Prof. Srijan Kumar is an Assistant Professor in the School of Computational Science and Engineering, College of Computing, Georgia Institute of Technology. His research develops data science solutions to address the high-stakes challenges on the web and in the society. He has pioneered the development of user models and network science tools to enhance the well-being and safety of people. Applications of his research widely span e-commerce, social media, finance, health, web, and cybersecurity. His methods to predict malicious users and false information have been widely adopted in practice (being used in production at Flipkart and Wikipedia) and taught at graduate level courses worldwide. He has received several awards including the ACM SIGKDD Doctoral Dissertation Award runner-up 2018, Larry S. Davis Doctoral Dissertation Award 2018, and best paper awards from WWW and ICDM. His research has been the subject of a documentary and covered in popular press, including CNN, The Wall Street Journal, Wired, and New York Magazine. He completed his postdoctoral training at Stanford University, received a Ph.D. in Computer Science from University of Maryland, College Park, and B.Tech. from Indian Institute of Technology, Kharagpur.

Siva is Fouts Family Early Career Professor and an Assistant Professor in the H. Milton Stewart School of Industrial & Systems Engineering at Georgia Tech.

Before joining Georgia Tech, he spent two years in the Stochastic Processes and Optimization group, which is part of the Mathematical Sciences Department at the IBM T. J. Watson Research Center. He received my Ph.D. in ECE from the University of Illinois at Urbana-Champaign in 2014 and was advised by Prof R. Srikant. Before that, he received an MS in ECE from UIUC, which was advised by Prof R. Srikant and Prof. Bruce Hajek. Maguluri also hold an MS in Applied Maths from UIUC. He obtained my B.Tech in Electrical Engineering from Indian Institute of Technology Madras.

Maguluri received the NSF CAREER award in 2021, 2017 Best Publication in Applied Probability Award from INFORMS Applied Probability Society, and the second prize in 2020 INFORMS JFIG best paper competition. Joint work with his students received the Stephen S. Lavenberg Best Student Paper Award at IFIP Performance 2021. As a recognition of his teaching efforts, Siva received the Student Recognition of Excellence in Teaching: Class of 1934 CIOS Award in 2020 for ISyE 6761 and the CTL/BP Junior Faculty Teaching Excellence Award, also in 2020, both presented by the Center for Teaching and Learning at Georgia Tech.

Santosh Vempala is a prominent computer scientist. He is a Distinguished Professor of Computer Science at the Georgia Institute of Technology. His main work has been in the area of Theoretical Computer Science. 

Vempala secured B.Tech. degree in Computer Science and Engineering from Indian Institute of Technology, Delhi, in 1992 then he attended Carnegie Mellon University, where he received his Ph.D. in 1997 under professor Avrim Blum. 

In 1997, he was awarded a Miller Fellowship at Berkeley. Subsequently, he was a professor at MIT in the Mathematics Department, until he moved to Georgia Tech in 2006. 

His main work has been in the area of theoretical computer science, with particular activity in the fields of algorithms, randomized algorithms, computational geometry, and computational learning theory, including the authorship of books on random projection and spectral methods. 

In 2008, he co-founded the Computing for Good (C4G) program at Georgia Tech.

Vempala has received numerous awards, including a Guggenheim Fellowship, Sloan Fellowship, and being listed in Georgia Trend's 40 under 40.[5] He was named Fellow of ACM "For contributions to algorithms for convex sets and probability distributions" in 2015.[6] He was named a Fellow of the American Mathematical Society, in the 2022 class of fellows, "for contributions to randomized algorithms, high-dimensional geometry, and numerical linear algebra, and service to the profession".

