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DTSTART;TZID=America/New_York:20261020T130000
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UID:62558-1792501200-1792686600@astrobiology.com
SUMMARY:2026 NASA Cosmic Origins Early-Career Workshop
DESCRIPTION:Registration & Abstract Submission \nNASA’s Cosmic Origins Program is excited to invite you to the second Early Career Workshop\, designed to support and empower the next generation of astrophysics leaders and PIs. \nThe workshop aims to provide insights to early career scientists about the wide range of work done in the Cosmic Origins Program\, to explain and demonstrate the tools and opportunities available to them\, and to answer any questions they may have. \nThis workshop will take place virtually on October 20th-22nd from 1-4:30 pm Eastern. The three days will be focused on Science (Day 1)\, Missions (Day 2) and Careers (Day 3). \nDay 1: Participants will receive an overview of the science themes covered by Cosmic Origins and give early career scientists opportunities to share their research. \nDay 2: We will highlight the many NASA archives\, data analysis tools\, and upcoming proposal opportunities so that participants can see a clear path for themselves to get involved with NASA missions. \nDay 3: Participants will engage with speakers who have taken a variety of career paths that have led them to NASA science and mission work. \nThe abstract submission deadline is October 10th\, 2026 and acceptance notifications will be sent out mid-October. \nFollow the link here to attend. Note: meeting links are listed at the top of each day in the agenda: Additionally\, if you are not a current participant in the NASA Cosmic Pathfinders Program  you can follow the link here to join: https://discord.gg/DsDq5UX8TJ \nOn behalf of the Workshop Science Organizing Committee\, \nRon Gamble\nSwara Ravindranath\nPeter Kurczynski\nAvrajit Bandyopadhyay
URL:https://astrobiology.com/event/2026-nasa-cosmic-origins-early-career-workshop/
LOCATION:Online – Webinar
ATTACH;FMTTYPE=image/png:https://astrobiology.com/wp-content/uploads/2026/09/Cosmic-origins.png
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DTSTART;TZID=America/New_York:20261026T140000
DTEND;TZID=America/New_York:20261026T150000
DTSTAMP:20261026T181536Z
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LAST-MODIFIED:20261026T181536Z
UID:63818-1793023200-1793026800@astrobiology.com
SUMMARY:NASA Science Leadership Town Hall Meeting
DESCRIPTION:NASA will host a community town hall from 2 to 3 p.m. EDT Monday\, Oct. 26\, featuring Dr. Nicola “Nicky” Fox\, associate administrator for the agency’s Science Mission Directorate\, and other NASA science leaders. Fox will provide an overview of NASA’s new Competition Model 2.0 (CM 2.0)\, followed by an opportunity for participants to ask questions. \nMembers of the science community\, academia\, media\, and the public are invited to join the virtual town hall at: \nBROKEN LINK \nhttps://events.gcc.teams.microsoft.com/event/7d9bba42-46cc-4f09-8fb5-95b57c88cf1f@7005d458-45be-48ae-8140-d43da96dd17b?source=copyLinkLegacyShareEventDialog \nCORRECT LINK \n https://teams.microsoft.com/v2/?meetingjoin=true#/l/meetup-join/19:meeting_MjgwNzNlY2UtOGU5Mi00NjU1LTkxYTItNTA4NGMzMTcxYTgw@thread.v2/0?context=%7B%22Tid%22%3A%227005d458-45be-48ae-8140-d43da96dd17b%22%2C%22Oid%22%3A%22c8523246-213e-42ec-bd56-f62fc4a0b891%22%7D&lightExperience=false \nParticipants may submit questions and vote on questions submitted by others at: \nhttps://nasa.cnf.io/sessions/eawk \nQuestions will be screened for spam and inappropriate content before appearing publicly. NASA science leaders will address as many questions as time allows. \nA recording of the town hall will be posted online following the event.
URL:https://astrobiology.com/event/nasa-science-leadership-town-hall-meeting/
LOCATION:Online – Webinar
ATTACH;FMTTYPE=image/png:https://astrobiology.com/wp-content/uploads/2026/01/SMD-2026.png
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DTSTART;TZID=America/New_York:20261027T150000
DTEND;TZID=America/New_York:20261027T170000
DTSTAMP:20261027T001158Z
CREATED:20261027T001158Z
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UID:64049-1793113200-1793120400@astrobiology.com
SUMMARY:NASA Ames Machine Learning Seminar INDUS and INDUS-SDE: Scientific Language Models for Metadata Curation and Discovery Across NASA Science Divisions
DESCRIPTION:JOIN THIS ML SEMINAR SERIES HERE \nTime: October 27th\, 12PM PDT/3PM EDT \nEveryone is invited to the monthly machine learning virtual seminar hosted by the ML-Astrobiology Initiative at NASA Ames Research Center. Previously recorded seminars can be found on the ML-Astrobiology website. \nThe speaker for this event will be Dr. Kumar Ramasubramanian from the NASA-OSDI team and University of Alabama. \nTitle: INDUS and INDUS-SDE: Scientific Language Models for Metadata Curation and Discovery Across NASA Science Divisions \nAbstract: \nScientific discovery in astrobiology depends on content drawn from planetary science\, Earth science\, biology\, and astrophysics\, each with its own terminology\, and distributed across mission websites\, data portals\, technical reports\, and publications with incomplete or inconsistent metadata. \nGeneral-purpose large language models do not resolve this fragmentation. Their answers are bounded by what their training data or retrieval layer happened to cover\, and content that was never indexed or tagged remains invisible regardless of the interface used to query it. A query for all historical Raman spectroscopy data from Mars therefore returns a plausible subset with no guarantee of completeness. \nWe present INDUS\, a family of compact encoder language models developed to address this problem at the level of the archive rather than the query. INDUS models are pretrained on NASA science text across five science divisions and are designed to curate heterogeneous scientific content at scale: assigning controlled-vocabulary keywords\, classifying documents into topical portals\, routing content to the appropriate science division\, and producing embeddings for semantic retrieval. Because they are encoders\, inference cost per document is low enough to process the full corpus continuously rather than sample from it. \nThe first generation of INDUS outperformed general-purpose and scientific baselines on NASA tasks and is deployed in NASA’s Science Discovery Engine. The second generation\, INDUS-SDE\, extends this work to the noisy\, web-sourced content that constitutes most of the archive. \nWe introduce Weighted Dynamic Masking\, a pretraining strategy that prioritizes domain-relevant terminology over structural boilerplate such as website headers\, and an extended 1024-token context window suited to full metadata records. Evaluated on approximately 600\,000 documents\, INDUS-SDE matches domain-specific models trained on substantially more in-domain data\, and its companion sentence transformer\, INDUS-SDE-ST\, supports semantic discovery over the curated corpus. \nFor astrobiology\, this yields a shared representation space in which terminology from different disciplines aligns. In this talk\, we discuss the utility of INDUS models for astrobiology\, with examples of how they can be adapted to a new vocabulary and downstream task from a set of expert-labeled examples. We describe the deployed system\, the requirements for such adaptation\, and the role of community-contributed labeled data in extending INDUS to astrobiology-focused mission development.
URL:https://astrobiology.com/event/nasa-ames-machine-learning-seminar-indus-and-indus-sde-scientific-language-models-for-metadata-curation-and-discovery-across-nasa-science-divisions/
LOCATION:Online – Webinar
ATTACH;FMTTYPE=image/png:https://astrobiology.com/wp-content/uploads/2026/03/NASA-Ames-AIML-Seminar-Series-Machine-Learning.png
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