Date: 2026-04-13 17:00:00 -0400
Our colleagues at the Institute for Artificial Intelligence and Fundamental Interactions (IAIFI) have announced the IAIFI Summer Workshop 2026, taking place August 10–14, 2026 at MIT, Cambridge, MA. About the Workshop The IAIFI Summer Workshop brings together researchers from across Physics and AI for plenary talks, poster sessions, and networking to promote research at the intersection of Physics and AI. Submissions for contributed talks and/or posters will also be accepted. IAIFI is enabling physics discoveries and advancing foundational AI through the development of novel AI approaches that incorporate first principles, best practices, and domain knowledge from fundamental physics. The goal...
Date: 2026-01-05 09:00:00 -0500
AstroAI was again represented at the 249th AAS meeting!
Date: 2025-03-06 12:50:00 -0500
Revolutionizing Astrophysics with AI Tuesday, March 12, 2024 from 11:30 AM - 12:30 PM, CT in Salon C of the Hilton Austin Downtown If you are at SXSW 2025, come visit our session: https://schedule.sxsw.com/2024/events/PP1145780 At the Center for Astrophysics, we believe ground-breaking discoveries in astrophysics will come from AI. Our goal is to foster a community where top AI and astrophysics experts collaborate at the cutting edge of both fields. Join us to explore the transformative impact that AI is having in astrophysics – from the quest to detect life’s biomarkers on exoplanets to decoding the mysterious physics of black...
Date: 2025-01-15 09:00:00 -0500
Congratulations to AstroAI Director Cecilia Garraffo for being awarded a PECASE. Dr. Cecilia Garraffo, the founding director of AstroAI, has received a Presidential Early Career Award for Scientists and Engineers (PECASE). Dr. Garraffo has made major advances in spin-down of stars, angular momentum evolution, and space weather around exoplanets. Her accomplishments include artificial intelligence applications, a SmallSat concept, and a post-baccalaureate program in astrophysics. PECASE is the highest honor bestowed by the U.S. government on outstanding scientists and engineers who are beginning their independent research careers and show exceptional promise for leadership in science and technology.
Date: 2025-01-11 09:00:00 -0500
AstroAI and EarthAI were well represented at the 247th AAS meeting:
Date: 2024-03-09 23:50:00 -0500
Revolutionizing Astrophysics with AI Tuesday, March 12, 2024 from 11:30 AM - 12:30 PM, CT in Salon C of the Hilton Austin Downtown If you are at SXSW 2024, come visit our session: https://schedule.sxsw.com/2024/events/PP1145780 At the Center for Astrophysics, we believe ground-breaking discoveries in astrophysics will come from AI. Our goal is to foster a community where top AI and astrophysics experts collaborate at the cutting edge of both fields. Join us to explore the transformative impact that AI is having in astrophysics – from the quest to detect life’s biomarkers on exoplanets to decoding the mysterious physics of black...
Date: 2024-01-05 13:03:00 -0500
AstroAI is actively looking for collaborators and researchers at all career stages. If you are interested in working with AstroAI, please check out our Apply page for more details. Please fill out this Google Form by March 31, 2024 to send us your information. We aim to be in contact with everyone who sends us their information by mid-April.
Date: 2023-07-27 20:37:00 -0400
AstroAI member Camilo Fosco was recently interviewed by Wired! The interview discusses how people and AI view artwork as memorable. Read the article here: https://www.wired.com/story/beauty-is-in-the-eye-of-the-beholder-but-memorability-may-be-universal/
Date: 2023-07-13 15:30:00 -0400
Huge congrats to AstroAI’s first intern, Mayeul Aubin, and our dedicated team for clinching the #1 spot in the Ariel Data Challenge by the European Space Agency! Swift models, groundbreaking domain knowledge, and incredible team effort powered our work. Proving once again that the AstroAI model shines bright in the universe of machine learning! AstroAI congratulates Mayeul Aubin, our first intern, for leading multidisciplinary team to victory over a field of 293 teams in the ESA Ariel Data Challenge! The Challenge was a “fox and hounds” competition to solicit the best machine learning approaches for characterizing planetary atmospheric parameters from...
