Peng Chen

Peng Chen
pchen402@gatech.edu
Scientific Machine Learning (SciML) and Uncertainty Quantification (UQ)

Dr. Chen is an Assistant Professor in the School of Computational Science and Engineering. Previously he was a Research Scientist at the Oden Institute for Computational Engineering and Sciences at the University of Texas at Austin. Dr. Chen’s research is in the multidisciplinary fields of computational mathematics, data science, scientific machine learning, and parallel computing with various applications in materials, energy, health, and natural hazard. Specifically, his research focuses on developing fast, scalable, and parallel computational methods for integrating data and models under high-dimensional uncertainty to make (1) statistical model learning via Bayesian inference, (2) reliable system prediction with uncertainty quantification, (3) efficient data acquisition through optimal experimental design, and (4) robust control and design by stochastic optimization.

Assistant Professor
Office
CODA | E1350B
Additional Research
Bayesian InferenceInfectious DiseasesOptimal Experimental DesignPlasma FusionStochastic OptimizationUncertainty Quantification
Google Scholar
https://scholar.google.com/citations?hl=en&user=AaVPa5kAAAAJ&view_op=list_works&sortby=pubdate
LinkedIn

Brian Gunter

Brian Gunter
brian.gunter@ae.gatech.edu
Reaearch Website

Dr. Gunter is an Assistant Professor in Aerospace Engineering at the Georgia Institute of Technology. He received his B.S. in mechanical engineering from Rice University, and later his M.S. and Ph.D. in aerospace engineering from the University of Texas at Austin, specializing in orbital mechanics. Prior to joining Georgia Tech, Dr. Gunter was on the faculty of the Delft University of Technology (TU-Delft) in the Netherlands, as a member of the Physical and Space Geodesy section. His research activities involve various aspects of spacecraft missions and their applications, such as investigations into current and future laser altimetry missions, monitoring changes in the polar ice sheets using satellite data, applications of satellite constellations/formations, and topics surrounding kinematic orbit determination. He has been responsible for both undergraduate and graduate courses on topics such as satellite orbit determination, Earth and planetary observation, scientific applications of GPS, and space systems design. He is currently a member of the AIAA Astrodynamics Technical Committee, and also serves as the Geodesy chair for the Fall AGU Meeting Program Committee. He has received a NASA group achievement award for his work on the GRACE mission, and he is also a former recipient of a NASA Earth System Science Graduate Fellowship. He is a member of the American Institute of Aeronautics and Astronautics (AIAA), the American Geophysical Union (AGU), and the International Association of Geodesy (IAG).

Associate Professor
Phone
404.385.2345
Office
ESM 205
Additional Research
satellite geodesy; space systems; orbital mechanics; Earth and planetary observation; remote sensing
Research Focus Areas
Google Scholar
https://scholar.google.com/citations?hl=en&user=ba8fWHIAAAAJ&view_op=list_works&sortby=pubdate

Neha Kumar

Neha Kumar
neha.kumar@gatech.edu
Departmental Bio

Neha Kumar is an Associate Professor jointly appointed at the Sam Nunn School of International Affairs and the School of Interactive Computing at Georgia Tech. Her research lies at the intersection of human-computer interaction and global sustainable development, with a focus on global health and community informatics. Her work contributes feminist perspectives to the design and integration of emerging technologies across marginalized contexts in the Global South. 

Her research has been recognized by multiple ACM Best Paper and Honorable Mention awards. Neha received the College of Computing's Lockheed Inspirational Young Faculty Award (2017) and the Lockheed Excellence in Teaching Award (2019). She currently serves as the President of ACM SIGCHI. She earned her Ph.D. in Information Management Systems from UC Berkeley, Master’s degrees in Computer Science and Education from Stanford University, and Bachelor’s in Computer Science and Applied Math from UC Berkeley.

Associate Professor
BBISS Co-lead: Collaborative Social Impact
Additional Research
Human-Computer Interaction for Global Development
BBISS Initiative Lead Project - Collaborative Social Impact