James Gumbart

James Gumbart
gumbart@physics.gatech.edu

My lab is focused on understanding how proteins and other biological systems function at a molecular level. To probe these systems, we carry out molecular dynamics simulations, modeling biological behavior one atom at a time. The simulations serve as a "computational microscope" that permits glimpses into a cell's inner workings through the application of advanced software and high-powered supercomputers. We are particularly interested in how bacteria utilize unique pathways to synthesize proteins and insert them into both the inner and outer membranes, how they import nutrients across two membranes, and how their cell walls provide shape and mechanical strength.

Associate Professor
Phone
404-385-0797
Office
Howey W202
Additional Research

Computational Chemistry

IRI/Group and Role
Bioengineering and Bioscience > Faculty
Data Engineering and Science > Faculty
Data Engineering and Science
Bioengineering and Bioscience
University, College, and School/Department
Georgia Institute of Technology > College of Sciences > School of Physics

Martha Grover

Martha Grover
martha.grover@chbe.gatech.edu

Grover’s research activities in process systems engineering focus on understanding macromolecular organization and the emergence of biological function. Discrete atoms and molecules interact to form macromolecules and even larger mesoscale assemblies, ultimately yielding macroscopic structures and properties. A quantitative relationship between the nanoscale discrete interactions and the macroscale properties is required to design, optimize, and control such systems; yet in many applications, predictive models do not exist or are computationally intractable.

The Grover group is dedicated to the development of tractable and practical approaches for the engineering of macroscale behavior via explicit consideration of molecular and atomic scale interactions. We focus on applications involving the kinetics of self-assembly, specifically those in which methods from non-equilibrium statistical mechanics do not provide closed form solutions. General approaches employed include stochastic modeling, model reduction, machine learning, experimental design, robust parameter design, and estimation.

Professor, School of Chemical and Biomolecular Engineering
James Harris Faculty Fellow, School of Chemical and Biomolecular Engineering
Member, NSF/NASA Center for Chemical Evolution
Phone
404.894.2878
Office
ES&T 1228
Additional Research

Colloids; Crystallization; Organic and Inorganic Photonics and Electronics; Polymers; Discrete atoms and molecules interact to form macromolecules and even larger mesoscale assemblies, ultIMaTely yielding macroscopic structures and properties. A quantitative relationship between the nanoscale discrete interactions and the macroscale properties is required to design, optimize, and control such systems; yet in many applications, predictive models do not exist or are computationally intractable. The Grover group is dedicated to the development of tractable and practical approaches for the engineering of macroscale behavior via explicit consideration of molecular and atomic scale interactions. We focus on applications involving the kinetics of self-assembly, specific those in which methods from non-equilibrium statistical mechanics do not provide closed form solutions. General approaches employed include stochastic modeling, model reduction, machine learning, experimental design, robust parameter design, estIMaTion, and optimal control, monitoring and control for nuclear waste processing and polymer organic electronics

IRI/Group and Role
Bioengineering and Bioscience > Faculty
Data Engineering and Science > Faculty
Energy > Research Community
Data Engineering and Science
Bioengineering and Bioscience
Energy
University, College, and School/Department
Georgia Institute of Technology > College of Engineering > School of Chemical and Biomolecular Engineering
Research Areas
Energy
  • Nuclear
  • AI Energy Nexus

