Joseph Picone

Joseph Picone is a Professor in the Department of Electrical and Computer Engineering at the College of Engineering, Temple University. His research focuses on machine learning and signal processing with applications in biomedical data analysis and digital pathology. He leads the Signal and Information Processing (ISIP) Lab, which develops large-scale, annotated datasets for AI training in healthcare.

His research interests include machine learning, signal processing, digital pathology, biomedical engineering, and artificial intelligence. He has pioneered the development of annotated corpora such as the FCCC Digital Pathology Corpus (FCDP) and TUH DPATH, which support AI-driven cancer detection and medical image analysis. His work bridges engineering and clinical medicine, emphasizing practical, real-world impact.

The recent publications demonstrate a strong trend in applying machine learning to biomedical signals and medical imaging, particularly in neurology and oncology. His research integrates clinical data with advanced AI techniques, focusing on annotation assistance, sensing systems, and diagnostic support tools.

Joseph Picone actively mentors students and leads research initiatives. He organizes the annual IEEE Signal Processing in Medicine and Biology (SPMB) Symposium, fostering collaboration in the field. His lab secures data-sharing grants and supports open science through public data releases.

He leads the Signal and Information Processing (ISIP) Lab at Temple University, which specializes in creating and distributing large, annotated datasets for machine learning in medicine. The lab maintains extensive digital pathology and EEG corpora, supporting global research in AI for healthcare.