Fostering a New Data Culture with APL Machine Learning

Engage in a thought-provoking discussion during the first APL Machine Learning webinar 'Fostering an Open Data Culture with APL Machine Learning.' Data sharing can speed up the pace and improve science as well as advance researchers’ careers through increased discoverability, reuse, and even increased citations to papers. Learn more about the journal’s data policy that requires all data and code to be publicly available upon submission and explore trends in open data and machine learning research with expert speakers.

Date: Thursday, January 18, 2024
Time: Noon US Eastern time
Registration link: https://aipp.zoom.us/meeting/register/tZctde2hrj4iGdUS8Pl-JSJeMyzeGK3xGw3h#/registration

Moderator:

Adnan Mehonic, Associate Professor, University College London, UK and Editor-in-Chief APL Machine Learning

Dr. Adnan Mehonic is an Associate Professor in nanoelectronics and Senior Royal Academy of Engineering Research Fellow at the Department of Electronic and Electrical Engineering, University College London. He has authored more than 100 journal publications and international conference proceedings on memristive technologies, energy-efficient AI and neuromorphic systems. He is the inventor of numerous international patents and co-founder of a spinout company (IntrinSic Semiconductor Technology). In 2021 he received the MIT’s Technology Review’s The 35 Innovators Under 35 award, recognizing him among 35 exceptionally talented technologists whose work has great potential to transform the world. His work includes co-designing functional materials, devices, circuits, and algorithms to enable energy-efficient on-chip implementation of machine learning/artificial intelligence.

Panelists:

Jason Eshraghian, Assistant Professor, University of California, Santa Cruz, USA and Associate Editor, APL Machine Learning

Jason K. Eshraghian is an Assistant Professor at the Department of Electrical and Computer Engineering at the University of California, Santa Cruz. Prior to that, he was a Post-Doctoral Research at the University of Michigan. He received the Ph.D. (Engineering), Bachelor of Engineering, and Juris Doctor at the University of Western Australia. He serves as the Secretary of the IEEE Neural Systems and Applications Technical Committee, is an Associate Editor with APL Machine Learning, and is a co-founder of Open Neuromorphic. He is the developer of snnTorch, a Python library used to train and model brain-inspired spiking neural networks which has been downloaded over 100,000 times.

Jennifer Ding, Senior Researcher, Research Applications at The Alan Turing Institute, UK

Jennifer Ding is a Senior Researcher in Research Applications at The Alan Turing Institute, the UK’s national institute for data science and artificial intelligence. Previously, she was a startup founder and data scientist at several public interest tech companies, creating data products for industry and government partners. She enjoys massaging data big and small, and is also a co-founder of London Data Week.

Jennifer Muilenburg, Interim Director, Health Sciences Library and Research Data Services Librarian, University of Washington Libraries, Seattle, Washington, USA

Jenny Muilenburg is the Interim Director of the Health Sciences Library and Research Data Services Librarian at University of Washington Libraries. She facilitates the integration of research data support