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Questions?
Suzanne Sindi, UC Merced | ssindi [at] ucmerced.edu (ssindi[at]ucmerced[dot]edu)
Vagelis Papalexakis, UC Riverside | epapalex [at] cs.ucr.edu (epapalex[at]cs[dot]ucr[dot]edu)
Brian Gallagher, LLNL | gallagher23 [at] llnl.gov (gallagher23[at]llnl[dot]gov)
Omar DeGuchy, LLNL | deguchy1 [at] llnl.gov (deguchy1[at]llnl[dot]gov)
Mary Silva, LLNL | silva223 [at] llnl.gov (silva223[at]llnl[dot]gov)
Sira Neily, LLNL admin | neily1 [at] llnl.gov (neily1[at]llnl[dot]gov)
You could help advance world-class science this summer!
LLNL staff like to lead by example, and you'll work with some of our most talented and dedicated scientists.
Meet your mentors
Student Internships Director: Brian Gallagher, a computer scientist, directs LLNL's Data Science Summer Internships program. “My main goal is to provide an environment where everyone can grow,” he says. When he’s not working with students, he leads the Data Science & Analytics Group at LLNL’s Center for Applied Scientific Computing. His primary research interest is machine learning for scientific applications. He contributes to several projects in the areas of nuclear threat-reduction, computer networks, and materials discovery and development. Brian joined LLNL in 2005 after earning an M.S. in Computer Science at the University of Massachusetts Amherst in 2004 and a B.S. in Computer Science from Carleton College in 1998.
DSC Lead: Omar DeGuchy works on the development and application of deep learning models for object detection across a variety of modalities. A former LLNL intern, Omar focuses his research on machine learning, deep learning, multimodal object detection, and adversarial machine learning. He holds a Ph.D. in Applied Mathematics from UC Merced and an M.S. in Mathematics from Cal Poly Pomona.
Student Integration Lead: Mary Silva works in LLNL’s Global Security Computing Applications Division on the GUIDE program and the multi-institutional SPOKE project. Mary is a former LLNL intern and now serves as ambassador to the global Women in Data Science (WiDS) organization. Her research interests include machine learning and AI for bioinformatics, protein structure modeling, and protein sequence modeling. Mary has an M.S. in Statistics and Applied Math from UC Santa Cruz and a B.S. in Applied Math from San Francisco State University.
Lead Mentor: Mikel Landajuela is a machine learning researcher in LLNL’s Computational Engineering Division. His research interests include scientific computing, machine learning, computational mechanics, and mathematical modeling. Honored with the SMAI-GAMNI (French Society of Industrial and Applied Mathematics) award in 2017 for the best thesis in numerical methods for the mechanical and engineering sciences, Mikel holds a PhD in Computational and Applied Mathematics from Université Pierre-et-Marie-Curie and is part of the LLNL team that claimed a top prize at a 2022 international symbolic regression competition.
