Marc HON

Marc HON is an Assistant Professor at the National University of Singapore (NUS) under the NUS Presidential Young Professorship, specializing in time-domain astronomy and machine learning applications for NASA missions including Kepler, TESS, and the Roman Space Telescope. His work focuses on characterizing stellar populations and discovering novel astrophysical phenomena through data-driven methodologies.

His research spans asteroseismology for probing stellar interiors and Galactic archaeology to map the Milky Way's evolution using variable stars, alongside exoplanetary science investigations into planetary system evolution, habitable worlds, and James Webb Space Telescope atmospheric characterization. A core methodology involves developing machine learning frameworks like deep learning classifiers and generative models for large-scale astronomical datasets.

HON's publication trends (2018-2024) reveal consistent innovation at the astrophysics-ML intersection, with emphases on red giant asteroseismology, exoplanet dynamics, and scalable analysis pipelines for space telescope data. Key contributions include flow-based stellar evolution emulators, deep learning oscillation detectors, and large-scale TESS Galactic archaeology studies.

Scientific recognition includes:

• NASA Hubble Fellowship (2020)

He actively contributes to major international collaborations as a member of both the TESS and Kepler Asteroseismic Science Consortia, with direct involvement in MIT's TESS mission operations and data pipelines.