Zachary Danziger

Zachary Danziger
zachary.danziger@emory.edu
https://scholarblogs.emory.edu/danziger/

The effortlessness of moving your body belies the lurking complexity driving it. We are trying to understand how the nervous system makes something so complicated as controlling a human body feel so natural. We use human subjects studies, animal experiments, mathematical biology, and artificial intelligence to understand neural control of movement. New theories and insight promise advances in physical therapy, human-machine collaboration, brain-computer interfaces, neural modulation of peripheral reflexes, and more.

Associate Professor Division of Physical Therapy, Department of Rehabilitation Medicine
Associate Professor, W.H. Coulter Department of Biomedical Engineering
Phone
404-712-4801
Research Focus Areas
Algorithms & Optimizations
Bioengineering
Human-Centered Robotics
Machine Learning
Neuroscience
Systems Biology
IRI And Role
Bioengineering and Bioscience > Faculty
Bioengineering and Bioscience
University, College, and School/Department
Emory University
Zachary
Danziger
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Shaheen Dewji, Ph.D.

Shaheen Dewji, Ph.D.
shaheen.dewji@gatech.edu

Shaheen Azim Dewji, Ph.D., (she/her/hers) is an Assistant Professor in the Nuclear & Radiological Engineering and Medical Physics Programs at the Georgia Institute of Technology, where she leads the Radiological Engineering, Detection, and Dosimetry (RED²) research group. Dewji joined Georgia Tech following three years as faculty at Texas A&M University in the Department of Nuclear Engineering, and as a Faculty Fellow of the Center for Nuclear Security Science and Policy Initiatives (NSSPI). In her prior role at Oak Ridge National Laboratory, where she remained for almost 9 years, Dewji was Radiological Scientist in the Center for Radiation Protection Knowledge. Her research interests include development of dose coefficients, shielding design, and nuclear material detection assay using gamma-ray spectroscopy. Her recent work has focused on associated challenges in uncertainty quantification in dose estimation/reconstruction associated with the external exposure and internal uptake of radionuclides associated with applications of emergency response, defense, nuclear medicine, and occupational/public safety using Monte Carlo radiation transport codes and internal dose modeling. Dewji completed her Masters and Ph.D. degrees in Nuclear and Radiological Engineering at the Georgia Institute of Technology in Atlanta, GA and was a fellow of the Sam Nunn Security Program. She received her Bachelor of Science in Physics from the University of British Columbia. Dewji currently serves on the National Academies of Science, Engineering, and Medicine – Nuclear and Radiation Studies Board and is a member of the Board of Directors for both the American Nuclear Society and Health Physics Society.
   

Assistant Professor
Phone
404.894.5800
Office
Boggs 3-15
Research Focus Areas
AI for Security
Cancer Biology
Defense
Diagnostics
Energy
Health & Life Sciences
Machine Learning
Nuclear
Risk Management
Systems Biology
IRI And Role
Bioengineering and Bioscience > Faculty
Bioengineering and Bioscience
University, College, and School/Department
Georgia Institute of Technology > College of Engineering > Woodruff School of Mechanical Engineering
Lab
Shaheen
Dewji
Azim
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Munmun De Choudhury

Munmun De Choudhury
munmund@gatech.edu
http://www.munmund.net/biography.html

Munmun De Choudhury is an Associate Professor at the School of Interactive Computing in Georgia Institute of Technology. Dr. De Choudhury is renowned for her groundbreaking contributions to the fields of computational social science, human-computer interaction, and digital mental health. Through fostering interdisciplinary collaborations across academia, industry, and public health sectors, Dr. De Choudhury and her collaborators have contributed significantly to advancing the development of computational techniques for early detection and intervention in mental health, as well as in unpacking how social media use benefits or harms mental well-being. De Choudhury's contributions have been recognized worldwide, with significant scholarly impact evidenced by numerous awards like induction into the SIGCHI Academy and the 2023 SIGCHI Societal Impact Award. Beyond her academic achievements, Dr. De Choudhury is a proactive community leader, a persistent contributor to policy-framing and advocacy initiatives, and is frequently sought for expert advice to governments, and national and international media.

 

Associate Professor; Director of Social Dynamics and Well-Being Laboratory; Co-Lead of Children's Healthcare of Atlanta Pediatric Technology Center at Georgia Tech's Patient-Centered Care Delivery
Phone
4043858603
Research Focus Areas
Big Data
Bioinformatics
Diagnostics
Health & Life Sciences
Healthcare
Machine Learning
Public Health
Social & Environmental Impacts
IRI And Role
Bioengineering and Bioscience > Faculty
Data Engineering and Science
People and Technology
Bioengineering and Bioscience
Munmun
De Choudhury
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Animesh Garg

Animesh Garg
animesh.garg@gatech.edu
Personal Profile Page

Animesh Garg is a Stephen Fleming Early Career Assistant Professor at School of Interactive Computing at Georgia Tech. He leads the People, AI, and Robotics (PAIR) research group. He is on the core faculty in the Robotics and Machine Learning programs. Animesh is also a Senior Researcher at Nvidia Research. Animesh earned a Ph.D. from UC Berkeley and was a postdoc at the Stanford AI Lab. He is on leave from the department of Computer Science at University of Toronto and CIFAR Chair position at the Vector Institute.

Garg earned his M.S. in Computer Science and Ph.D. in Operations Research from UC, Berkeley. He worked with Ken Goldberg at Berkeley AI Research (BAIR). He also worked closely with Pieter Abbeel, Alper Atamturk & UCSF Radiation Oncology. Animesh was later a postdoc at Stanford AI Lab with Fei-Fei Li and Silvio Savarese.

