Brandon Reese develops network algorithms in the Operations Research department within the SAS Analytics R&D division. He began working at SAS in 2018 and focuses on the intersection between graph algorithms and machine learning. His postsecondary degrees include a B. S. in Aerospace Engineering from Massachusetts Institute of Technology and a Ph. D. in Mechanical Engineering from Florida State University.
SAS' Brandon Reese the EURO Meets NeurIPS 2022 Vehicle Routing Competition, which combined efforts of operations research and machine learning experts.
In this introduction to powerful knowledge graph tools, SAS' Brandon Reese shows you how they can predict disease similarity and compound similarity using an unsupervised approach.
A note from Udo Sglavo: A wealth of connectivity is pervasive in the data we gather across many industries. In other words, networks are all around us. A data science trend you cannot ignore is to organize, learn from, and drive decision-making based on connected data. Network analytics engines provide efficient
