Machine Learning

Social & Environmental Impacts

Public Health

IRI And Role

Bioengineering and Bioscience > Faculty

Bioengineering and Bioscience

People and Technology

Alexander Adams

Read more about Alexander Adams

aadams322@gatech.edu

https://www.uncommonsenselabs.com

Alex Adams’s research focuses on designing, fabricating, and implementing new ubiquitous and wearable sensing systems. In particular, he is interested in how to develop these systems using equity-driven design principles for healthcare. Alex leverages sensing, signal processing, and fabrication techniques to design, deploy, and evaluate novel sensing technologies.

Originally a musician, Alex became fascinated by how he could capture and manipulate sounds through analog hardware and digital signal processing, which led him back to his hometown (Concord, NC). Alex completed his BS at the University of North Carolina at Charlotte in 2014 and his Ph.D. at Cornell University in 2021 (advised by Professor Tanzeem Choudhury). Alex then became the resident Research Scientist for the Precision Behavioral Health Initiative at Cornell Tech (NYC) until the fall of 2022, when he joined the School of Interactive Computing at the Georgia Institute of Technology. Currently, his research focuses on the equity-driven design and the development of multi-modal sensing systems to simultaneously assess mental and physical health to enable a new class of mobile health technologies.

Assistant Professor

Phone

7044671939

Office

237 TSRB

Research Focus Areas

Biotechnology

Diagnostics

Health & Life Sciences

Healthcare

Medical Device Design, Development and Delivery

IRI And Role

Bioengineering and Bioscience > Faculty

Robotics

Bioengineering and Bioscience

Haomin Zhou

Read more about 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

IRI And Role

Georgia Institute of Technology > College of Sciences > School of Mathematics

University, College, and School/Department

Dimitrios Psaltis

Read more about 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

IRI And Role

Georgia Institute of Technology > College of Sciences > School of Physics

University, College, and School/Department

Vidya Muthukumar

Read more about 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

IRI And Role

Georgia Institute of Technology > College of Engineering > School of Electrical and Computer Engineering

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=VVz2wdwAAAAJ&view_op=list_works&sortby=pubdate

Personal Website

Yiyi He

Read more about 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

IRI And Role

Georgia Institute of Technology > College of Design > School of City and Regional Planning

University, College, and School/Department

Google Scholar

https://scholar.google.com/citations?hl=en&user=xoUOI-wAAAAJ&view_op=list_works&sortby=pubdate

Raphaël Pestourie

Read more about 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

IRI And Role

Georgia Institute of Technology > College of Computing > School of Computer Science

University, College, and School/Department

Google Scholar

https://scholar.google.com/citations?hl=en&user=Lxv3W74AAAAJ&view_op=list_works&sortby=pubdate

LinkedIn Personal Website

Alexey Tumanov

Read more about 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

IRI And Role

Georgia Institute of Technology > College of Computing > School of Computer Science

University, College, and School/Department

Google Scholar

https://scholar.google.com/citations?hl=en&user=7P-gZioAAAAJ&view_op=list_works&sortby=pubdate

LinkedIn CoC Profile Page

Divya Mahajan

Read more about Divya Mahajan

divya.mahajan@gatech.edu

Personal Website

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

Computer ArchitectureSystems for Machine LearningLarge Scale Infrastructure for AI and Data Storage

Research Focus Areas

System Design & Optimization

IRI And Role

Georgia Institute of Technology > College of Computing > School of Computer Science

University, College, and School/Department

Georgia Institute of Technology > College of Engineering > School of Electrical and Computer Engineering

Google Scholar

https://scholar.google.com/citations?hl=en&user=HmBa_6gAAAAJ&view_op=list_works&sortby=pubdate

Yingyan (Celine) Lin

Read more about Yingyan (Celine) Lin

celine.lin@gatech.edu

EIC Lab Website

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

Research Focus Areas

AI Systems

IRI And Role