Enes Algül, Phd Email and Phone Number

I am a Graph Machine Learning Engineer who has both deep academic and hands-on experience holding a PhD degree at University of York. I have deep experience in coding complex data. I represents complex data into graph-structured data or 3D Point cloud structured data forms and combines them with learning algorithms. Then, use these representations in graph kernel methods and Geometric Deep Learning methods. Geometric deep learning methods are based on Graph Neural Networks and 3D Point Cloud methods.On my last project, by labelling biological functions I have developed a large RNA data set from the world-wide protein databank (rcsb.org). I have represented 1/2/3D RNA Data into graph structured forms and 3D point cloud forms in order to use in learning applications. The learning methods are Weisfeiler-Lehman Optimal Assignment (WL-OA), All Path Cycle method (APC), and Shortest Path (SP) kernel method, GDL methods based on Graph Neural Networks (DGCNN, Structure2Vec, GIN, Graph-U-Nets, and LCGNN), and GDL methods based on 3D Point Clouds (PointNet, PointNet++, and PointConv).