Kyle Cranmer selected as Editor in Chief of Machine Learning: Science and Technology

The journal Machine Learning: Science and Technology (MLST) has selected Kyle Cranmer as its next editor in chief. Cranmer’s three-year term will begin this week.

Cranmer, who is the incoming director of the American Family Insurance Data Science Institute at UW-Madison and who will join the Department of Physics faculty in July, takes over leadership of this journal from Anatole von Lilienfeld, University of Toronto and TU Berlin. Cranmer has served on the MLST editorial board since its launch in 2019.

“I am honored to take on the role as editor in chief of Machine Learning: Science and Technology,” says Cranmer. “I remember when Anatole first approached me about MLST. I was happy to be part of the effort as I recognized the need for a journal with this scope. That need has only become more clear in the last few years, as we are seeing an explosion in applications of machine learning for scientific research.”

MLST is a multidisciplinary, open-access journal that bridges the application of machine learning across the sciences with advances in machine learning methods and theory. This journal fills a gap in the academic publishing landscape.

Cranmer explains, “The potential for machine learning in the context of science and technology is enormous, but the existing publishing landscape is not well suited to support these developments. Publication of new machine learning techniques in domain-specific journals is a barrier to the cross-pollination of ideas between fields. In contrast, MLST facilitates this cross-pollination of ideas by targeting a multidisciplinary audience.”

During his tenure as MSLT editor in chief, Cranmer says he hopes to address the shortcomings in the conference-oriented machine learning publishing model. He aims to establish the journal as the obvious venue for work highlighting the synergies that result from pairing a machine learning perspective with scientific insight.

Von Lilienfeld expressed his gratitude to Cranmer as he stepped down from his leadership of this journal. “I would like to thank Kyle very much that he agreed to take over, and I very much look forward to MLST’s continued growth and flourishment under his leadership.”

“I would like to thank Anatole for his leadership, and the IOP Publishing team for getting the journal off the ground,” says Cranmer. “The Editorial Board has done a fantastic job of cultivating high-quality, high-impact contributions, and I look forward to working them in service of the community.”

Read more about Machine Learning: Science and Technology on the journal homepage.