Introducing the 2019 SDO Team

 
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Researcher : Luiz Fernando Guedes Dos Santos
Luiz Fernando is a PhD student at The Catholic University of America (CUA) and a Research Assistant at NASA Goddard Space Flight Center. He has a Bachelor’s Degree in Physics from University of Brasília (UnB) and a Master of Science in Physics from CUA. Luiz’s main area of research is Interplanetary Coronal Mass Ejections and Magnetic Clouds (MCs) with a focus on implementing Machine Learning on in-situ measurements of spacecrafts.

Luiz has been conducting a research focused on Image Recognition models using Convolutional Neural Networks and Deep Learning to identify patterns data from spacecraft such as Wind with the objective to classify and predict MCs events. He has also been assisting on the development of Flux Ropes models in order to reconstructs events based on in-situ data. In addition, in 2013 Luiz Fernando was granted by the Brazilian government a merit scholarship award to study as an exchange student for a year at St. John’s university, in New York City, and for three months was an intern at Boston University where he helped to develop and benchmark ForeCAT.


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Researcher: Brad Neuberg

I am a full stack machine learning engineer, with 15+ years experience across startups, open source, and companies like Google and Dropbox. My machine learning specialty is focused on deep learning, using neural networks to craft learning-based solutions. My research interests are machines that can see, hear, and plan in order to augment people and expand society’s capabilities.

Most recently I’ve been on the Machine Learning team at Dropbox, doing industrial R&D to ship ML-powered products to millions of users. Recent work at Dropbox has included launching features that automatically run advanced deep learning models on billions of images a day; building an industry leading OCR pipeline using deep learning for millions of users; and doing R&D using deep learning for features such as meeting assistants and intelligent file systems.

I am passionate about innovation. I have a long history of untraditional R&D across many kinds of organizations, including open source, startups, and large companies like Dropbox and Google. I created Coworking, which morphed into an international grassroots movement to establish a new kind of workspace for the self-employed, with more than 10,000 coworking spaces now open internationally. At Inkling I founded Inkling Habitat, which re-imagined interactive digital textbooks for higher education and how they are published by adopting ideas from computer science. Inkling Habitat turned into a multi-million dollar business that was adopted by the world’s major educational publishers, such as Pearson.


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Researcher: Valentina Salvatelli

Valentina is a data scientist and a physicist by background. In her current role at IQVIA she build advanced machine learning models to support the cure of rare diseases by leveraging large amount of medical records. Previously she researched how to use astronomical data and bayesian inference to understand the evolution of the universe. She holds a PhD in Astrophysics from La Sapienza University of Rome and before moving into the industry she worked on the data analysis and interpretation of different ESA/NASA experiments at several research institutes worldwide, including the University of California Irvine and the CPT of Marseille.

She also collaborated with the University of Cambridge to personalize online education through machine learning. She has a strong background in math and experience in sequential modeling, deep learning and bayesian statistics. Valentina worked with massive datasets on supercluster and distributed clusters and she recently wrote software for automatized data processing and predictive modeling. She likes to work in international, interdisciplinary and creative teams. Valentina believes AI and machine learning can bring huge benefit to our lives and to scientific research and she interested in making this positive impact real. When not working or experimenting with the latest Python/ML package, Valentina likes having a walk or a run outdoor, cooking for her friends and travelling to natural wonders.


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Researcher: Souvik Bose

Souvik Bose, doctoral researcher at the Rosseland Center for Solar Physics, University of Oslo: Souvik’s research mainly focuses on the dynamics of the solar atmosphere, in particular the origin and the evolution of spicules and jets in the solar chromosphere. Furthermore, he has also worked extensively on the long term variability of the sun-as-a-star magnetic field with datasets from the NASA’s Solar Dynamics Observatory (SDO). An Astrophysicist by profession, he uses the data from both ground and space-based solar telescopes for his research. Passionate about data analysis and artificial intelligence, he also uses machine learning methods in his work which serves as a bridge between academia and industry in today’s world. In addition, he makes use of numerical codes for reproduction of synthetic data to compare with actual solar observations.

 
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ENHANCED PREDICTABILITY OF GNSS DISTURBANCES CHALLENGE

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EXPANDING THE CAPABILITIES OF NASA’S SOLAR DYNAMICS OBSERVATORY CHALLENGE