Richard (Rich) Vuduc is an Associate Professor at the Georgia Institute of Technology (“Georgia Tech”), in the School of Computational Science and Engineering, a department devoted to the study of computer-based modeling and simulation of natural and engineered systems. His research lab, The HPC Garage (@hpcgarage), is interested in high-performance computing, with an emphasis on algorithms, performance analysis, and performance engineering. He is a recipient of a DARPA Computer Science Study Groupgrant; an NSF CAREER award; a collaborative Gordon Bell Prize in 2010; Lockheed-Martin Aeronautics Company Dean’s Award for Teaching Excellence (2013); and Best Paper Awards at the SIAM Conference on Data Mining (SDM, 2012) and the IEEE Parallel and Distributed Processing Symposium (IPDPS, 2015), among others. He has also served as his department’s Associate Chair and Director of its graduate programs. External to Georgia Tech, he currently serves as Chair of the SIAM Activity Group on Supercomputing (2018-2020); co-chaired the Technical Papers Program of the “Supercomputing” (SC) Conference in 2016; and serves as an associate editor of both the International Journal of High-Performance Computing Applications and IEEE Transactions on Parallel and Distributed Systems. He received his Ph.D. in Computer Science from the University of California, Berkeley, and was a postdoctoral scholar in the Center for Advanced Scientific Computing the Lawrence Livermore National Laboratory.

Ling Liu is a Professor in the School of Computer Science at Georgia Institute of Technology. She directs the research programs in Distributed Data Intensive Systems Lab (DiSL), examining various aspects of large scale big data systems and analytics, including performance, availability, security, privacy and trust. Prof. Liu is an elected IEEE Fellow and a recipient of IEEE Computer Society Technical Achievement Award (2012). She has published over 300 international journal and conference articles and is a recipient of the best paper award from numerous top venues, including ICDCS, WWW, IEEE Cloud, IEEE ICWS, ACM/IEEE CCGrid. In addition to serve as general chair and PC chairs of numerous IEEE and ACM conferences in big data, distributed computing, cloud computing, data engineering, very large databases fields, Prof. Liu served as the editor in chief of IEEE Transactions on Service Computing (2013-2016), on editorial board of over a dozen international journals. Ling’s current research is sponsored primarily by NSF and IBM.

Kaye Husbands Fealing is the Assistant Director of the Social, Behavioral and Economic Sciences at the National Science Foundation (NSF) and co-chair of the Subcommittee on Social and Behavioral Sciences of the Committee on Science of the National Science & Technology Council (NSTC). She is the former Dean of the Ivan Allen College of Liberal Arts at the Georgia Institute of Technology and a former Chair of the School of Public Policy Georgia Tech, where she currently holds the title professor. She specializes in science of science and innovation policy, the public value of research expenditures, and broadening participation in STEM fields and the workforce.

Prior to her positions at Georgia Tech, Husbands Fealing taught at the Humphrey School of Public Affairs, University of Minnesota, and she was a study director at the National Academy of Sciences. Prior to the Humphrey School, she was the William Brough professor of economics at Williams College, where she began her teaching career in 1989. She developed and was the inaugural program director for NSF's Science of Science and Innovation Policy program and co-chaired the Science of Science Policy Interagency Task Group, chartered by the Social, Behavioral and Economic Sciences Subcommittee of the NSTC. At NSF, she also served as an Economics Program director. Husbands Fealing was a visiting scholar at Massachusetts Institute of Technology’s Center for Technology Policy and Industrial Development, where she conducted research on NAFTA’s impact on the Mexican and Canadian automotive industries, and research on strategic alliances between aircraft contractors and their subcontractors.

Husbands Fealing is an elected member of the American Academy of Arts and Sciences, is an Elected Fellow of the National Academy of Public Administration, an Elected Fellow of the American Association for the Advancement of Science (AAAS). She was awarded the 2023 Carolyn Shaw Bell Award from the American Economic Association's Committee on the Status of Women in the Economics Profession, and the 2017 Trailblazer Award from the National Medical Association Council on Concerns of Women Physicians. She is a member of the International Women’s Forum-Georgia Chapter, and member of the YWCA's Academy of Women Achievers. She serves as a member on AAAS' Executive Board, the National Academy of Public Administration's board, the trustee board for the R. Howard Dobbs Jr. Foundation, and the Society for Economic Measurement's board. She has served on several committees and panels, including: AAAS committees; National Academies’ panels; Council of Canadian Academies panels; American Academy of Arts and Sciences working groups; NSF’s Social, Behavioral, and Economic Sciences Advisory Committee, STEM Education Advisory Committee, and the Committee on Equal Opportunities in Science and Engineering; NIH’s National Institute of General Medical Sciences Council; General Accountability Office’s Science, Technology Assessment, and Analytics Polaris Council; and American Economic Association’s Committee on the Status of Women in the Economic Profession. At Georgia Tech, she co-chaired the Arts@Tech Institute Strategic Planning committee, and she has served on the Institute for Data Engineering and Science Council, the Intellectual Property Advisory Board, and other committees.

