A recent joint study between Linköping University and the Department of Forensic Genetics and Forensic Toxicology of the National Board of Forensic Medicine (both in Linköping, Sweden) demonstrated a 32-element metal oxide semiconductor (MOS)-based e-nose, integrated with advanced supervised machine learning (ML) algorithms, for forensic applications including distinguishing human vs. animal samples, postmortem vs. antemortem states, and estimating postmortem intervals. LCGC International spoke to Donatella Puglisi, associate professor at Linköping University, and corresponding author of the paper that resulted from this work.