David has been a visiting researcher developing a library for Causal Inference, while writing a Framework for Validation of AI/ML in Biomedical applications. He has been advising on AL/ML projects being spun-out from Charité Berlin and the Max-Delbrueck Center. He does deep-dives into datasets and toolsets; due diligence; and advises the spin-out teams on how to build their desired technical solutions.
As Head of Data Science of the MIKA App by Fosanis GmbH David helped personalising the delivery of psychological support and content to cancer patients. He brought in sizeable funding, built and managed a team of data scientists, hired a wider team of 14 people, then built a data-science backend.
In a combined research and teaching position, David came into a new lab for computational neuroscience and ended up running the lab for the first months of its existence.
… is a data science expert who has a wealth of expertise creating mathematical models. He likes to abstract real-world systems, find their core, make a formal model and implement it for a real-world use case.
He has setup organisations using the same approach and has combined his abilities with a profound interest in biology and high-performance computing throughout his career. His previous work has provided solutions in sports science, online student assessment and numerous biological and data analytics applications.
Since 2018 David has explored the AI side of the startup world setting up a pre-clinical research company in Berlin and joining the founding team at Fosanis, where he established data-scientific approaches at the core of the product.