Aristeidis Tsaris is a research scientist in large-scale data science and learning at National Center for Computational Sciences at ORNL. His research focus is on scalable machine learning applications on HPC systems, benchmarking, and imaging. He has been working with scientific applications to scale their analytics algorithms on HPC systems. Before he joined ORNL, Aristeidis received his PhD on Medium Energy Particle Physics from Florida State University, working at Jefferson Lab. He also worked as a postdoc at Scientific Computing Division (SCD) at Fermi National Lab where he contributed to a wide variety of deep learning applications for neutrino and collider physics.
Chemistry and Materials
Climate, Weather and Earth Sciences
Computer Science, Machine Learning, and Applied Mathematics