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John Dagdelen

2 articles
United States airth.io

Biography

John Dagdelen is a senior PhD candidate in the materials science and engineering department at UC Berkeley and the head machine learning advisor at Airth.io. His research sits at the intersection of computational materials science, artificial intelligence, and high-performance computing. He is an expert on how machine learning techniques can be used to accelerate scientific discovery.

Publications by Year
Showing 2 of 2
Improving Resource Models with Reconciliation driven Machine Learning
John Dagdelen airth.io
Ferhat Koc airth.io
Mustafa Kaplan airth.io
Minerals and Materials Technical Session
Artificial Intelligence in Resource Estimation II
CIM 2023 Convention Montreal
Advancing Short-Range Resource Modeling through Machine Learning: A Case Study with airth.io and Capstone Copper
Erik Anderson airth.io
James Adu JNA Resource Advisory
John Dagdelen airth.io
Digitization in Mining: Risks and Opportunities Technical Session
Digitization of the Resource I
CIM Connect 2024 Vancouver