex bioimaging, microfluidic biodynamics, and big data biocomputation. Using high-dimensional nanoscale imaging datasets, we address fundamental challenges in immuno-engineering, cancers, and pediatric diseases. Our lab pursues a transformative multi-omics technology to integrate spatially resolved epigenetics and spatial genomics, proteomics, and metabolomics, all in the same platform. We uniquely benefit from super-resolution microscopy, imaging mass spectrometry, combinatorial molecular barcoding, and machine learning to enhance the information capacity of our cellular data. Variability of single cell images can be used to understand differences in therapeutic responses, as well as satisfy our curiosity on understanding how cells are spatially organized in nature.