WPI-NanoLSI Special Computational Workshop on Digital Solutions （2023年2月8日）
概要
Digital data management, advanced analysis, and machine learning
Modern research efforts benefit from a rapidly increasing ability to generate a wealth of experimental and modelling data. Recent developments in data science, machine learning, and automation provide powerful opportunities to leverage this research data. To use scientific data as a resource beyond its initial publication, database infrastructures and digital workflows must be established to collect, store, organise and analyse the data, with records of how it was produced, and how it was processed or transformed afterwards. Good management of research data is of critical importance to knowledge-led discovery and innovation, and is increasingly embedded in the requirements of research journals and funding bodies. It is a prerequisite step in the application of data science and machine learning techniques in research. In this workshop, we highlight some examples of modern data management and discuss case studies involving the application of machine learning to scientific data. Emphasis is placed on applications to Scanning Probe Microscopy (SPM) in general and Atomic Force Microscopy (AFM) in particular.
日時
2023年2月8日（水）9：30～16：30
オーガナイザー
ナノ生命科学研究所 数理計算科学 特任助教 Damien Hall
開催方式
ハイブリッド
- オンサイト会場： 金沢大学ナノ生命科学研究所 4階 大会議室
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参加登録費
無料
使用言語
英語
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プログラム （日本時間）
February 8th – Wednesday 9:30am – 12:30pm
Adam Foster: Workshop overview, digital workflows, open data, advanced analysis
David Gao: Introduction to digital data and machine learning tools
Filippo Canova: Highly optimized data management tools
February 8th – Wednesday 1:30pm – 4:30 pm
Adam Foster: Advanced analysis of AFM images
Niko Oinonen: Disease recognition from AFM adhesion measurements
Damien Hall: Computational AFM tools for biophysical measurements of dynamic surfaces
ブックレット
主催
金沢大学ナノ生命科学研究所