Saumya Jain

Saumya Jain
sjain738@gatech.edu
The Jain Lab @ GT

Saumya Jain is an Assistant Professor in the School of Biological Sciences. He received a B.Tech and an M.Tech in Biochemical Engineering and Biotechnology from the Indian Institute of Technology, Delhi and a Ph.D. in Molecular and Cellular Biology from the University of Arizona. He conducted postdoctoral work at the University of California, Los Angeles as a Helen Hay Whitney Fellow in the lab of Dr. Larry Zipursky. His research focuses on the regulation of gene expression in developing nervous systems across space and time.

Animal brains consist of a vast number of neurons (~100 billion in humans, ~100 million in mice), and thousands of neuron-types. These neurons generated at different times and locations in the developing brain come together in precise ways to form specific connections (~100 trillion connections in the human brain). Even subtle defects in wiring are associated with conditions such as autism, schizophrenia and epilepsy. How does biology ensure the assembly of such a complex structure? A key piece of this puzzle is ensuring that the right set of genes are expressed at the right time and in the right place. The Jain lab is trying to address the following questions: 1) How are the timing and cell-type specificity of gene expression controlled in developing neurons to ensure proper circuit formation? 2) How are these mechanisms perturbed in neurodevelopmental disorders? To address these questions, the lab applies single-cell genomics, genetics and molecular biology approaches in the developing mouse and fruit fly visual systems.

Assistant Professor
Phone
4043858531
Office
EBB 3015
Additional Research
  • Bioinformatics
  • Computational Genomics
  • Neuroscience

 

Saumya
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Ashok Goel

Ashok Goel
ashok.goel@cc.gatech.edu
Design & Intelligence Laboratory

Ashok Goel is a Professor of Computer Science in the School of Interactive Computing at Georgia Institute of Technology in Atlanta, USA. He obtained his Ph.D. from The Ohio State University. At Georgia Tech, he is also the Director of the Ph.D. Program in Human-Centered Computing, a Co-Director of the Center for Biologically Inspired Design, and a Fellow of Brook Byers Institute for Sustainable Systems. For more than thirty years, Ashok has conducted research into artificial intelligence, cognitive science and human-centered computing, with a focus on computational design, modeling and creativity. His recent work has explored design thinking, analogical thinking and systems thinking in biological inspired design (https://www.youtube.com/watch?v=wiRDQ4hr9i8), and his research is now developing virtual research assistants for modeling biological systems. Ashok teaches a popular course on knowledge-based AI as part of Georgia Tech's program on Online Masters of Science in Computer Science. He has pioneered the development of virtual teaching assistants, such as Jill Watson, for answering questions in online discussion forums (https://www.youtube.com/watch?v=WbCguICyfTA). Chronicle of Higher Education recently called virtual assistants exemplified by Jill Watson as one of the most transformative educational technologies in the digital era. Ashok is the Editor-in-Chief of AAAI's AI Magazine.

Professor; School of Interactive Computing
Director| Ph.D. program in Human-Centered Computing; College of Computing
Co-Director; Center for Biologically Inspired Design
Fellow; Brook Byers Institute for Sustainable Systems
Office
GVU/TSRB
Additional Research

Artificial Intelligence; Cognitive Science; Computational Design; Computational Creativity; Educational Technology; Design Science; Learning Science and Technology; Human-Centered Computing

Google Scholar
https://scholar.google.com/citations?hl=en&user=VjNg25EAAAAJ&view_op=list_works&sortby=pubdate
Ashok
Goel
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Alan Ritter

Associate Professor Alan Ritter
alan.ritter@cc.gatech.edu
Personal Website

Alan Ritter is an associate professor in the School of Interactive Computing at Georgia Tech. His research interests include natural language processing, information extraction, and machine learning. He completed his Ph.D. at the University of Washington and was a postdoctoral fellow in the Machine Learning Department at Carnegie Mellon.  His research aims to solve challenging technical problems that can help machines learn to read vast quantities of text with minimal supervision.  His work has been featured in the press including WIRED, TNW and VentureBeat.  Alan is the recipient of an NSF CAREER, an Amazon Research Award, a Sony Faculty Innovation Award, and several paper awards presented at the Annual Meeting of the Association for Computational Linguistics.

