Dr. Doo Nam Kim is a scientist at the Pacific Northwest National Laboratory. His expertise encompasses structural biology, protein structure design, experimental expression and characterization of protein and RNA samples, cheminformatics, and the application of machine learning and quantum chemistry. His significant contributions to the field include the development of automated processes for integrating molecular dynamics-based model fitting into cryo-electron microscopy (cryo-EM) maps and determination of the first three-dimensional structure of a long non-coding RNA. Recently, he directed researchers conducting extensive automated high-throughput docking, along with the execution and examination of AI software for numerous proteins and ligands.

Andrew McNaughton, a computational scientist at Pacific Northwest National Laboratory, enjoys applying his skills in machine learning, AI, and diverse programming languages to explore intriguing problems in biology, chemistry, and astronomy. Currently at PNNL, he contributes to the Modeling & Simulation Team, learning alongside experienced researchers and pursuing his own research interests. He has co-authored publications and presented at conferences, always eager to improve and contribute meaningfully to the scientific community. Andrew's passion lies in understanding the world around him, and he views himself as a continuous learner driven by a genuine interest in tackling complex challenges collaboratively.

Dr. Neeraj Kumar, serving as the Chief Data Scientist at the Pacific Northwest National Laboratory's Advanced Computing, Mathematics, and Data division, is distinguished for his commitment to mentoring and developing staff scientists. His research, covering a broad spectrum including artificial intelligence, applied math, natural language processing, and various computational techniques, significantly advances both practical and theoretical science. Dr. Kumar's extensive list of publications (more than 100), including  scientific articles, reviews, reports, highlights, and technical papers, underscores his profound impact on the field. He is known for his pioneering efforts in computational chemistry and biology, as well as his role in developing advanced and scalable AI/ML systems. His work is notable for its application beyond the academic sphere, offering innovative solutions to intricate challenges in science, biosecurity, and engineering, effectively addressing a spectrum of scientific inquiries.