Harry Hochheiser

Harry Hochheiser is an Assistant Professor in the Department of Biomedical Informatics at the University of Pittsburgh School of Medicine, where he also serves as Associate Director of the Biomedical Informatics Training Program. His academic career spans multiple disciplines at the intersection of computing and healthcare, with a strong focus on human-computer interaction, bioinformatics, and medical informatics.

Dr. Hochheiser's research interests include human-computer interaction, information visualization, bioinformatics, universal usability, security, privacy, and public policy implications of computing systems. His work particularly focuses on NIH-funded projects related to bioinformatics research portals, visualization for review of chart records, and tools for aiding the discovery of animal models of human diseases. His research demonstrates a commitment to developing technology that addresses real clinical needs while considering user experience and ethical implications.

His publication record shows consistent scholarly output across multiple domains, with recent work emphasizing biomedical informatics, machine learning applications in healthcare, epidemiological modeling, and academic publishing practices. His research demonstrates a strong interdisciplinary approach that bridges computer science with clinical medicine and public health, with particular attention to human-centered design principles in healthcare technology.

• Editorial Board Member, PeerJ - the Journal of Life & Environmental Sciences
• Editorial Board Member, PeerJ Computer Science
• Over 2,900 points on PeerJ representing 2,800 editorial contributions and 105 reviews

Dr. Hochheiser has made significant contributions across numerous subject areas including Science and Medical Education, Science Policy, Statistics, Human-Computer Interaction, Computational Science, Bioinformatics, and many others. His work has practical implications for healthcare technology development, particularly in creating more effective, user-friendly systems that address real clinical needs while considering privacy and security concerns.