Santiago Grijalva

Santiago Grijalva
sgrijalva@ece.gatech.edu

Dr. Grijalva joined the Georgia Institute of Technology in the summer of 2009 as Associate Professor of Electrical and Computer Engineering. He is the Director of the Advanced Computational Electricity Systems (ACES) Laboratory, where he conducts research on real-time power system control, informatics, and economics, and renewable energy integration in power. From 2012-2015, Dr. Grijalva served as the Strategic Energy Institute (SEI) Associate Director for Electricity Systems, responsible for coordinating large efforts on electricity research and policy at Georgia Tech. Dr. Grijalva received the Electrical Engineer degree from EPN-Ecuador in 1994, the M.S. Certificate in Information Systems from ESPE-Ecuador in 1997, and the M.S. and Ph.D. degrees in Electrical Engineering from the University of Illinois at Urbana-Champaign in 1999 and 2002, respectively. He was a post-doctoral fellow in Power and Energy Systems at the University of Illinois from 2003 to 2004. From 1995 to 1997, he was with the Ecuadorian National Center for Energy Control (CENACE) as engineer and manager of the Real-Time EMS Software Department. From 2002 to 2009, he was with PowerWorld Corporation as a senior software architect and developer of innovative real-time and optimization applications used today by utilities, control centers, and universities in more than 60 countries. Dr. Grijalva is a leading researcher on ultra-reliable architectures for critical energy infrastructures. He has pioneered work on de-centralized and autonomous power system control, renewable energy integration in power, and unified network models and applications. He is currently the principal investigator of various future electricity grid research projects for the US Department of Energy, ARPA-E, EPRI, PSERC as well as other Government organizations, research consortia, and industrial sponsors. Research interests: Power system and smart grid computation De-centralized and autonomous power control architectures Ultra-reliable electricity internetworks Seamless integration of large-scale renewable energy Electricity markets design and power system economics

Professor; Associate Director for Electricity Strategic Energy Institute (SEI); Georgia Power Distinguished Professor
Phone
(404) 894-2974
Office
VL E284
Additional Research
  • AI for Power Generation
  • Electrical Grid
  • Energy Storage
  • System Design & Optimization
IRI/Group and Role
Data Engineering and Science > Faculty
Energy > Research Community
Data Engineering and Science
Energy
University, College, and School/Department
Georgia Institute of Technology > College of Engineering > School of Electrical and Computer Engineering
Research Areas
Energy
  • Energy Systems, Grid Resilience, and Cybersecurity
  • AI Energy Nexus
  • Energy Economics, Policy, and Public Health
  • Energy and National Security
  • Energy Storage
  • Electric Vehicles

Ashok Goel

Ashok Goel
ashok.goel@cc.gatech.edu

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

IRI/Group and Role
Data Engineering and Science > Faculty
People and Technology > Affiliated Faculty
Robotics > Core Faculty
Sustainable Systems
Data Engineering and Science
People and Technology
Tech AI > ITAB
University, College, and School/Department
Georgia Institute of Technology > College of Computing > School of Interactive Computing
Research Areas
Artificial Intelligence

Greg Gibson

Greg Gibson
greg.gibson@biology.gatech.edu

Greg Gibson is Professor of Biology and Director of the Center for Integrative Genomics at Georgia Tech. He received his BSc majoring in Genetics from the University of Sydney (Australia) and PhD in Developmental Genetics from the University of Basel. After transitioning to quantitative genetic research as a Helen Hay Whitney post-doctoral fellow at Stanford University, he initiated a program of genomic research as a David and Lucille Packard Foundation Fellow at the University of Michigan. He joined the faculty at Georgia Tech in Fall of 2009, after ten years at North Carolina State University where he developed tools for quantitative gene expression profiling and genetic dissection of development in the fruitfly Drosophila. He is now collaborating with the Center for Health Discovery and Well Being on integrative genomic analyses of the cohort. Dr Gibson is an elected Fellow of the American Association for the Advancement of Science, and serves as Section Editor for Natural Variation for PLoS Genetics. He has authored a prominent text-book, a "Primer of Genome Science" as well as a popular book about genetics and human health, "It Takes a Genome".

