Camille Girabawe, Ph.D
About Camille Girabawe, Ph.D
Camille Girabawe, Ph.D, is a Senior Machine Learning Manager at Adobe, where she has worked since 2024. She has a strong background in data science and physics, holding a Ph.D. from Brandeis University and experience in various roles within Adobe and other organizations.
Work at Adobe
Camille Girabawe has been employed at Adobe since 2021, where she currently holds the position of Senior Machine Learning Manager. In this role, she has been responsible for overseeing machine learning projects and initiatives. Prior to her current role, she worked as a Data Science Manager at Adobe for three years. During her tenure, she has contributed to various data-driven projects and has utilized her extensive background in data science and machine learning.
Previous Experience at SAP
Before joining Adobe, Camille Girabawe worked at SAP as a Data Scientist from 2017 to 2019. In this position, she focused on data analysis and modeling, applying her skills to enhance business processes. Her experience at SAP provided her with a strong foundation in data science methodologies and practices.
Education and Expertise
Camille Girabawe earned her Bachelor of Science (BSc) in Physics and Material Science from the Kigali Institute of Science and Technology, studying from 2007 to 2011. She then pursued her Doctor of Philosophy (Ph.D.) in Physics at Brandeis University, completing her studies from 2011 to 2017. Her academic background has equipped her with expertise in microfluidics, soft lithography, and photolithography fabrication techniques, as well as proficiency in various programming languages and analytical skills.
Research and Teaching Experience
Camille Girabawe has significant experience in academic settings. She served as a Ph.D. Research Assistant at Brandeis University from 2011 to 2017, where she conducted research in physics. Additionally, she held the position of Head Teaching Assistant for the Introductory Physics Laboratory from 2011 to 2013. Her role as a mentor for Research Experiences for Undergraduates (REU) in 2013 and 2014 further highlights her commitment to education and research.
Technical Skills and Competencies
Camille Girabawe possesses a diverse skill set in programming and data analysis. She is experienced in using MATLAB, R, Python, Tableau, SQLite, TeradataSQL, MongoDB, and LabView. Her analytical capabilities include statistics, linear regression, decision trees, and image processing. Additionally, she has problem-solving skills related to reaction-diffusion equations and coupled non-linear equations, which are essential in her field of work.