Introducing the 2019 Super-Resolution Mentors

 
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Core Domain Mentor: Andres Munoz Jaramillo
Andrés is a senior research scientist at the Southwest Research Institute and a veteran FDL mentor on its heliophysics challenges. His research aims to understand and forecast the solar magnetic cycle, space weather, and their impact on solar variability and humanity’s technological infrastructure. He sees deep learning and data visualization as invaluable tools that enhance humanity’s capability of interfacing with data and maximizing their scientific throughput.


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Core Domain Mentor: Paul Wright
Paul Wright is a postdoctoral research fellow within the W. W. Hansen Experimental Physics Laboratory at Stanford University. Prior to joining Stanford, he obtained his PhD in Physics from the University of Glasgow. Paul’s current research utilises magnetic field data obtained by the Helioseismic and Magnetic Imager (HMI) onboard the Solar Dynamics Observatory (SDO); however, his PhD research concentrated on obtaining and analysing pioneering observations of the X-ray Sun with NASA’s Nuclear Spectroscopic Telescope Array (NuSTAR).

During the final stages of his PhD, Paul participated in FDL 2018 as a member of “Predicting Solar Spectral Irradiance from SDO/AIA Observations” team. In addition to training a neural network to nowcast solar spectral irradiance from SDO/AIA, the team have also published a machine learning data set prepared from eight years of SDO observations.


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Mentor: Atilim Gunes Baydin

Atilim Gunes Baydin is a postdoctoral researcher at the University of Oxford, working at the intersection of generative modeling, probabilistic programming, and deep learning. His current work is on enabling efficient probabilistic inference in large-scale simulators in particle physics, in collaboration with CERN researchers. He co-organizes the Deep Learning for Physical Sciences workshop at the Neural Information Processing Systems (NIPS) conference, covering applications of machine learning to problems in physical sciences. He received his PhD in artificial intelligence from Universitat Autonoma de Barcelona in 2013. His research interests also include automatic differentiation, hyperparameter optimization, and evolutionary algorithms.


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Mentor: Bennie Lewis

Dr. Bennie G. Lewis Jr. is a Research Scientist in the Advanced Technology Center at Lockheed Martin Space Sunnyvale/Palo Alto California with a focus on AI, Deep Learning / Machine Learning, AR/VR, Embedded Systems, Cognitive Systems, Space Systems, Human Machine Interaction, and Robotics. Prior to his current role, he was a Software Engineer for Lockheed Martin Missiles and Fire Control Orlando Florida. He has a B.S. and M.S in Computer Engineering as well as a Ph.D. in Computer Engineering with a focus in robotics and intelligent systems from the Department of Electrical Engineer and Computer Science at the University of Central Florida working in the Intelligent Agents Lab.


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Supporting Mentor: Freddie Kalaitzis
Element AI


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Supporting Mentor: Zhichao Lin
Element AI


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Supporting Mentor: Julien Cornebise
Element AI