Chao Zhang is an Assistant Professor at the School of Computational Science and Engineering, Georgia Institute of Technology. His research area is data mining, machine learning, and natural language processing. His research aims to enable machines to understand text data in more label-efficient and robust way in open-world settings. Specific research topics include weakly-supervised learning, out-of-distribution generalization, interpretable machine learning, and knowledge extraction and reasoning. He is a recipient of Google Faculty Research Award, Amazon AWA Machine Learning Research Award, ACM SIGKDD Dissertation Runner-up Award, IMWUT distinguished paper award, and ECML/PKDD Best Student Paper Runner-up Award. Before joining Georgia Tech, he obtained his Ph.D. degree in Computer Science from University of Illinois at Urbana-Champaign in 2018.

Ellen Zegura, Ph.D., is a Professor and the Stephen Fleming Chair in Telecommunications at the School of Computer Science, College of Computing at the Georgia Institute of Technology. Zegura’s research concerns the development of wide-area (Internet) networking services and mobile wireless networking.  Wide-area services are utilized by applications that are distributed across multiple administrative domains (e.g., web, file sharing, multi-media distribution). Her focus is on services implemented both at the network layer, as part of network infrastructure, and at the application layer.  In the context of mobile wireless networking, she is interested in challenged environments where traditional ad-hoc and infrastructure-based networking approaches fail. These environments have been termed Disruption Tolerant Networks.  She received a Bachelor's in Computer Science (1987) and Bachelor's in Electrical Engineering (1987), a Master's in Computer Science (1990) and the D.Sc. in Computer Science (1993) all from Washington University, St. Louis, Missouri. Since 1993, she has been a faculty member at Georgia Tech. She was an Assistant Dean in charge of Space and Facilities Planning from Fall 2000 to January 2003. She served as Interim Dean of the College for six months in 2002. She was Associate Dean responsible for Research and Graduate Programs from 2003-2005, and served as the first Chair of the School of Computer Science from 2005-2012.  Zegura is a Fellow of the IEEE and ACM.

Alenka Zajic is currently the Ken Byers Professor in the School of Electrical and Computer Engineering at the Georgia Institute of Technology. She has received the B.Sc. and M.Sc. degrees from the University of Belgrade, Belgrade, Serbia, in 2001 and 2003, respectively, and the Ph.D. degree in electrical and computer engineering from the Georgia Institute of Technology, Atlanta, in 2008. Before joining Georgia Tech as an assistant professor, Zajic was a post-doctoral fellow in the Naval Research Laboratory and visiting faculty in the School of Computer Science at the Georgia Institute of Technology. Zajic is the recipient of the following awards: IEEE Atlanta Section Outstanding Engineer Award (2019), The Best Poster Award at the IEEE International Conference on RFID (2018), NSF CAREER Award (2017), Best Paper Award at the 49th Annual IEEE/ACM International Symposium on Microarchitecture (2016), the Best Student Paper Award at the IEEE International Conference on Communications and Electronics (2014), Neal Shepherd Memorial Best Propagation Paper Award (2012), the Best Paper Award at the International Conference on Telecommunications (2008), the Best Student Paper Award at the Wireless Communications and Networking Conference (2007), IEEE Outstanding Chapter Award as a Chair of the Atlanta Chapter of the AP/MTT Societies (2016), LexisNexis Dean's Excellence Award (2016), and Richard M. Bass/Eta Kappa Nu Outstanding Teacher Award (2016). She was an editor for IEEE Transactions on Wireless Communications 2012-2017 and an executive editor for Wiley Transactions on Emerging Telecommunications Technologies 2011-2016 .

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.

Dr. Shihao Yang is an assistant professor in the School of Industrial & Systems Engineering at Georgia Tech. Prior to joining Georgia Tech, he was a post-doc in Biomedical Informatics at Harvard Medical School after finishing his PhD in statistics from Harvard University. Dr. Yang’s research focuses on data science for healthcare and physics, with special interest in electronic health records causal inference and dynamic system inverse problems.

Helen Xu comes to Georgia Tech from Lawrence Berkeley National Laboratory where she was the 2022 Grace Hopper Postdoctoral Scholar. She completed her Ph.D. at MIT in 2022 with Professor Charles E. Leiserson. Her main research interests are in parallel and cache-friendly algorithms and data structures. Her work has previously been supported by a National Physical Sciences Consortium fellowship and a Chateaubriand fellowship. She has interned at Microsoft Research, NVIDIA Research, and Sandia National Laboratories. 

Yao Xie is a Coca-Cola Foundation Chair and Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech, which she joined in 2013 as an Assistant Professor. She also serves as Associate Director of Machine Learning and Data Science of the Center for Machine Learning. From September 2017 until March 2023 she was the Harold R. and Mary Anne Nash Early Career Professor. She was a Research Scientist at Duke University from 2012 to 2013. 

Her research lies at the intersection of statistics, machine learning, and optimization in providing theoretical guarantees and developing computationally efficient and statistically powerful methods for problems motivated by real-world applications. 

She is currently an Associate Editor for IEEE Transactions on Information Theory, IEEE Transactions on Signal Processing, Journal of the American Statistical Association: Theory and Methods, Sequential Analysis: Design Methods and Applications, INFORMS Journal on Data Science, and an Area Chair of NeurIPS and ICML.

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.

Professor John Wise uses numerical simulations to study the formation and evolution of galaxies and their black holes. He is one of the lead developers of the community-driven, open-source astrophysics code Enzo and has vast experience running state-of-the-art simulations on the world’s largest supercomputers. He received his B.S. in Physics from the Georgia Institute of Technology in 2001. He then studied at Stanford University, where he received his Ph.D. in Physics in 2007. He went on to work at NASA’s Goddard Space Flight Center just outside of Washington, DC as a NASA Postdoctoral Fellow. Then in 2009, he was awarded the prestigious Hubble Fellowship which he took to Princeton University before arriving at Georgia Tech in 2011, coming back home after ten years roaming the nation.