Daniel Miner

Head of AI DACH: In my current position I manage our AI and Data Science team and lead our AI practice in the DACH region. My current focus, aside from the day-to-day operation of the team and practice, is the development of an end-to-end generative AI offering as well as internal generative AI enablement, usage policies, and strategy.

AI Practice Lead DACH: I worked as the Lead Technical Consultant for AI and Data Science in the DACH region, leading a team of Data Scientists and tripling the team's size, and have been responsible for the development of our technical offerings and skills. As well, I co-led the EMEAL Innovation Center for Quantum Computing.

I worked as a senior technical consultant with a focus on data science, artificial intelligence, and other cutting-edge analytics and operations concepts and technologies such as quantum computing and optimization. At the same time I co-led our AI team and drove our internal and international AI network for the German-speaking market.

My work focuses on modeling the way sequences of stimuli may be stored in the cortex, the way these sequences may be recalled in order to produce sequences of action, and the way that distractions and disruptions to this recall process can effect recall, planning, and decision-making.

The majority of my work focused on understanding the way in which recurrent microcircuits in the cortex self-organize, and the resulting implications for computation and structure in said microcircuits.

I assisted in the final phase construction and commissioning of the hadronic calorimeter of the Compact Muon Solenoid (CMS) experiment on the Large Hadron Collider, and made myself available as an on-call expert for said subsystem. I also spearheaded initial development and analysis on a study of a novel statistical measurement known as the dijet centrality ratio at the CMS experiment.

High-energy experimental particle physics

Physics, with minor in math and extensive additional studies in philosophy