Introducing the 2019 Super-Resolution Team


Researcher : Shane Maloney
Dr Maloney is postdoctoral research fellow at Trinity College Dublin and the Dublin Institute for Advanced Studies. He is a member of the STIX team, an X-ray imaging spectrometer due for launch on Solar Orbiter in early 2020, developing the software to process and analyse STIX data. He also works on a number of solar and space-weather projects using traditional and more modern machine learning approaches. His primary research interest as a solar and space weather scientist are the build-up, trigger, and release of magnetic energy in the form of flares, coronal mass ejections (CMEs), solar energetic particle (SEPs) events and related phenomena.


Researcher: Anna Jungbluth

Anna is currently studying for a PhD in Condensed Matter Physics at the University of Oxford, researching organic solar cells. Before starting her PhD, she graduated with a degree in Physics and Materials Science from MIT. Anna is passionate about promoting females in STEM subjects and applying her science background to tackle global challenges such as climate change. At MIT, she researched semi-transparent solar cells to be used for windows and phone screens. She was also part of a project researching how to increase global access to clean drinking water, which was presented to representatives from MIT, Harvard, and the World Bank.

At Oxford, Anna has won a number of innovation competitions focused on creating technologies for the betterment of society. With a team of four other students, Anna won the UK finals of the 2018 European Space Agency sponsored “Act in Space” competition for designing a satellite and machine learning based phone navigation app for increased street safety. In her free time, Anna enjoys learning new languages, traveling and skiing.


Researcher: Xavier Gitaux

I am a first year PhD candidate in the Computer Science Program at George Mason University. My interests are in explaining deep learning algorithms and improving fairness and privacy in machine learning. Current applications focus on generating and certifying data that do not leak information on individual sensitive attributes while maintaining high utility. I am also exploring the robustness of so-called anonymous protocols on the block-chain. Prior to join George Mason, I was a data scientist/senior economist for the Denver Regional Council of Governments and monitor large scale data mining tasks for the State of Colorado and the Center for Medicare and Medicaid Services. I hold a Master in Engineering from Ecole Polytechnique (France) and a Master in Economics from the University of Colorado (Boulder)


Researcher: Carl Shneider

Originally from Brooklyn, New York, Carl Shneider has studied at Rensselaer Polytechnic Institute in the US, the Swiss Federal Institute of Technology (ETH Zurich) in Switzerland, the University of Cambridge in the UK, and at Utrecht University and Leiden University in the Netherlands.

He currently works as a postdoc in space weather and machine learning in the Multiscale Dynamics group at the Dutch National Institute for Mathematics and Computer Science (CWI) at the Amsterdam Science Park. He holds a PhD in astrophysics from Leiden Observatory, Leiden University.

After his PhD, Carl also worked in precision medicine, first at the Diagnostic Image Analysis Group (DIAG) at the Radboud University Medical Center, followed by a postdoc at the Utrecht University Medical Center where his research focused on cancer genomics and utilized techniques from bioinformatics and machine learning.

Carl enjoys participating in public science outreach activities and is the event manager for the Utrecht city branch of the annual Pint of Science Public Science Festival which takes place worldwide.

He also has language competencies in Russian, Spanish, German, and Dutch.