Professor
Director, Center for Integrative Genomics
Adjunct Professor, School of Medicine, Emory University
Phone
404-385-2343
Office
EBB 2115A
Additional Research
Quantitative Evolutionary Genetics. After 15 years working on genomic approaches to complex traits in Drosophila, my group has spent much of the past 10 years focusing on human quantitative genetics. We start with the conviction that genotype-by-environment and genotype-by-genotype interactions are important influences at the individual level (even though they are almost impossible to detect at the population level). We use a combination of simulation studies and integrative genomics approaches to study phenomena such as cryptic genetic variation (context-dependent genetic effects) and canalization (evolved robustness) with the main focus currently on disease susceptibility.​ Immuno-Transcriptomics.As one of the early developers of statistical approaches to analysis of gene expression data, we have a long-term interest in applications of transcriptomics in ecology, evolution, and lately disease progression. Since blood is the mostaccessible human tissue, we've examined how variation is distributed within and among populations, across inflammatory and auto-immune states, and asked how it relates to variation in immune cell types. Our axes-of-variation framework provides a new way of monitoring lymphocyte, neutrophil, monocyte and reticulocyte profiles from whole peripheral blood. Most recently we have also been collaborating on numerous studies of specific tissues or purified cell types in relation to such diseases as malaria, inflammatory bowel disease, juvenile arthritis, lupus, and coronary artery disease. Predictive Health Genomics. Personalized genomic medicine can be divided into two domains: precision medicine and predictive health. We have been particularly interested in the latter, asking how environmental exposures and gene expression, metabolomic and microbial metagenomics profiles can be integrated with genomesequencing or genotyping to generate health risk assessments. A future direction is incorporation of electronic health records into genomic analyses of predictive health. Right now it is easier to predict the weather ten years in advance than loss of well-being, but we presume that preventative medicine is a big part of the future of healthcare.​
IRI/Group and Role
Bioengineering and Bioscience > Faculty
Data Engineering and Science > Faculty
Data Engineering and Science
Bioengineering and Bioscience
University, College, and School/Department
Georgia Institute of Technology > College of Sciences > School of Biological Sciences

Ada Gavrilovska

Ada Gavrilovska
ada@cc.gatech.edu

Ada Gavrilovska is an Associate Professor at the College of Computing and a researcher with the Center for Experimental Research in Computer Systems (CERCS) at Georgia Tech. Her interests include experimental systems, focusing on operating systems, virtualization, and systems software for heterogeneous many-core platforms, emerging non-volatile memories, large scale datacenter and cloud systems, high-performance communication technologies and support for novel end-user devices and services. Her research is supported by the National Science Foundation, the US Department of Energy, and industry grants, including from Cisco, HP, IBM, Intel, Intercontinental Exchange, LexisNexis, VMware, and others. She has published numerous book chapters, journal and conference publications, and edited a book “High Performance Communications: A Vertical Approach” (CRC Press, 2009). In addition to research, she also teaches courses on operating systems and high performance communications. She has a Bachelor's  in Computer Engineering from University Sts. Cyril and Methodius in Macedonia ('98), and a Master's ('99) and Ph.D. ('04) degrees in Computer Science from Georgia Tech.

Senior Research Scientist
Phone
404.894.0387
Additional Research

Cloud Security; Large-Scale or Distributed Systems; Cloud Systems; Virtualizations; Operating Systems

IRI/Group and Role
Data Engineering and Science > Faculty
Data Engineering and Science
University, College, and School/Department
Georgia Institute of Technology > College of Computing > School of Computer Science
Research Areas
Artificial Intelligence

Hamid Garmestani

Hamid Garmestani
hamid.garmestani@mse.gatech.edu

Hamid Garmestani is a professor in the School of Materials Science and Engineering at the Georgia Institute of Technology. He received his education from Cornell University (Ph.D. 1989 in Theoretical and Applied Mechanics) and the University of Florida (B.S. 1982 in Mechanical Engineering, M.S. 1984 in Materials Science and Engineering). After serving a year as a post-doctoral fellow at Yale University, he joined the Mechanical Engineering Department at Florida State University (FAMU-FSU College of Engineering) in 1990. 

Primary research and teaching interests include microstructure/property relationship in textured polycrystalline materials, composites, superplastic, magnetic and thin film layered structures. He uses phenomenological and statistical mechanics models in a computational framework to investigate microstructure and texture (micro-texture) evolution during processing and predict effective properties (mechanical, transport and magnetic). His present research interests are processing of fuel cell materials and modeling of their transport and mechanical properties.

Garmestani has been the recipient of a research award (FAR) through NASA in  1997. He received the Superstar in  Research award in 1999 by FSU-CRC.  He  has also been the recipient of the Engineering Research Award at the FAMU-FSU College of Engineering, Spring 2000. He is a member of the editorial board of the International Journal of Plasticity and board of reviewers for journal of Metal Transaction.  He is presently funded through NSF (MRD), NASA, Air Force and the Army.