Husbands Fealing holds a Ph.D. in economics from Harvard University, and a B.A. in mathematics and economics from the University of Pennsylvania.

Dr. Justin Romberg is the Schlumberger Professor and the Associate Chair for Research in the School of Electrical and Computer Engineering and the Associate Director for the Center for Machine Learning at Georgia Tech.

Dr. Romberg received the B.S.E.E. (1997), M.S. (1999) and Ph.D. (2004) degrees from Rice University in Houston, Texas. From Fall 2003 until Fall 2006, he was a Postdoctoral Scholar in Applied and Computational Mathematics at the California Institute of Technology. He spent the Summer of 2000 as a researcher at Xerox PARC, the Fall of 2003 as a visitor at the Laboratoire Jacques-Louis Lions in Paris, and the Fall of 2004 as a Fellow at UCLA's Institute for Pure and Applied Mathematics. In the Fall of 2006, he joined the Georgia Tech ECE faculty. In 2008 he received an ONR Young Investigator Award, in 2009 he received a PECASE award and a Packard Fellowship, and in 2010 he was named a Rice University Outstanding Young Engineering Alumnus. He is currently on the editorial board for the SIAM Journal on the Mathematics of Data Science, and is a Fellow of the IEEE.

His research interests lie on the intersection of signal processing, machine learning, optimization, and applied probability.

Dr. Duke has led over $21 million in funded research for industry, government, and foundation partners. Dr. Duke’s research focuses on advancing techniques for identifying patients of interest from diverse data sources with applications spanning research, quality, and clinical domains. He led the Merck-Regenstrief Partnership in Healthcare Innovation and was a founding member of OHDSI, an open-source international health data analytics collaborative. In addition to numerous peer-reviewed publications, his work has been featured in the lay media including the New York Times, NPR, and MSNBC. Dr. Duke completed his medical degree at Harvard Medical School and a master's in human-computer interaction at Indiana University.

Joel Sokol is the Harold E. Smalley Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. He is also Director of the interdisciplinary Master of Science in Analytics degree (on-campus and online).

His primary research interests are in sports analytics and applied operations research. He has worked with teams or leagues in all three of the major American sports. Dr. Sokol's LRMC method for predictive modeling of the NCAA basketball tournament is an industry leader, and his non-sports research has won the EURO Management Science Strategic Innovation Prize and been a finalist for the Cozzarelli Prize.

Dr. Sokol has also won recognition for his teaching and curriculum development from IIE and the NAE, held the Fouts Family Associate Professorship for a three-year term, and is the recipient of Georgia Tech's highest awards for teaching. He served two terms as INFORMS Vice President of Education, and is a past Chair and founding officer of the INFORMS section on sports operations research.

Dr. Sokol's Ph.D. in operations research is from MIT, and his bachelor's degrees in mathematics, computer science, and applied sciences in engineering are from Rutgers University.

I am currently a Senior Research Scientist at Georgia Tech working in the School of Computer Science in the College of Computing since 2015. Previously, I have worked as as a research scientist in the School of Computational Science and Engineering (CSE) from 2013 to 2015. This work focused on advanced user support and benchmarking for the Keeneland project and investigating architecture-related research topics for Dr. Jeff Vetter’s Future Technologies Group at Oak Ridge National Lab.

With a background in computer architecture, my main research interests are focused on the intersection of high-performance computing and novel accelerators including GPUs, Xeon Phi, FPGAs, and Arm SVE processors. I am currently working on a collaborative research program for near-memory computing with High Bandwidth Memory (HBM) for processors and GPUs, SuperSTARLU, which is funded by the NSF. I am co-director of Georgia Tech’s Center for High Performance Computing, and I am also the director of a novel architecture testbed, the CRNCH Rogues Gallery, that aims to simplify and democratize access to novel post-Moore accelerators in the neuromorphic, reversible, and novel networking spaces.

I defended my PhD in August 2013 in the area of computer architecture working under Dr. Sudhakar Yalamanchili. More information on this networks- and memory-related research can be found under the publications tab.