Chemical Informatics: We combine computational chemistry and machine learning to mine chemical space for fragrant molecules and predict their smell.

Neuromorphic computing: We develop event-based algorithms for neuromorphic olfaction, with the aim to achieve low-latency detection and identification of odorants and other chemical signals. 

Gas-based robotic navigation: We apply neuromorphic principles to improve robot navigation on odor cues. 

Dr Schmuker's research aims at translating algorithms and processes from biology and the brain into solutions for data science and machine learning. He is a pioneer in neuromorphic computing, an emerging technology that takes inspiration from the brain to achieve low-power and low-latency AI. He and his team develop event-based algorithms for neuromorphic olfaction, that is, low-latency detection and identification of chemical signals. 

Dr Schmuker has a degree in Biology, a PhD in Chemical Informatics, as well as postdoctoral experience in developing and applying data science methods in Neuroscience, Chemistry, and Computer Science, solving problems in a wide area of fields ranging from drug discovery and brain imaging to gas sensing in turbulent environments. Before joining the University of Hertfordshire in 2016, he held a Marie Curie Fellowship at the University of Sussex.

Dr Schmuker is a member of the European research flagship "Human Brain Project”, where he led the work package “Neuromorphic Applications and Benchmarks”. He is also a founding member of the NEUROTECH consortium to coordinate and support the advancement of neuromorphic technology in Europe. Since August 2020 he is a member of the NeuroNex "Odor to Action" consortium, which investigates how sensory information guides behavior in animals.