Introducing the 2019 Lunar Mapping Team
Researcher : Valentin Bickel
Valentin is a PhD candidate in Planetary Geology and Remote Sensing at the Max Planck Institute for Solar System Research (MPS), Germany, and the ETH in Zurich (ETHZ), Switzerland. His academic background includes geosciences (BSc., Technical University Munich, Ludwig-Maximilians University Munich, Germany), arctic engineering and technology (University Centre in Svalbard, Norway), as well as geotechnical engineering and remote sensing (MSc., ETHZ, Switzerland). Scientific training included field mapping exercises and trainee placements throughout the world, including Panama, Costa Rica, Namibia, Kyrgyzstan, Malaysia, and Arctic Norway.
His current research topics include lunar and Martian rockfalls, the determination of geotechnical parameters of regolith, the locomotion performance of wheeled and legged rover concepts on unknown planetary surfaces - including lunar permanently shadowed regions - and deep neural networks for space-borne object detection and mapping.
When he is off-duty, Valentin can likely be found playing water polo, mountain biking, mountaineering, caving, watching & reading mission records from the Apollo archives and dreaming of the road ahead.
Researcher: Jérôme Burelbach
Jérôme Burelbach attended the University of Glasgow and the University of Paris-Sud as an undergraduate in physics, before transferring to the University of Cambridge for his postgraduate studies. After specializing in astrophysics, soft matter and biological systems, he did his PhD with Dr. Erika Eiser at the Cavendish Laboratory, working on the theory of phoretic particle motion based on non-equilibrium thermodynamics and its validation by means of experiments and computer simulations. He then continued his work as a postdoctoral researcher in the group of Prof. Holger Stark at the Technical University of Berlin. His current research focuses on the theoretical description of active Janus particles.
Researcher: Nicole Relatores
Nicole recently finished her PhD in Physics from the University of Southern California, where she also completed a Masters in Computer Science with an emphasis in Data Science. She did her doctoral research at Carnegie Observatories, where she studied the dark matter distributions of a sample of 26 low-mass disk galaxies. Using observations taken with the Palomar Cosmic Web Imager, she derived rotation curves which were used with photometry to construct models of the various mass components of each galaxy, revealing their dark matter distributions. The galaxies she studied showed a diverse range of inner dark matter density profiles, which has important implications for our understanding of stellar feedback in low-mass galaxies and about the nature of dark matter itself.
Nicole previously completed a Masters in Astrophysics from Queen Mary, University of London and a Bachelor of Science in Mathematics from University of California, Santa Barbara. Before beginning her PhD, she spent several years teaching math and science at a one-on-one school.
Researcher: Benjamin Moseley
I am a DPhil student at the University of Oxford’s Centre for Doctoral Training in Autonomous Intelligent Machines and Systems. I am researching the use of AI for seismic sensing and inversion; I accelerated seismic simulation using deep learning. I am a physicist by background and I previously worked as a geophysicist in the energy industry, where I co-founded a data science community with over 400 members. I have a strong interest in how AI can be used for physics-based problems and I am super excited to be contributing to the lunar resource mapping mission at the FDL this year.