System Description
System descriptions encompass the design, implementation, and evaluation of computational systems addressing diverse challenges. Current research focuses on improving system efficiency and accuracy through techniques like hybrid neural networks for optimal control, fine-tuned BERT models for question answering, and various large language model (LLM) applications for tasks ranging from automatic scoring to creative idea generation. These advancements are significant for improving automation in various fields, from energy management and disaster response to healthcare and education, and for advancing our understanding of AI capabilities and limitations.
Papers
Mixed formulation of physics-informed neural networks for thermo-mechanically coupled systems and heterogeneous domains
Ali Harandi, Ahmad Moeineddin, Michael Kaliske, Stefanie Reese, Shahed Rezaei
Incorporating Total Variation Regularization in the design of an intelligent Query by Humming system
Shivangi Ranjan, Vishal Srivastava