rpcruz@fe.up.pt 0000-0002-5189-6228 github.com/rpmcruz PDF
Ricardo Cruz has worked on a wide range of machine learning topics, with particular emphasis on theoretical aspects of deep learning and computer vision – with 20+ publications and 100+ citations in such topics as: • adapting ranking models for class imbalance; • making convolutional neural networks invariant to background; • making them faster by adjusting the computational effort to each image; • losses for ordinal regression. He is a Post-doc Researcher on autonomous driving at the Faculty of Engineering, University of Porto, and he has been a researcher at INESC TEC since 2015, where his research earned him the computer science PhD in 2021. He has a BSc in computer science and a MSc in applied mathematics. He is frequently invited to teach at the Faculty of Engineering, University of Porto, where he earned a pedagogic award.
Sources (last update: 2024-04-15): • Citation counts are from Crossref. • Impact Factor (IF) comes from each journal's webpage. • SJR rank quantiles are from Scimago and relate to the subject category closest to machine learning (not necessarily the best quantile). • CORE rank is from ICORE for whatever last year is available for that conference.
Last update: 2024-04-15