Rebecca Steinert

WORK HISTORY

EDUCATION

SKILLS

ABOUT REBECCA STEINERT

I\'m an experienced scientist and leader in AI, including machine learning, analytics and statistical modelling. My team builds data-driven capabilities (involving probabilistic modeling and/or deep learning as the problem requires) and tools (including Generative AI) to support critical services and operations with impact at global scale for Amazon. We improve the operations and availability of services with a positive impact on millions of users every year. We leverage off the sciences of data and information processing to build tooling and machine learning capabilities with high business impact. Please see full (slightly outdated) CV or the one-pager summary as pdfs below.Technical expertise:• Expert in artificial intelligence, machine learning, probabilistic and data-driven methods for automated processes and autonomous systems.• Expert skills in programming, operating systems, research tools, data analytics, machine learning techniques and distributed systems.Research leadership expertise:• Expert in proposal writing and driving research proposals to EU, EUREKA, EIT Digital, Vinnova, Swedish Foundation for Strategic Research (SSF) and the Swedish Research Council (VR), etc. together with industry and academia.• Expert in project management and in leading industrial and academic research efforts - individually and in teams, nationally and internationally.• Experience of IPR, patenting processes and standardization.• Substantial leadership and staff management experience, including budgeting, reporting, hiring, supervision, coaching, strategy, organization, public speaking as well as knowledge about data protection regulations (e.g. GDPR) and Swedish/German labor laws.Summary of academic research achievements (RISE/SICS, pre-Amazon):• 45 MSEK (~4.3 MEUR) in project funding as main and co-applicant since 2013.• 43 projects out of which 13 as project leader.• 38 peer-reviewed publications, 976 citations, h-index 14.• 15 talks, presentations, workshops and expert panels.• 6 technical reports, theses and book chapters.• 6 supervision of MSc students (3/6) and PhD students (3/6).• 4 US patents (2/4) and standardization contributions (2/4)• 4 open source code releases, https://github.com/nigsics.