PNNL

Dennis Thomas is a computational scientist with over 20 years of research experience in developing and applying computational methods for solving problems in basic sciences and engineering. His expertise is in mathematical and physics-based modeling of biological and physical systems at continuum, molecular and mesoscopic length scales and time scales; high-performance computing, machine learning and QSAR modeling; computational pipeline/tools and signature development; ontology and data standards development; graph analytics, and network science. He has authored over 50 peer-reviewed journal articles, four conference papers, two book chapters and several technical reports.

Dennis' doctoral thesis work culminated with 3-dimensional dynamical simulations that showed for the first time, the flow instabilities and spatio-temporal pattern formation in Taylor-Couette flow of viscoelastic dilute polymer solutions. His postdoctoral work resulted in the development of a new ontology and data sharing specification for semantic integration and sharing of data from nanoparticle characterization studies. His recent work focuses on goal hypotheses inference from data using inverse reinforcement learning methods, resilience characterization of critical infrastructure networks using graph analytics and network science methods, and computational pipeline and tool development for enabling the molecular dynamics simulations of peptides and proteins containing non-canonical amino acids.

• Doctor of Science in chemical engineering, Washington University in St. Louis, St. Louis, MO, U.S.A. August 2001 – August 2006
• Master of Science in chemical engineering, Washington University in St. Louis, St. Louis, MO, U.S.A. August 2001 – December 2004
• Bachelor of Technology in chemical engineering, Indian Institute of Technology, Madras (Chennai), India. September 1997 – May 2001

• Outstanding Performance Award in recognition of outstanding contribution in developing a novel dynamic network analysis algorithm for early nuclear proliferation detection, Pacific Northwest National Laboratory (2021)
• Pathway to Excellence award in recognition for a 2020 patent award on “CADDY: Passive Asset Dependence Discovery” (Patent no. 10637744), Pacific Northwest National Laboratory (2021)
• 2nd prize, Best Poster Presentation, 2nd Annual Nanotechnology and the Life Sciences Symposium (2007), St. Louis, MO
• Recipient, Student Travel Grant, 76th Annual Society of Rheology Meeting (2005), Lubbock, TX
• Outstanding Teaching Assistant Award (2003 – 2004), Department of Chemical Engineering, Washington University in St. Louis, St. Louis, MO