(January 2026) Members of the Cool Star Lab presented multiple research results at the 247th meeting of the American Astronomical Society (AAS) in Phoenix, AZ, as part of a large contingent of UCSD Astronomy & Astrophysics and STARTastro researchers. Cool Star Lab PI Adam Burgasser gave a plenary lecture on "The Brown Dwarf-Milky Way Connection: How Failed Stars Play a Unique Role in Galactic Archaeology" and co-hosted a special session titled "JWST ♡ Brown Dwarfs: Discoveries, Populations, and Atmospheres", while current and past members of the CSL team presented various iposters and oral presentations throughout the 4-day conference. Here were the presentations made by current members of the CSL:
Marylin Loritsch (iposter 269.01): "Identifying and Characterizing Low-Temperature Stars and Brown Dwarfs in Deep JWST Spectroscopic Surveys"
Evan Pritchard (iposter 269.02): "Classification and Characterization of Thick Disk and Halo Low Mass Stars in Deep JWST Surveys"
Emma Softich (iposter 269.03 "Should I Stay or Should I Go: Comparing MCMC vs. RFR For Modeling Low Temperature Brown Dwarf Spectra from JWST"
Adam Burgasser (iposter 269.04): "ucdmcmc: A Fast Fitting Algorithm for Cool Star, Brown Dwarf, and Exoplanet Atmospheres"
Julia Haynes (iposter 443.61): "Using Machine Learning to Identify Brown Dwarfs in Deep JWST Surveys"
Special congratulations to our first-time AAS presenters Evan & Julia!
(December 2025) Former Cool Star Lab undergraduate researcher Juan Diego Draxl Giannoni reported the findings of a machine learning project to identify unresolved brown dwarf binaries from combined-light spectra. Using synthetic binaries constructed from the SpeX Prism Library, the team created a hierarchical random forest model that can both distinguish single and binary systems and classify binary components. The models achieved an overall precision of 85% and classification errors of ≤1 subtype, far better than earlier index-based approaches. This study highlights the utility of machine-learning methods for uncovering rare binaries among the large samples of spectra anticipated from SPHEREx and Euclid (read the preprint by Draxl Giannoni et al.).
(December 2025) Cool Star Lab researcher Vivian Liu has been selected as part of the inaugural UCSD TRELS Cohort Experience. TRELS stands for Triton Research & Experiential Learning Scholars, and is a UCSD-wide program to support undergraduate research. The Cohort Experience is a new program that provides cohort meetings, professional events, engagement with faculty and guest speakers, and the opportunity to present at the Spring Mentored Undergraduate Research and Applied Learning Symposium (MURALS) event. Congratulations Vivian!
(December 2025) Cool Star Lab researcher Marylin Loritsch has been awarded the UCSD School of Physical Sciences Selma and Robert Silagi Award for Undergraduate Excellence. This annual award recognizes outstanding graduating seniors in Astronomy & Astrophysics, Biology, Chemistry & Biochemistry, Mathematics, and Physics who demonstrate exceptional academic merit, research, and future promise in their scientific fields. Marylin, a STARTastro scholar and recipient of a AAS Chambliss presentation award, is the first Astronomy & Astrophysics student to win this award. Congratulations Marylin!
(November 2025) South Pasadena high school researcher Wings Zhang reported the discovery of over 100 new high proper stars detected in the UKIRT Hemisphere Survey (UHS), as part of the Backyard Worlds collaboration. Shane 3m Kast spectroscopy obtained by Cool Star Lab members confirmed two sources as metal-poor M subdwarfs 100-200 pc from the Sun, and color and absolute magnitude measurements indicate these sources encompass a wide range of previously unknown, ancient metal-poor low-mass stars (see the AJ article by Zhang et al.).
(November 2025) Recent UCSD graduate Sara Morrissey has reported the findings of her Honors thesis, the discovery of 7 distant L and T dwarfs in deep JWST spectroscopy by the RUBIES survey. Sara used the 1-5 µm spectra to classify her discoveries and determine their temperatures, metallicities, and distances, the last reaching out to 3,000 pc from the Sun. Two of the sources show evidence of being metal-poor brown dwarfs. Congratulations on your first peer-reviewed article Sara! (see the preprint by Morrissey et al.)
(September 2025) Cool Star Lab undergraduate researcher Tianxing Zhou has led a new study investigating machine learning classification methods for low-temperature dwarfs. Drawing on a set of low-resolution near-infrared spectra from the SPLAT archive, Tianxing explored multiple ML models, and found that a k-nearest neighbors algorithm was able to classify 96% of sources to with one subtype and assign gravity and metallicity classifications with 90% accuracy. Tianxing's work advances tools for studying large samples of spectra now emerging from space telescopes such as Euclid and JWST (see the ApJ article by Zhou et al.)