Editorial board

Scientific leadership of Machine Learning: Health will be provided by the Editor-in-Chief and will be supported by an Editorial Board with broad scientific and geographical distribution.

Machine Learning: Health is currently making appointments to the Editorial Board and this page will be updated accordingly in due course. Through the process of Board Member appointment we strive for scientific, gender, geographic, and ethnic diversity, and welcome nominations from the community. For further information please contact our Publishing team: mlhealth@ioppublishing.org

Editor-in-Chief

Jimeng Sun, University of Illinois Urbana-Champaign, USA

Dr. Sun’s research focuses on using artificial intelligence (AI) to improve healthcare. This includes deep learning for drug discovery, clinical trial optimization, computational phenotyping, clinical predictive modeling, treatment recommendation, and health monitoring. He has been recognized as one of the Top 100 AI Leaders in Drug Discovery and Advanced Healthcare. Dr. Sun has published over 300 papers with over 25,000 citations, and h-index 81. He collaborates with leading hospitals such as MGH, Beth Israel Deaconess, Northwestern, Sutter Health, Vanderbilt, Northwestern, Geisinger, and Emory, as well as the biomedical industry, including IQVIA, Medidata and multiple pharmaceutical companies. Dr. Sun earned his B.S. and M.Phil. in computer science at Hong Kong University of Science and Technology, and his Ph.D. in computer science at Carnegie Mellon University.

Executive Editorial Board

Chris Gibbons, Oracle Health, USA
AICDSS, NLP, LLMs, agents, health services research, population health, clinical trials.

Steve Jiang, University of Texas Southwestern Medical Center, USA
Artificial intelligence in medicine.

Holger Fröhlich, Fraunhofer SCAI, Germany
Development and application of AI/ML models for drug target prioritization, precision medicine, and clinical trials.