Jim Brase is the Deputy Associate Director for Programs in LLNL’s Computing Directorate. He leads LLNL research in the application of large-scale data analytics and simulation to national security missions. Brase’s research interests focus on machine learning, agent-based modeling, statistical methodologies, and applications to cybersecurity. He has also led programs in laser and imaging research at LLNL.
Felice Lightstone is a Distinguished Member of the Technical Staff and is the leader of the Biochemical and Biophysical Systems Group. Her team uses a wide range of computational biology methods that employ LLNL’s high-performance computing resources to simulate systems from subatomic scale to population level. Her current work focuses developing new computational methods to describe and predict biological systems, including physics-based simulations and statistical and machine-learning models to accelerate the design and development of safe and effective therapeutics. Overall, she seeks predictive understanding of protein-mediated processes related to critical missions of LLNL, including bioenergy, medical countermeasures, and new materials.
Jonathan Allen develops and applies genome sequence analysis software tools for detecting and characterizing pathogenic organisms. His current work focuses on applying novel high performance computing architectures to conduct scalable metagenomics analysis software, as well as the development of algorithms for recovering viral quasi-species populations from ultra-deep next generation sequencing.
Daniel Faissol is the program lead for the predictive design of biologics at LLNL and leads LLNL’s initiative in deep reinforcement learning for national security applications. He currently serves on the LLNL Data Science Institute Council and is the lead for the computational and data science area within the LLNL Bioengineering Center. His work is focused on developing novel approaches for integrating artificial intelligence, simulation, and experimental evaluations to accelerate design and scientific discovery, primarily for antibody and vaccine antigen design applications.
Brian Bennion applies computational approaches to understand the chemistry of small molecules and their interactions with proteins in the human body. He studies the interactions of traditional chemical warfare agents with acetyl and butyryl cholinesterases in order to understand the effects they have on the motions of such important enzymes. This knowledge will guide the design of more effective countermeasures.
Marisa Torres is a Bioinformatics Lead at LLNL. She builds analysis tools to combat disease, specifically contributing to machine learning for drug discovery and pathogen detection. She is currently developing computational models for COVID-19 countermeasures and to fight cancer for the ATOM consortium. Her computational tools help biologists make decisions on public health, and her predictive biology research improves result interpretability for biosecurity. She is interested in building more useful molecular data modeling systems for understanding disease-related mechanisms and treatment.
Matt Coleman is a senior staff biomedical scientist at LLNL in the Biology and Biotechnology division. He is also an adjunct professor in the Department of Radiation Oncology at the University of California at Davis. His major research focus areas lie within radiobiology, in support of cancer treatment and biodosimetry. His group is also active in the development of biotechnology and advanced biochemical techniques around cell-free expression, membrane proteins, and nanoparticles made of apolipoproteins called nanolipoprotein particles (NLPs).
