Personalized education is proven to produce learning gains for the average student to the order of two standard deviations. Our mission is to apply recent breakthroughs in deep learning to make personalized education accessible to everyone — providing these benefits on a global scale.
Sana is an artificial intelligence company that applies recent breakthroughs in deep learning to personalize education. Sana was founded in Stockholm in 2016 and is backed by a renowned set of investors and advisors. Our interdisciplinary team consists of experienced engineers and scientists with backgrounds ranging from Imperial College and the Royal Institute of Technology to CERN.
The global education industry is vast, valued at over $5 trillion in 2016, and is undergoing a sea change with the move to digital and online instruction, materials and modalities. This shift, to digital and online resources, is enabling what many educators consider to be the holy grail of learning — personalized, adaptive instruction and assessment. With our API, we aim to be the engine that drives forward this change — fundamentally improving the function of the entire industry, directly affecting hundreds of millions of people's lives every day.
An enterprising child, Joel taught himself to code in C at age 13 and founded his first company, a video recommendation technology, at 16. While a senior in high school, Joel developed the initial Sana algorithm. Although it was only the seed of what Sana would become, the technology received widespread attention from world-class investors, advisors and artificial intelligence researchers. Subsequently, at age 20, Joel raised $1M from some of Europe’s most prominent investors to bring Sana to the world.
Anna has 15 years of experience developing and implementing marketing strategies for a wide variety of brands, with a pronounced focus on fast growing tech companies. Previously Anna worked as a Senior Marketing Strategist at Saatchi & Saatchi and King. She currently sits on the board of Stockholm AI.
Susanna earned her PhD in Applied Mathematics at Imperial College London. She previously worked at AstraZeneca, harnessing predictive modelling and segmentation techniques to optimise drug therapies in a selection of target populations, to great effect.
Anton earned his MSc in Applied Mathematics at the Royal Institute of Technology. He previously worked at Ampfield where he researched bayesian engines for implementation in algorithmic trading. Prior to Ampfield, Anton interned at CERN.
Xiaolu earned his PhD in Computer Science at Worcester Polytechnic Institute. While at Worcester, Xiaolu deployed machine learning models to identify student learning patterns and helped over 35,000 students to improve learning performance. He previously interned at IBM, EdX, and Microsoft.
Paul earned his PhD in Aerospace Engineering at the University of Toronto, after which he also excelled in two graduate-level machine learning courses taught by Geoffrey Hinton. He then spent 11 months studying under Hod Lipson and, before joining us at Sana, worked at MDA with AIs for implementation in space and mobile robots.
Andrii earned his MSc in Applied Mathematics at University of Kiev. He previously worked at Google where he built data pipelines for Google Search and, after that, spent 4 years at Spotify working on data insights.
114 34 Stockholm
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