Jan. 16, 2024, 12:02 a.m. | Michael Galkin

Towards Data Science - Medium towardsdatascience.com

State-of-the-Art Digest

Graph & Geometric ML in 2024: Where We Are and What’s Next (Part I — Theory & Architectures)

Following the tradition from previous years, we interviewed a cohort of distinguished and prolific academic and industrial experts in an attempt to summarise the highlights of the past year and predict what is in store for 2024. Past 2023 was so ripe with results that we had to break this post into two parts. This is Part I focusing on …

academic architectures art artificial intelligence deep-dives experts geometric-deep-learning graph graph-machine-learning industrial machine learning next part prolific state theory tradition

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Tableau/PowerBI Developer (A.Con)

@ KPMG India | Bengaluru, Karnataka, India

Software Engineer, Backend - Data Platform (Big Data Infra)

@ Benchling | San Francisco, CA