Director of Engineering for the LINCC Frameworks team
Jeremy Kubica is a director of software engineering who specializes in scalable algorithms and machine learning. He is currently the director of engineering for the LINCC Frameworks team, where he oversees the development of scalable analytical software and frameworks for Rubin’s LSST. He is passionate about the team’s mission to develop software that will enable broad scientific impact on Rubin data. He holds a bachelors in computer science from Cornell University and a PhD in Robotics from Carnegie Mellon University. His thesis work focused on the development of novel tree-based algorithms for the efficient linkage for asteroid detections. He helped develop the first generation moving object pipeline for PanSTARRS and consulted on early LSST algorithms.
Jeremy brings a combination of academic and industrial experience with specific focus on software development and team building. He spent fifteen years at Google where he led multiple projects in applied machine learning, scalable infrastructure, and statistical analysis. Throughout that time he developed significant experience in the importance of developing software that can be broadly used by the community, is long term maintainable by a range of developers, and provide strict accuracy and performance guarantees. He is an advocate for bringing industry best practices to more research software to increase its long term sustainability and impact within the community. He brings extensive experience creating successful teams and mentoring early career leaders.
Jeremy also brings a commitment to public service, mentorship, education, and scientific outreach. He volunteers time to serve as a mentor for multiple early career leaders from industry. He recently served two 3-year terms as a member of the board of trustees for the Carnegie Library of Pittsburgh. In his free time, Jeremy has multiple books on algorithms, data structures, and computational thinking including: the Computational Fairy Tales series, which is aimed at introducing high school aged students to computational thinking, and Data Structures the Fun Way, which is aimed at providing self-taught programmers with a comprehensive introduction to data structures and their uses.