Haomin Zhou

Haomin Zhou
hmzhou@math.gatech.edu
Personal Website
Professor
Additional Research
Optimal transport and control algorithms Machine learning methods in numerical PDEs Wavelets and PDE techniques in digital image and video processing Analysis and computations of stochastic differential equations
Research Focus Areas
Machine Learning
IRI And Role
Data Engineering and Science > Faculty
Data Engineering and Science
University, College, and School/Department
Georgia Institute of Technology > College of Sciences > School of Mathematics

Dimitrios Psaltis

Dimitrios Psaltis
dpsaltis3@gatech.edu
Personal Website

I am a professor of Physics at Georgia Tech. I use advanced computational techniques, hybrid computer architectures, and innovative algorithms to answer fundamental questions related to the observational appearance of black holes, the properties of magnetohydrodynamic turbulence, and the interaction of matter with radiation in extreme conditions.

I am a founding member of the Event Horizon Telescope, the international mm-VLBI experiment that has taken the first picture of a black hole with the horizon-scale resolution, and served for three years (2016-2019) as the Project Scientist of the collaboration.

Before moving to Georgia Tech in 2022, I was a professor of Physics and Astronomy at the University of Arizona and the Chair of the Theoretical Astrophysics Program there.

Professor
Additional Research
Black Hole Images General Relativity
Research Focus Areas
High Performance Computing
Machine Learning
IRI And Role
Data Engineering and Science > Faculty
Data Engineering and Science
University, College, and School/Department
Georgia Institute of Technology > College of Sciences > School of Physics

Vidya Muthukumar

Vidya Muthukumar
vmuthukumar8@gatech.edu
ECE Profile Page

Vidya Muthukumar is an Assistant Professor in the School of Electrical and Computer Engineering and H. Milton Stewart School of Industrial and Systems Engineering at Georgia Institute of Technology. Dr. Muthukumar’s broad interests are in game theory, online and statistical learning. She is particularly interested in designing learning algorithms that provably adapt in strategic environments, fundamental properties of overparameterized models, and the foundations of multi-agent decision-making.

Dr. Muthukumar received the B.Tech (with honors) degree from the Indian Institute of Technology, Madras and the Ph.D. degree in Electrical Engineering from University of California, Berkeley. She interned at IBM Research in the summer of 2018 as a Science for Social Good fellow. Before joining Georgia Tech, she spent a semester at the Simons Institute for the Theory of Computing as a research fellow for the program “Theory of Reinforcement Learning.” She is the recipient of an Amazon Research Award, NSF CAREER Award, Adobe Data Science Research Award, Simons-Berkeley Google Research Fellowship, and the UC Berkeley EECS Outstanding Course Development and Teaching Award.

Dr. Muthukumar has served/is serving as an Area Chair for COLT (2021-2024), NeurIPS (2023 and 2024), ALT 2024 and UAI 2024. She also co-organizes several mentorship workshops as part of the Learning Theory Alliance team, and organized the ITALT symposium in 2024.

Assistant Professor
Additional Research
Statistical signal processingGame theorySequential decision-making
Research Focus Areas
Machine Learning
IRI And Role
Data Engineering and Science > Faculty
Data Engineering and Science
University, College, and School/Department
Georgia Institute of Technology > College of Engineering > School of Electrical and Computer Engineering
Georgia Institute of Technology > College of Engineering > School of Industrial Systems Engineering
Google Scholar
https://scholar.google.com/citations?hl=en&user=VVz2wdwAAAAJ&view_op=list_works&sortby=pubdate
Personal Website

Roshan Joseph

Roshan Joseph
roshan@gatech.edu
ISyE Profile Page

Roshan Vengazhiyil Joseph is a A. Russell Chandler III Chair and Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech.

Dr. Joseph's research interests are in the broad areas of applied and computational statistics. A major focus of his research is in developing novel data analytic methods for solving complex engineering problems. He has several years of consulting experience in solving quality-related problems in industries.

Dr. Joseph's honors include Distinguished Dissertation Award from the University of Michigan in 2003, CAREER Award from National Science Foundation in 2005, Jack Youden Prize from ASQ in 2005, Coca-Cola Junior Chair Professorship from ISYE in 2008, Best Paper Award from IIE Transactions in 2009, Franz Edelman Laureate from INFORMS in 2017, Statistics in Physical & Engineering Sciences Award from ASA in 2019, SPAIG Award from the ASA in 2020, and Lloyd S. Nelson Award from ASQ in 2021. He is a Fellow of ASA (elected in 2012) and ASQ (elected in 2020). Currently he is serving as the Editor of Technometrics (2020-2022).

Dr. Joseph received a Ph.D. degree in Statistics from the University of Michigan, Ann Arbor in 2002 and holds an M.Tech. degree in Quality, Reliability, and Operations Research and a B.Tech. degree in Production Engineering and Management. 

A. Russell Chandler III Chair
Professor
Phone
404.894.0056
Office
Groseclose 342
Additional Research
StatisticsExperimental DesignBayesian ComputationUncertainty QuantificationQuality Engineering
Research Focus Areas
Big Data
IRI And Role
Data Engineering and Science > Faculty
Data Engineering and Science
University, College, and School/Department
Georgia Institute of Technology > College of Engineering > School of Industrial Systems Engineering
Google Scholar
https://scholar.google.com/citations?hl=en&user=-XDlRfAAAAAJ&view_op=list_works&sortby=pubdate
Personal Website

Aaron Drysdale

Aaron Drysdale
adrysdale3@gatech.edu

Aaron Drysdale, a Master of Computer Science graduate from Georgia Tech, is the Chief Technologist at the Cloud Hub. He manages the proposal process for research grants, organizes industry training sessions, and provides direct technical support to research teams utilizing cloud resources. Aaron's role also involves collaborating with Microsoft’s technical teams to resolve complex issues, ensuring seamless and efficient research progress. His expertise and proactive approach are vital to the success of the Cloud Hub's mission to advance innovative research.

