Virtual Conference on
Applications of Statistical Methods and Machine Learning in the Space Sciences
17-21 May 2021
hosted by Space Science Institute, Boulder, Colorado
The goal of the conference "Applications of Statistical Methods and Machine Learning in the Space Sciences" is to bring together academia and industry to leverage the advancements in statistics, data science, methods of artificial intelligence (AI) such as machine learning and deep learning, and information theory to improve the analytic models and their predictive capabilities making use of the enormous data in the field of space sciences.
Conceived as a multidisciplinary gathering, this conference welcomes researchers from all disciplines of space science: (solar physics and aeronomy, planetary sciences, geology, exoplanet and astrobiology, galaxies), from the fields of AI, statistics, data science and from industry who make use of statistical analysis and methods of AI. We encourage contributions from a wide range of topics including but not limited to: advanced statistical methods, deep learning and neural networks, times series analysis, Bayesian methods, feature identification and feature extraction, physics-based models combined with machine learning techniques and surrogate models, space weather prediction and other domain topics where AI is applied, model validation and uncertainty quantification, turbulence and non-linear dynamics in space plasma, physics informed neural networks, information theory and data reconstruction and data assimilation.
The conference will be fully virtual, given the pandemic, and will consists of invited and contributed talks, and designated discussion sessions. The conference will be an opportunity for students, young researchers and seniors to enhance their knowledge in the emerging techniques of AI and statistical studies and a platform for future collaborations.
There will be limited funds for waiving the registration fee for students and early careers. Please indicate if you are requesting registration fee waiver when you submit your abstracts.
Scientific Organizing Committee
- Michael Balikhin, University of Sheffield, UK
- Joe Borovsky, SSI, Boulder, CO
- Raffaella D'Amicis, Institute for Space Astrophysics and Planetology, Rome
- Maria Dainotti, National Astronomical Observatory of Japan; SSI Affiliate
- Manolis Georgoulis, Academy of Athens, Greece
- Jay Johnson, Andrews University, MI
- Karly Pitman, SSI, Boulder, CO
- Bala Poduval, University of New Hampshire, Durham, NH; SSI Affiliate (SOC Chair)
- Ralph Shuping, SSI, Boulder, CO
- Olga Verkhoglyadova, JPL, Pasadena, CA
- Simon Wing, Johns Hopkins University, Laurel, MD; SSI Affiliate
- Peter Wintoft, Swedish Institute of Space Physics, Sweden
- Astronomy, Solar/Stellar Physics
- Atmospheric sciences and aeronomy
- Space weather (SW) prediction
- SW at other planets/locations in the solar system
- Solar wind-magnetospheric coupling
- Turbulence and non-linear dynamics in space plasmas
- Bayesian Analysis and Advanced Statistical methods
- Data, Model and Performance Verication
- Data Reconstruction and Assimilation
- Information theory
- Machine Learning (ML)/Deep Learning (DL)
- Physics-based Models in ML and DL methods
- Pattern Recognition and Feature Extraction
- Surrogate Models
- Time Series Analysis
- Berkay Aydin, Georgia State University, USA
- Abigail Azari, Space Sciences Lab at UC Berkeley, USA
- Malgorzata Bogdan, Wroclaw University, Poland
- Enrico Camporeale, CIRES/NOAA, USA
- Lika Guhathakurta, NASA Headquarters, USA
- Hannah Kerner, University of Maryland/NASA Harvest, USA
- Giovanni Lapenta, KU, Leuven, Belgium
- Chris Maddison, University of Toronto, Canada
- Bob McPherron, UCLA, USA
- Meg Millhouse, University of Melbourne, Australia
- Adnane Osmane, University of Helsinki, Finland
- Agnieska Pollo, Jagiellonian University, Krakow, Poland
- Daniele Telloni, INAF Astrophysical Observatory of Turin, Italy
- Shasha Zou, University of Michigan, USA
Consent for Sharing and Recording
Please be aware that SSI is recording the Zoom sessions for the "Applications of Statistical Methods and Machine Learning in the Space Sciences" virtual conference and intends to make all content (slides, posters, and Zoom recordings) publicly available at the conclusion of the conference. Should you object to your presentation being recorded or shared with others, you must notify the session chair prior to the start of your presentation. If you do not notify the session chair before your presentation begins then it will be presumed that you consent to the recording of your session.
Code of Conduct
Space Science Institute is committed to providing a safe, productive, and welcoming environment for all participants in any program hosted or managed by Space Science Institute no matter what role they play or their background. This includes respectful treatment of everyone regardless of gender, gender identity or expression, sexual orientation, disability, physical appearance, age, body size, race, religion, national origin, ethnicity, level of experience, political affiliation, veteran status, pregnancy, genetic information, as well as any other characteristic protected under state or federal law. All participants (and guests) are required to abide by this Code of Conduct.
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This Code of Conduct is adapted from the one adopted by American Geophysical Union (AGU), complies with the new directive from the National Science Foundation (NSF) as well as National Aeronautics and Space Administration (NASA) guidelines, complies with requirements from the American Physical Society (APS), meets the ethics edicts of the American Astronomical Society (AAS), and applies to all Space Science Institute related events.
- All participants are treated with respect and consideration, valuing a diversity of views and opinions
- Be considerate, respectful, and collaborative
- Communicate openly with respect for others, critiquing ideas rather than individuals and gracefully accepting criticism
- Acknowledging the contributions of others
- Avoid personal attacks directed toward other participants
- Be mindful of your surroundings and of your fellow participants
- Alert Space Science Institute staff and suppliers/vendors if you notice a dangerous situation or someone in distress
- Respect the rules and policies of the project and venue
Unacceptable Behavior includes, but is not limited to:
- Harassment, intimidation, or discrimination in any form
- Physical or verbal abuse by anyone to anyone, including repeated use of pronouns other than those requested
- Unwelcome sexual attention or advances
- Personal attacks directed at other guests, members, participants, etc.
- Publishing others' private information, such as a physical or electronic address, without explicit permission
- Alarming, intimidating, threatening, or hostile comments or conduct
- Threatening or stalking anyone, including a participant
- Inappropriate use of sexual language, nudity, or sexual imagery in any venue, including online workshops, meetings, or gatherings, Twitter and other online media.
- Other conduct which could reasonably be considered inappropriate in a professional setting
- Anyone requested to stop unacceptable behavior is expected to comply immediately.
- Space Science Institute staff (or their designee) or security/local police may take action deemed necessary and appropriate, including immediate removal from the event, program without warning or refund.
- Space Science Institute reserves the right to prohibit attendance at a future event, conference, workshop or field project.
- Notification of an infraction to a Home Institution. In cases where there has been a potentially serious policy or code of conduct violation Space Science Institute will notify the offender's home institution.