Vidya Muthukumar

Vidya Muthukumar's profile picture
vmuthukumar8@gatech.edu
Assistant Professor
Additional Research
  • Statistical signal processing
  • Game theory
  • Sequential decision-making
Research Focus Areas
Google Scholar
https://scholar.google.com/citations?hl=en&user=VVz2wdwAAAAJ&view_op=list_works&sortby=pubdate

Roshan Joseph

Roshan Joseph's profile picture
roshan@gatech.edu

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
  • Statistics
  • Experimental Design
  • Bayesian Computation
  • Uncertainty Quantification
  • Quality Engineering
Research Focus Areas
Google Scholar
https://scholar.google.com/citations?hl=en&user=-XDlRfAAAAAJ&view_op=list_works&sortby=pubdate

Aaron Drysdale

Aaron Drysdale's profile picture
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
University, College, and School/Department

Yiyi He

Yiyi He's profile picture
yiyi.he@design.gatech.edu

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, School of City and Regional Planning
Additional Research
  • GI Science Network Science
  • Environmental Planning
Google Scholar
https://scholar.google.com/citations?hl=en&user=xoUOI-wAAAAJ&view_op=list_works&sortby=pubdate

Helen Xu

Helen Xu's profile picture
hxu615@gatech.edu

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 Computing
  • Cache-Efficient Algorithms
  • Performance Engineering
Google Scholar
https://scholar.google.com/citations?hl=en&user=ZcguQt4AAAAJ&view_op=list_works&sortby=pubdate

Kai Wang

Kai Wang's profile picture
kwang692@gatech.edu

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 Impact
  • Data-Driven Decision Making
  • Multi-Agent Systems
  • Optimization
Research Focus Areas
Google Scholar
https://scholar.google.com/citations?hl=en&user=spWVns8AAAAJ

Raphaël Pestourie

Raphaël Pestourie's profile picture
rpestourie3@gatech.edu

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, School of Computer Science
Additional Research
  • Scientific Machine Learning
  • Inverse Design in Electromagnetism
Research Focus Areas
Google Scholar
https://scholar.google.com/citations?hl=en&user=Lxv3W74AAAAJ&view_op=list_works&sortby=pubdate

Alexey Tumanov

Alexey Tumanov's profile picture
atumanov@gatech.edu

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
  • High Performance Computing
  • Logistics
  • Machine Learning
  • Systems Design
Research Focus Areas
Google Scholar
https://scholar.google.com/citations?hl=en&user=7P-gZioAAAAJ&view_op=list_works&sortby=pubdate

Divya Mahajan

Divya Mahajan 's profile picture
divya.mahajan@gatech.edu

Divya is an Assistant Professor in School of ECE and Computer Science. Divya received her Ph.D. from Georgia Institute of Technology and Master’s from UT Austin. She obtained her Bachelor’s from IIT Ropar where she was conferred the Presidents of India Gold Medal, the highest academic honor in IITs.

Prior to joining Georgia Tech, Divya was a Senior Researcher at Microsoft Azure since September 2019. Her research has been published in top-tier venues such as ISCA, HPCA, MICRO, ASPLOS, NeurIPS, and VLDB. Her dissertation has been recognized with the NCWIT Collegiate Award 2017 and distinguished paper award at High Performance Computer Architecture (HPCA), 2016.

Currently, she leads the Systems Infrastructure and Architecture Research Lab at Georgia Tech. Her research team is devising next-generation sustainable compute platforms targeting end-to-end data pipeline for large scale AI and machine learning. The work draws insights from a broad set of disciplines such as, computer architecture, systems, and databases.

Assistant Professor
Additional Research
  • Artificial Intelligence
  • Machine Learning
  • Sustainable Systems for AI
  • System Design & Optimization
Google Scholar
https://scholar.google.com/citations?hl=en&user=HmBa_6gAAAAJ&view_op=list_works&sortby=pubdate

Yingyan (Celine) Lin

Yingyan (Celine) Lin's profile picture
celine.lin@gatech.edu

Yingyan (Celine) Lin is currently an Associate Professor in the School of Computer Science at the Georgia Institute of Technology. She leads the Efficient and Intelligent Computing (EIC) Lab, which focuses on developing efficient machine learning systems via cross-layer innovations from algorithm to architecture down to chip design, aiming to promote green AI and enable ubiquitous machine learning powered intelligence. She received a Ph.D. degree in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign in 2017. 

Prof. Lin is a Facebook Research Award (2020), NSF CAREER Award (2021), IBM Faculty Award (2021), and Meta Faculty Research Award (2022) recipient, and received the ACM SIGDA Outstanding Young Faculty Award in 2022. She was selected as a Rising Star in EECS by the 2017 Academic Career Workshop for Women at Stanford University. She received the Best Student Paper Award at the 2016 IEEE International Workshop on Signal Processing Systems (SiPS 2016), and the 2016 Robert T. Chien Memorial Award for Excellence in Research at UIUC. Prof. Lin is currently the lead PI of multiple multi-university projects, such as RTML and 3DML, and her group has been funded by NSF, NIH, DARPA, SRC, ONR, Qualcomm, Intel, HP, IBM, and Meta. Her group’s research won first place in both the University Demonstration at DAC 2022 and the ACM/IEEE TinyML Design Contest at ICCAD 2022, and was selected as an IEEE Micro Top Pick of 2023

Associate Professor
Additional Research
  • AI Systems
  • Energy-efficient AI/ML Algorithms
  • Green AI
  • Machine Learning
  • Trustworthy AI for Physics
Research Focus Areas
University, College, and School/Department
Google Scholar
https://scholar.google.com/citations?hl=en&user=dio8IesAAAAJ&view_op=list_works&sortby=pubdate