J. Sollerman

About

J. Sollerman is a leading figure in time-domain astronomy, specializing in the study of gamma-ray bursts (GRBs) and supernovae (SNe). His early, highly influential work on GRB 060927—a paper with 66 citations—pushed the boundaries of observational cosmology by detecting an optical afterglow just 20 seconds after the burst, providing one of the earliest rest-frame views of the universe’s end of the Dark Ages. More recently, Sollerman has been instrumental in advancing the automated classification of transients. He co-developed the "byecr" and "contsep" modules for the SEDMachine (57 citations), which are critical for cleaning spectral data of cosmic rays and non-target light, a major bottleneck in modern sky surveys. His latest work, "CCSNscore" (2025), introduces a multi-input deep learning tool that rapidly classifies core-collapse supernovae from Zwicky Transient Facility spectra. With a career spanning from high-redshift GRBs to cutting-edge machine learning for supernova taxonomy, Sollerman’s contributions are essential for handling the deluge of data from next-generation surveys, making him a key architect of the automated transient discovery pipeline.

Research Focus

Key Achievements

Top Papers

1. 1
   Detection of GRB 060927 at<i>z</i>= 5.47: Implications for the Use of Gamma‐Ray Bursts as Probes of the End of the Dark Ages

   66 citations · 2007
2. 2
   New Modules for the SEDMachine to Remove Contaminations from Cosmic Rays and Non-target Light: byecr and contsep

   57 citations · 2022
3. 3
   CCSNscore: A Multi-input Deep Learning Tool for Classification of Core-collapse Supernovae Using SED-machine Spectra

   5 citations · 2025

Key Collaborators

Contact & Links