Garg's research vision is to build the Algorithmic Foundations for Generalizable Autonomy, that enables robots to acquire skills, at both cognitive & dexterous levels, and to seamlessly interact & collaborate with humans in novel environments. His group focuses on understanding structured inductive biases and causality on a quest for general-purpose embodied intelligence that learns from imprecise information and achieves flexibility & efficiency of human reasoning.

Assistant Professor
Additional Research

Robot Learning3D Vision and Video ModelsCausal InferenceReinforcement LearningCurrent Applications: Mobile-Manipulation in Retail/Warehouse, personal, and surgical robotics

Research Focus Areas
Foundations of Robotics
Human-Centered Robotics
Machine Learning
Robotics
IRI And Role
People and Technology > Affiliated Faculty
Robotics > Core
People and Technology
Robotics
Matter and Systems > Affiliated Faculty
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=zp8V7ZMAAAAJ&view_op=list_works&sortby=pubdate
LinkedIn
Animesh
Garg
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Mathieu Dahan

Mathieu Dahan
mathieu.dahan@isye.gatech.edu
ISyE Faculty Page and Contact Info

Mathieu Dahan is an Assistant Professor in the H. Milton Stewart School of Industrial and Systems Engineering. His research interests are in combinatorial optimization, game theory, and predictive analytics, with applications to service operations management and disaster logistics. His primary focus is on developing strategies for improving the resilience of large-scale infrastructures — particularly, transportation and natural gas networks — in the face of correlated failures such as security attacks and natural disasters. Current projects include: (i) Strategic design of network inspection systems; and (ii) Analytics-based response operations under uncertainty.

Dr. Dahan received a Ph.D. and M.S. in Computational Science and Engineering from the Massachusetts Institute of Technology, a M.Eng. and B.Eng. from the École Centrale Paris, and a B.S. in Mathematics from Paris-Sud University. He is the recipient of the MIT Robert Thurber Fellowship, the MIT Robert Guenassia Award, the Honorable Mention for the J-WAFS Fellowships, and the Best Poster Award at the Princeton Day of Optimization.

During the summer of 2016, he worked as a research scientist intern at Amazon.com (Seattle) in the Supply Chain Optimization Technologies team. Using Machine-Learning techniques, he worked on predicting the fulfillment cost and developing a prototype to grant a fast and accurate access to future shipping cost estimates.

Assistant Professor
Phone
404.385.3054
Research Focus Areas
Analytics and Prognostics Systems
Energy
Healthcare
Machine Learning
Supply Chain
IRI And Role
People and Technology > Affiliated Faculty
People and Technology
University, College, and School/Department
Georgia Institute of Technology > College of Engineering
Mathieu
Dahan
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Nagi Gebraeel

Nagi Gebraeel
nagi.gebraeel@isye.gatech.edu
Website

Professor Nagi Gebraeel is the Georgia Power Early Career Professor and Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. He received his MS and PhD from Purdue University in 1998 and 2003, respectively.

Dr. Gebraeel's research interests lie at the intersection of Predictive Analytics and Machine Learning in IoT enabled maintenance, repair and operations (MRO) and service logistics. His key focus is on developing fundamental statistical learning algorithms specifically tailored for real-time equipment diagnostics and prognostics, and optimization models for subsequent operational and logistical decision-making in IoT ecosystems. Dr. Gebraeel also develops cyber-security algorithms intended to protect IoT-enabled critical assets from ICS-type cyberattacks (cyberattacks that target Industrial Control Systems). From the standpoint of application domains, Dr. Gebraeel has general interests in manufacturing, power generation, and service-type industries. Applications in Deep Space missions are a recent addition to his research interests, specifically, developing Self-Aware Deep Space Habitats through NASA's HOME Space Technology Research Institute.

Dr. Gebraeel leads Predictive Analytics and Intelligent Systems (PAIS) research group at Georgia Tech's Supply Chain and Logistics Institute. He also directs activities and testing at the Analytics and Prognostics Systems laboratory at Georgia Tech's Manufacturing Institute. Formerly, Dr. Gebraeel served as an associate director at Georgia Tech's Strategic Energy Institute (from 2014 until 2019) where he was responsible for identifying and promoting research initiatives and thought-leadership at the intersection of Data Science and Energy applications. He was also the former president of the Institute of Industrial and Systems Engineers (IISE) Quality and Reliability Engineering Division, and is currently a member of the Institute for Operations Research and the Management Sciences (INFORMS), and IISE (since 2005).

Georgia Power Associate Professor, School of Industrial Systems Engineering
Phone
404.894.0054
Office
Groseclose Building, Room 327
Additional Research
  • Data Mining
  • IoT
  • Sensor-based Prognostics & Degradation Modeling
  • Reliability Engineering
  • Service Logistics
  • System Design & Optimization
  • Cyber/ Information Technology
Research Focus Areas
Diagnostics
Energy
Machine Learning
IRI And Role
Manufacturing > Affiliated Faculty
Data Engineering and Science > Affiliated Faculty
Energy > Research Community
Manufacturing
Data Engineering and Science
Energy
University, College, and School/Department
Georgia Institute of Technology > College of Engineering > School of Industrial Systems Engineering
Nagi
Gebraeel
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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
Dimitrios
Psaltis
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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
Vidya
Muthukumar
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