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2026 Jui Lin (Allen) Yen Award recipients: Mark Dodici and Nolan Koblischke!

Дата публикации: 17-07-2026 16:00:48

I’m pleased to announce the 2026 Jui Lin (Allen) Yen Award recipients: Mark Dodici and Nolan Koblischke. Mark’s award recognizes his contribution to the field of binary stars evolution in the central-parsec zone of galactic center environments, especially with his recently published work “Dynamical Evolution...

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2026 Jui Lin (Allen) Yen Award recipients: Mark Dodici and Nolan Koblischke!

17 Jul 2026

I’m pleased to announce the 2026 Jui Lin (Allen) Yen Award recipients: Mark Dodici and Nolan Koblischke.

Mark’s award recognizes his contribution to the field of binary stars evolution in the central-parsec zone of galactic center environments, especially with his recently published work “Dynamical Evolution of Stellar Binaries in Galactic Centers”, in which he demonstrates that the interactions between the effects of black hole gravity, passing stars, and “vector resonant” interactions with other stars leads a much larger fraction of binaries to plunge close to one another, and then harden into a tightly-bound state, than had previously been predicted. This has significant implications for galactic centre phenomena like the production of hypervelocity stars, extreme mass ratio inspirals, and stellar tidal disruptions, as well as the production of interacting binary systems.

Nolan’s award reflects his work harnessing sophisticated artificial intelligence techniques to create tools that mine large astronomical data sets with natural language. Focusing on galaxy images as a prototype, Nolan captioned a set of 300,000 astronomical images using LLMs. The text embeddings of these captions were aligned with image embeddings from a foundation model in a shared latent space that allowed new text queries to be matched with a database of 100 million images. In his recently submitted paper “Semantic Search for 100M+ Galaxy Images Using AI-Generated Captions”, Nolan benchmarks the code and explores how re-ranking the results with vision-aware LLMs can improve the relevance of top matches and bring the most interesting objects into the top search results. Notably, Nolan has made all the code available and provides a web engine, so you can try it yourself. Ultimately, Nolan’s novel search engine promises to open up the search for rare and important specimens in the galactic zoo.

Mark’s and Nolan’s work highlights the strength of our graduate research, in the long tradition of the Jui Lin (Allen) Yen Award.

Congratulations to both!

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