Associate Professor
Office
CODA 1157B
Additional Research
  • AI
  • Large Language Models
  • Natural Language Processing
Google Scholar
https://scholar.google.com/citations?hl=en&user=unXtH3IAAAAJ&view_op=list_works&sortby=pubdate
LinkedIn Profile
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Alberto Dainotti

Associate Professor Alberto Dainotti
dainotti@gatech.edu
Internet Intelligence Lab @ Georgia Tech

Alberto Dainotti is an Associate Professor in the School of Computer Science at the College of Computing at Georgia Tech where is the Director of the Internet Intelligence Lab. His research is at the intersection of Internet measurement, data science and cybersecurity. He is interested in understanding when and how Internet infrastructure can fail and proposing remedies. To this end, he develops methods and builds near-real-time streaming data analytics systems (IODA, BGPStream, GRIP) that combine diverse data to monitor and improve Internet infrastructure security and reliability. He is also interested in understanding political motivations and implications of Internet cybersecurity events and phenomena. Before joining Georgia Tech, he was an Associate Research Scientist and Principal Investigator at CAIDA, the Center for Applied Internet Data Analysis at the San Diego Supercomputer Center, University of California San Diego. He received my Ph.D. in Computer Engineering and Systems at University of Napoli "Federico II", Italy, in 2008.

Associate Professor
Phone
Office
Klaus Advanced Computing Building, #3336
Additional Research
  • Data Analytics
  • Internet Data Science
  • Internet & Democracy
  • Networking, Systems, Security
  • Network Measurements

 

Google Scholar
https://scholar.google.com/citations?hl=en&user=oZNdAREAAAAJ&view_op=list_works&sortby=pubdate
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Peter Kasson

Peter Kasson
peter.kasson@chemistry.gatech.edu
https://kassonlab.org/

Peter Kasson is an international leader in the study of biological membrane structure, dynamics, and fusion, with particular application to how viruses gain entry to cells. His group performs both high-level experimental and computational work – a powerful combination that is critical to advancing our understanding of this important problem. His publications describe inventive approaches to the measurement of viral fusion rates and characterization of fusion mechanisms, and to the modeling of large-scale biomolecular and lipid assemblies. He has applied these insights to the prediction of pandemic outbreaks and drug resistance, with particular attention to Zika, SARS-CoV-2, and influenza pathogens in recent years. See https://kassonlab.org/ for more information.

Professor of Chemistry and Biomedical Engineering
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Saurabh Sinha, Ph.D.

Saurabh Sinha, Ph.D.
Lab

Saurabh Sinha received his Ph.D. in Computer Science from the University of Washington, Seattle, in 2002, and after post-doctoral work at the Rockefeller University with Eric Siggia, he joined the faculty of the University of Illinois, Urbana-Champaign, in 2005, where he held the positions of Founder Professor in Computer Science and Director of Computational Genomics in the Carl R. Woese Institute for Genomic Biology until 2022. He joined Georgia Institute of Technology in 2022, as Wallace H. Coulter Distinguished Chair in Biomedical Engineering, with joint appointments in Biomedical Engineering and Industrial & Systems Engineering. Sinha’s research is in the area of bioinformatics, with a focus on regulatory genomics and systems biology. Sinha is an NSF CAREER award recipient and has been funded by NIH, NSF and USDA. He co-directed an NIH BD2K Center of Excellence and was a thrust lead in the NSF AI Institute at UIUC. He led the educational program of the Mayo Clinic-University of Illinois Alliance, and co-led data science education for the Carle Illinois College of Medicine. Sinha has served as Program co-Chair of the annual RECOMB Regulatory and Systems Genomics conference and served on the Board of Directors for the International Society for Computational Biology (2018-2021). He was a recipient of the University Scholar award of the University of Illinois, and selected as a Fellow of the AIMBE in 2018.