Date: 2023-07-07 21:50:00 -0400
AstroAI congratulates Thaddaeus Kiker finishing 10th in the 2023 Regeneron Science Talent Search. The 2023 finalists were selected from 1,949 highly qualified entrants based on the originality and creativity of their scientific research, as well as their achievement and leadership both inside and outside of the classroom. Each finalist is awarded at least $25,000, and the top 10 awards range from $40,000 to $250,000. Learn more about the project Thaddaeus was working on here: https://www.societyforscience.org/regeneron-sts/2023-student-finalists/thaddaeus-kiker/ More information about the Regeneron Science Talen Search can be found here: https://www.societyforscience.org/regeneron-sts/
Date: 2023-07-07 15:30:00 -0400
AstroAI affiliate Carolina Cuesta-Lazaro was one of three MIT postdocs to be awarded the inagural Mauricio and Carlota Botton Foundation fellowship. Read more about it here: https://news.mit.edu/2023/botton-foundation-fellowships-spanish-mit-physics-postdocs-0609 More information about the Mauricio and Carlota Botton Foundation can be found here (in Spanish): https://www.fundacionbotton.es
Date: 2023-05-22 21:50:00 -0400
AstroAI affiliate Javier Viaña Pérez recently gave a talk at TEDxBoston discussing the importance of explainability and interpretability in the AI community. Watch the talk below:
Date: 2023-04-11 21:50:00 -0400
On April 11, 2023 in Sanders Theatre, 2023 Harvard Horizons Scholar, Harvard Griffin GSAS astronomy student, and AstroAI leadership member Floor Broekgaarden presented her PhD research in her talk “Gravitational Wave Paleontology: a new Frontier to Explore the Lives of Stars to the Edge of our Observable Universe.” Watch the talk below!
Date: 2023-03-20 13:50:00 -0400
The field of machine learning has drawn increasing interest from various other fields due to the success of its methods at solving a plethora of different problems. An application of these has been to train artificial neural networks to solve differential equations without the need of a numerical solver. This particular application offers an alternative to conventional numerical methods, with advantages such as lower memory required to store solutions, parallelization, and, in some cases, a lower overall computational cost than its numerical counterparts. In this work, we train artificial neural networks to represent a bundle of solutions of the differential...
Date: 2023-01-25 13:50:00 -0500
Black hole X-ray binary systems (BHBs) contain a close companion star accreting onto a stellar-mass black hole. A typical BHB undergoes transient outbursts during which it exhibits a sequence of long-lived spectral states, each of which is relatively stable. GRS 1915+105 is a unique BHB that exhibits an unequaled number and variety of distinct variability patterns in X-rays. Many of these patterns contain unusual behaviour not seen in other sources. These variability patterns have been sorted into different classes based on count rate and color characteristics by Belloni et al (2000). In order to remove human decision-making from the pattern-recognition...
Date: 2023-01-24 13:50:00 -0500
AstroAI congratulates Thaddaeus Kiker for being one of the Regeneron Science Talent Search 2023 Finalists. The Society for Science and Regeneron Pharmaceuticals, Inc. congratulate the 40 finalists in the Regeneron Science Talent Search 2023, the nation’s oldest and most prestigious science and math competition for high school seniors. The 2023 finalists were selected from 1,949 highly qualified entrants based on the originality and creativity of their scientific research, as well as their achievement and leadership both inside and outside of the classroom. Each finalist is awarded at least $25,000, and the top 10 awards range from $40,000 to $250,000.
Date: 2023-01-24 13:50:00 -0500
With the upcoming plethora of astronomical time-domain datasets and surveys, anomaly detection as a way to discover new types of variable stars and transients has inspired a new wave of research. Yet, the fundamental definition of what constitutes an anomaly and how this depends on the overall properties of the population of light curves studied remains a discussed issue. Building on a previous study focused on Kepler light curves, we present an analysis that uses the Unsupervised Random Forest to search for anomalies in TESS light curves. We provide a catalogue of anomalous light curves, classify them according to their...