Chief Technologist - CloudHub @ GT
Research Focus Areas
AI
Artificial Intelligence (AI)
High Performance Computing
IRI And Role
Data Engineering and Science > Faculty
Data Engineering and Science
University, College, and School/Department
Georgia Institute of Technology
LinkedIn

Yiyi He

Yiyi He
yiyi.he@design.gatech.edu
College of Design Profile Page

Yiyi He is an assistant professor in the School of City and Regional Planning (SCaRP) at the College of Design at Georgia Tech. Her research centers on the interdisciplinary fields of urban planning, GIScience, climate science, and artificial intelligence. She is interested in building a better understanding of the uncertainty and asymmetric impacts of climate-change-induced extreme weather events (e.g., flooding, wildfires, extreme heat) on critical components of the built environment (e.g., lifeline infrastructure networks, vulnerable neighborhoods). She leverages data-driven approaches, such as GIS, network science, hyperspectral remote sensing, machine learning, and spatial statistics to tackle complex challenges in climate change and resilience research and to inform more intelligent planning and policy directives.

Her previous work involves using 3D hydrodynamic flood models to simulate flooding under different climate change scenarios and analyze the impact of both coastal and inland flooding on critical infrastructure networks. She received her bachelor’s degree from Nanjing University and her master’s and Ph.D. degree from UC Berkeley.

Assistant Professor
Additional Research
GI Science Network ScienceEnvironmental Planning
Research Focus Areas
City and Regional Planning
Machine Learning
IRI And Role
Data Engineering and Science > Faculty
Data Engineering and Science
University, College, and School/Department
Georgia Institute of Technology > College of Design > School of City and Regional Planning
Google Scholar
https://scholar.google.com/citations?hl=en&user=xoUOI-wAAAAJ&view_op=list_works&sortby=pubdate
LinkedIn

Helen Xu

Helen Xu
hxu615@gatech.edu
CoC Profile Page

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. 

Assistant Professor
Additional Research
Parallel ComputingCache-Efficient AlgorithmsPerformance Engineering
Research Focus Areas
Algorithms & Optimizations
Computer Engineering
High Performance Computing
IRI 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 Computational Science and Engineering
Google Scholar
https://scholar.google.com/citations?hl=en&user=ZcguQt4AAAAJ&view_op=list_works&sortby=pubdate
LinkedIn Personal Website

Kai Wang

Kai Wang
kwang692@gatech.edu
CoC Profile Page

Kai Wang recently attained his Ph.D. in Computer Science at Harvard University where he was advised by Professor Milind Tambe. His research interests include multi-agent systems, computational game theory, machine learning and optimization, and their applications in public health and conservation. One of Wang's key technical contributions includes decision-focused learning, which integrates machine learning and optimization to strengthen learning performance; with his algorithms currently deployed assisting a non-profit in India focused on improving maternal and child health. He is the recipient of the Siebel Scholars award and the best paper runner-up award at AAAI 2021. 

Assistant Professor
Additional Research
AI for Social ImpactData-Driven Decision MakingMulti-Agent SystemsOptimization
Research Focus Areas
AI
IRI 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
Google Scholar
https://scholar.google.com/citations?hl=en&user=spWVns8AAAAJ
LinkedIn Personal Website

Raphaël Pestourie

Raphaël Pestourie
rpestourie3@gatech.edu
CoC Profile Page

Raphaël Pestourie earned his Ph.D. in Applied Mathematics and an AM in Statistics from Harvard University in 2020. Prior to Georgia Tech, he was a postdoctoral associate at MIT Mathematics, where he worked closely with the MIT-IBM Watson AI Lab. Raphaël’s research focuses on scientific machine learning at the intersection of applied mathematics and machine learning and inverse design via scientific machine learning and large-scale electromagnetic design. 

Assistant Professor
Additional Research
Scientific Machine LearningInverse Design in Electromagnetism
Research Focus Areas
AI
Machine Learning
IRI 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
Google Scholar
https://scholar.google.com/citations?hl=en&user=Lxv3W74AAAAJ&view_op=list_works&sortby=pubdate
LinkedIn Personal Website

Alexey Tumanov

Alexey Tumanov
atumanov@gatech.edu
Systems for AI Lab

I've started as a tenure-track Assistant Professor in the School of Computer Science at Georgia Tech in August 2019, transitioning from my postdoc at the University of California Berkeley, where I worked with Ion Stoica and collaborated closely with Joseph Gonzalez. I completed my Ph.D. at Carnegie Mellon University, advised by Gregory Ganger. At Carnegie Mellon, I was honored by the prestigious NSERC Alexander Graham Bell Canada Graduate Scholarship (NSERC CGS-D3) and partially funded by the Intel Science and Technology Centre for Cloud Computing and Parallel Data Lab. Prior to Carnegie Mellon, I worked on agile stateful VM replication with para-virtualization at the University of Toronto, where I worked with Eyal de Lara and Michael Brudno. My interest in cloud computing, datacenter operating systems, and programming the cloud brought me to the University of Toronto from industry, where I had been developing cluster middleware for distributed datacenter resource management.

Assistant Professor
Additional Research
Systems for MLResource ManagementScheduling
Research Focus Areas
Logistics
Machine Learning
IRI 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
Google Scholar
https://scholar.google.com/citations?hl=en&user=7P-gZioAAAAJ&view_op=list_works&sortby=pubdate
LinkedIn CoC Profile Page
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