Wallace H. Coulter Distinguished Chair in Biomedical Engineering
Professor
Office
3108 UAW
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Vida Jamali

Vida Jamali
vida@gatech.edu
Jamali Lab

Vida Jamali earned her Ph.D. in chemical and biomolecular engineering from Rice University under the guidance of Professor Matteo Pasquali and her B.S. in chemical engineering from Sharif University of Technology. Jamali was a postdoctoral researcher in Professor Paul Alivisato's lab at UC Berkeley and Kavli Energy Nanoscience Institute before joining Georgia Tech. The Jamali Research Group uses experimental, theoretical, and computational tools such as liquid phase transmission electron microscopy, rheology, statistical and colloidal thermodynamics, and machine learning to study the underlying physical principles that govern the dynamics, statistics, mechanics, and self-organization of nanostructured soft materials, in and out of thermal equilibrium, from both fundamental and technological aspects.

Assistant Professor, School of Chemical and Biomolecular Engineering
Phone
404.894.5134
Office
ES&T 1222
Additional Research

Studying dynamics and self-assembly of nanoparticles and macromolecules in heterogeneous chemical and biological environmentsInvestigating individual to collective behavior of active nanomachinesHarnessing the power of machine learning to understand physical rules governing nanostructured-soft materials, design autonomous microscopy experimentation for inverse material design, and develop new statistical and thermodynamic models for multiscale phenomena

ChBE Profile Page
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Peng Qiu

Peng Qiu
peng.qiu@bme.gatech.edu
Website

Peng Qiu is a professor in the Wallace H. Coulter Department of Biomedical Engineering at Georgia Tech School of Engineering and Emory University School of Medicine. 

His research interests are in the areas of bioinformatics and computational biology, focusing on machine learning, data integration, statistical signal processing, control systems and optimization. 

In particular, he is interested in developing machine learning methods to advance single-cell data science, with applications in characterizing cellular heterogeneity, identifying cancer biomarkers, understanding disease progression, reconstructing gene regulatory networks, etc.

Professor
Phone
404-385-1656
Office
EBB 2107
Additional Research
  • Computational Biology
  • Machine Learning
Google Scholar
https://scholar.google.com/citations?user=huPJapcAAAAJ
Coulter Department of Biomedical Engineering
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Anqi Wu

Anqi Wu
anqiwu@gatech.edu
Anqi Wu Research

Anqi Wu is an Assistant Professor at the School of Computational Science and Engineering (CSE), Georgia Institute of Technology. She was a Postdoctoral Research Fellow at the Center for Theoretical Neuroscience, the Zuckerman Mind Brain Behavior Institute, Columbia University. She received her Ph.D. degree in Computational and Quantitative Neuroscience and a graduate certificate in Statistics and Machine Learning from Princeton University. Anqi was selected for the 2018 MIT Rising Star in EECS, 2022 DARPA Riser, and 2023 Alfred P. Sloan Fellow. Her research interest is to develop scientifically-motivated Bayesian statistical models to characterize structure in neural data and behavior data in the interdisciplinary field of machine learning and computational neuroscience. She has a general interest in building data-driven models to promote both animal and human studies in the system and cognitive neuroscience.

Assistant Professor
Phone
323-868-1604
Research Focus Areas
BRAin INtelligence and Machine Learning (BRAINML) Laboratory
Anqi
Wu, Ph.D.
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Ahmet Coskun

Ahmet Coskun
acoskun7@gatech.edu
Website

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.

Associate Professor of Biomedical Engineering
Phone
404.894.3866
Office
Petit Biotechnology Building, Office 1311
Additional Research

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.

University, College, and School/Department
Google Scholar
https://scholar.google.com/citations?user=4MR2wSIAAAAJ&hl=en
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