I am a staff scientist in the Physics and Chemistry of Materials Group (T-1) of the Theoretical Division at Los Alamos National Laboratory (LANL), where my work primarily focuses on assessing quantum advantage for quantum chemistry applications. My research is also focused on the modeling of structural materials, specifically for their application under extreme conditions such as those found in fusion reactors, under shock deformation, and in environments with high radiation exposure.

One of my key areas of expertise lies in the exploration and development of functional materials (bulk to 2D materials). These materials are not just limited to energy applications but also extend to electronics, where they can play a pivotal role in advancing technology. The scope of my work in this domain ranges from conceptualization and computational design to practical applications, ensuring that the materials are versatile and capable of meeting diverse technological needs.

A significant portion of my research is also dedicated to leveraging machine learning algorithms to expedite our understanding and development of these materials. By utilizing advanced machine learning techniques, I aim to uncover and interpret complex, hidden correlations within vast datasets. This approach not only accelerates the research process but also opens new pathways for innovation in material science. I focus on developing virtual characterization tools to complement experiments. In my role at LANL, I also collaborate closely with a team of distinguished scientists and researchers.