Bilal Shabbir presented latest research at the 73rd ASMS Conference on Mass Spectrometry and Allied Topics (ASMS 2025), held in Baltimore, Maryland. The poster, titled “Beyond Mass-Only Filtering: A Multitask Deep Learning Framework for Predicting Peptide Properties from Mass Spectrometry Data,” introduced a novel approach that leverages multitask deep learning to extract richer biological insights from MS data. This work moves beyond traditional mass-based peptide filtering by jointly learning multiple peptide properties, potentially transforming workflows in proteomics and accelerating peptide identification. The presentation drew significant interest from both computational and experimental researchers for its innovation and broad applicability in mass spectrometry-based proteomics.