Professor, School of Materials Science and Engineering
Phone
404.385.4495
Office
Love 361
Additional Research

computational mechanics; micro and nanomechanics; Electrical charge storage and transport; Fuel Cells

IRI/Group and Role
Manufacturing > Affiliated Faculty
Data Engineering and Science > Faculty
Manufacturing
Data Engineering and Science
University, College, and School/Department
Georgia Institute of Technology > College of Engineering > School of Materials Science Engineering
Research Areas
Artificial Intelligence

Lu Gan

Lu Gan
lgan@gatech.edu

Lu Gan joined the Daniel Guggenheim School of Aerospace Engineering at the Georgia Institute of Technology as an Assistant Professor in January 2024. She leads the Lu's Navigation and Autonomous Robotics (Lunar) Lab at Georgia Tech, and is on the core faculty of the Institute for Robotics and Intelligent Machines. Her research interests include robot perception, robot learning, and autonomous navigation. Her group explores the use of computer vision, machine learning, estimation, probabilistic inference, kinematics and dynamics to develop autonomous systems in ground, air, and space applications.

She holds a B.S. in Automation from the University of Electronic Science and Technology of China, an M.S. in Control Engineering from Beihang University, and received her M.S. and Ph.D. in Robotics from the University of Michigan, Ann Arbor. Before joining Georgia Tech, she had a two-year appointment as a Postdoctoral Scholar at the Graduate Aerospace Laboratories of the California Institute of Technology and the Center for Autonomous Systems and Technologies at Caltech.

Assistant Professor - School of Aerospace Engineering
Office
Guggenheim 448A
Additional Research

Computer VisionPerception & NavigationRobot AutonomyFlight Mechanics & ControlsHuman-Robot Interaction

IRI/Group and Role
Data Engineering and Science > Faculty
Robotics > Core
Data Engineering and Science
Robotics
University, College, and School/Department
Georgia Institute of Technology > College of Engineering > Guggenheim School of Aerospace Engineering
Research Areas
Artificial Intelligence

Victor Fung

Victor Fung
victorfung@gatech.edu

Victor Fung is an Assistant Professor in the School of Computational Science and Engineering. Prior to this position, he was a Wigner Fellow and a member of the Nanomaterials Theory Insitute in the Center for Nanophase Materials Sciences at Oak Ridge National Laboratory. A physical chemist by training, Fung now works at the intersection of scientific artificial intelligence, computing, and materials science/chemistry.

Assistant Professor of Computational Science and Engineering
Office
E1354B | CODA Building, 756 W Peachtree St NW, Atlanta, GA 30308
Additional Research

Quantum chemistrySurrogate models for quantum chemistryData-driven inverse designChemically-informed machine learningHigh-throughput computational simulations

IRI/Group and Role
Data Engineering and Science > Faculty
Energy > Faculty
Matter and Systems > Affiliated Faculty
Data Engineering and Science
Energy
University, College, and School/Department
Georgia Institute of Technology > College of Computing > School of Computational Science and Engineering
Research Areas
Artificial Intelligence

Steven French

Steven French
steven.french@design.gatech.edu

Steven French is Senior Vice President and Chief Information Officer at Veracyte.. He brings more than 20 years of information and operational leadership experience in the life sciences and technology industries to his role at Veracyte. 

Prior to joining Veracyte in July 2022, Mr. French most recently served as President of a consultancy advising leading biotech companies on information technology strategy, cybersecurity, acquisitions and infrastructure integration, and business operations. He previously served as Chief Information Officer at Celularity, a clinical-stage biotechnology company. Prior to that, Mr. French was Vice President of Technology Development at Human Longevity, Inc., a San Diego-based venture focused on building a comprehensive database of human genotypes and phenotypes, where he developed and implemented the infrastructure for key data management strategies. Earlier, Mr. French was Co-Founder and Vice President of Strategy and Technology at Epic Sciences, a diagnostics company focused on advancing the treatment and management of cancer, where he established key strategies for information technology, software development, and quality systems. 

Mr. French holds a B.B.A. and an M.B.A from the University of San Diego.

Dean and John Portman Chair, College of Design
IRI/Group and Role
Data Engineering and Science > Faculty
Data Engineering and Science