Abstract: Scientific knowledge-guided machine learning (KGML) is an emerging field of research where scientific knowledge is deeply integrated in ML frameworks to produce solutions that are scientifically grounded, explainable, and likely to generalize on out-of-distribution samples even with limited training data. In this talk, we will demonstrate using both scientific knowledge and data as complementary sources of introduction in the design, training, and evaluation of ML models on scientific domains that is of interest to Department of Energy and ORNL. Particularly, we will show some of our recent research in the area of material and battery design.

Short Bio: **Dr. Ramakrishnan (Ramki) Kannan** is a distinguished scientist leading the Discrete Algorithms group at Oak Ridge National Laboratory (ORNL). His research expertise spans distributed machine learning and graph algorithms on High-Performance Computing (HPC) platforms, focusing on accelerating scientific discovery by significantly reducing computation times, often from weeks to seconds.

Dr. Kannan's notable achievements include leading the DSNAPSHOT project for COVID-19, a finalist for the ACM Gordon Bell Award in 2020 and 2022, Summit ranking 3rd on the Graph500 benchmark and achieved 1 ExaFLOPS on a KnowledgeGraph AI application on Frontier and  UT-Battelle Research Accomplishment Award in 2023.

With a track record of securing over $8M in research funding and leading projects exceeding $1 million for the Department of Defense, Dr. Kannan currently serves as the Deputy Director for the DOE Mathematical Multifaceted Integrated Capability Center (MMICC) [Sparsitute](https://sparsitute.lbl.gov/). He co-authored 'Knowledge-guided Machine Learning' with Prof. Anuj Karpatne of Virginia Tech and Prof. Vipin Kumar of the University of Minnesota, a significant publication in 2022. Dr. Kannan holds over 24 patents issued by the USPTO and has been recognized as an IBM Master Inventor. He earned his Ph.D. under Professor Haesun Park at Georgia Institute of Technology and his M.Sc (Engg) under Professor Y. Narahari at the Indian Institute of Science.