The research in our group bridges the gap between applied electronic structure theory and first-principles molecular simulation to enable predictive computational discovery of new materials and new chemistry. This research relies heavily on sophisticated high-performance and high-throughput computing paradigms, employing modern graphics processing unit (GPU) based computing. A primary focus is electrochemistry and electrochemical energy storage applications, and we seek to develop a fundamental understanding of how redox chemistry and other chemical and physical processes are modulated by strong electric fields. We are interested in chemical reaction mechanisms within highly ionic and heterogeneous environments, and are developing multi-scale modeling approaches to study chemical reactivity in the condensed phase. This method development includes novel QM/MM approaches and machine-learning reactive force fields, which are combined with enhanced sampling molecular dynamics/Monte Carlo techniques. Please see our research group website for more details!

Nicoleta Serban is the Peterson Professor of Pediatric Research in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech.

Dr. Serban's most recent research focuses on model-based data mining for functional data, spatio-temporal data with applications to industrial economics with a focus on service distribution and nonparametric statistical methods motivated by recent applications from proteomics and genomics. 

She received her B.S. in Mathematics and an M.S. in Theoretical Statistics and Stochastic Processes from the University of Bucharest. She went on to earn her Ph.D. in Statistics at Carnegie Mellon University.

Dr. Serban's research interests on Health Analytics span various dimensions including large-scale data representation with a focus on processing patient-level health information into data features dictated by various considerations, such as data-generation process and data sparsity; machine learning and statistical modeling to acquire knowledge from a compilation of health-related datasets with a focus on geographic and temporal variations; and integration of statistical estIMaTes into informed decision making in healthcare delivery and into managing the complexity of the healthcare system.

Kamran Paynabar is the Fouts Family Early Career Professor and Associate Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. He received his B.Sc. and M.Sc. in Industrial Engineering from Iran in 2002 and 2004, respectively, and his Ph.D. in Industrial and Operations Engineering from The University of Michigan in 2012. He also holds an M.A. in Statistics from The University of Michigan. His research interests comprise both applied and methodological aspects of machine-learning and statistical modeling integrated with engineering principles. He is a recipient of the INFORMS Data Mining Best Student Paper Award, the Best Application Paper Award from IIE Transactions, the Best QSR refereed paper from INFORMS, and the Best Paper Award from POMS. He has been recognized with the Georgia Tech campus level 2014 CETL/BP Junior Faculty Teaching Excellence Award and the Provost Teaching and Learning Fellowship. He served as the chair of QSR of INFORMS, and the president of QCRE of IISE.

Milton Mueller is an internationally prominent scholar specializing in the political economy of information and communication. The author of seven books and scores of journal articles, his work informs not only public policy but also science and technology studies, law, economics, communications, and international studies. His books Networks and States: The global politics of Internet governance (MIT Press, 2010) and Ruling the Root: Internet Governance and the Taming of Cyberspace (MIT Press, 2002) are acclaimed scholarly accounts of the global governance regime emerging around the Internet. Mueller’s research employs the theoretical tools of institutional economics, STS and political economy, as well as historical, qualitative and quantitative methods. Mueller’s prominence in scholarship is matched by his prominence in policy practice. He is the co-founder and co-director of the Internet Governance Project (IGP), a policy analysis center for global Internet governance. Since its founding in 2004, IGP has played a prominent role in shaping global Internet policies and institutions such as ICANN and the Internet Governance Forum. He has participated in proceedings and policy development activities of ICANN, the International Telecommunications Union (ITU), the National Telecommunications and Information Administration (NTIA) and regulatory proceedings in the European Commission, China, Hong Kong and New Zealand. He has served as an expert witness in prominent legal cases related to domain names and telecommunication policy. He was recently elected to the advisory committee of the American Registry for Internet Numbers (ARIN), and appointed in 2014 to the IANA Stewardship Coordination Group. Mueller has also been a practical institution-builder in the scholarly world, where he led the creation of the Global Internet Governance Academic Network (GigaNet), an international association of scholars.

Bjarne Kreitz is an incoming Assistant Professor of Chemical Engineering at Georgia Tech. Kreitz received a B.Sc. and M.Sc. in Chemical Engineering from Clausthal University of Technology (Germany). He obtained his Dr.-Ing. in Chemical Engineering from Clausthal University of Technology under the supervision of Prof. Thomas Turek, working on the microkinetic investigation of the transient methanation with experiments and multiscale modeling. 

Kreitz conducted postdoctoral work at Brown University with Prof. Franklin Goldsmith with a Feodor Lynen Postdoctoral Scholarship from the Alexander von Humboldt Foundation. Before joining Brown, he worked briefly as a postdoc at the Karlsruhe Institute of Technology (Germany) in the group of Prof. Olaf Deutschmann.

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.

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.

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.

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.

Dr. Vijay Ganesh is a professor of computer science at the Georgia Institute of Technology. Prior to joining Georgia Tech in 2023, Vijay was a professor at the University of Waterloo in Canada from 2012 to 2023 and a research scientist at the Massachusetts Institute of Technology from 2007 to 2012. Vijay completed his PhD in computer science from Stanford University in 2007. Vijay's primary area of research is the theory and practice of SAT/SMT solvers, and their application in AI, software engineering, security, mathematics, and physics. In this context he has led the development of many SAT/SMT solvers, most notably, STP, Z3str4, AlphaZ3, MapleSAT, and MathCheck. He has also proved several decidability and complexity results in the context of first-order theories. More recently he has started working on topics at the intersection of learning and reasoning, especially the use of machine learning for efficient solvers, and the use of solvers aimed at making AI more trustworthy, secure, and robust. For his research, Vijay has won over 30 awards, honors, and medals to-date, including an ACM Impact Paper Award at ISSTA 2019, ACM Test of Time Award at CCS 2016, and a Ten-Year Most Influential Paper citation at DATE 2008.