This page highlights selected leadership, strategy, and technical contributions.
I keep this curated rather than exhaustive.

Flagship highlights

Leading Information & Data Science across Helmholtz (2023–present)

As Head of Information & Data Science at Helmholtz head office, I coordinate strategy and execution across 18 research centres and six research fields, connecting a network of professionals spanning AI, data science, and IT leadership.

Building an innovation pipeline that secured >20M€ funding

I initiated and led multiple Information & Data Science incubator workshops, resulting in large-scale strategic programmes on foundation models for scientific research, software engineering, and benchmarking.

European flagship leadership: EU Human Brain Project (2014–2023)

PI / Work Package leader / Task leader across multiple phases of the Human Brain Project, with leadership responsibilities for applications and benchmarks in neuromorphic computing.

Machine olfaction at the speed of biology (Science Advances, 2024)

Work demonstrating high-speed odor sensing using a miniaturized electronic nose — relevant to sensing, robotics, and real-world ML under drift and noise.

Limits of generalization in neuromorphic olfaction (Nature Machine Intelligence, 2024)

Work outlining limitations in odor recognition and generalization in a neuromorphic olfactory circuit — relevant to robustness, evaluation, and out-of-distribution generalization.

Expert roles and international visibility

Invited expert to the Scientific Advisory Board of the Organisation for the Prohibition of Chemical Weapons (OPCW) and speaker at 80+ invited talks, seminars, and keynotes.

Domain expertise (selected)

Data science & AI

  • AI strategy and readiness
  • ML systems review and technical evaluation
  • Benchmarking and validation
  • Data governance and research data infrastructures
  • Responsible AI and risk-aware implementation

Chemical sensing, machine olfaction & electronic noses

  • High-speed sensing and real-time inference
  • Robust ML under drift and noise
  • Spatio-temporal signal structure (e.g., turbulence)
  • Neuromorphic sensing and event-based inference
  • Deployment under real-world constraints

Selected publications (curated)

  • Dennler N. et al., Schmuker M. (2024). Science Advances — High-speed odor sensing using a miniaturized electronic nose.
    [DOI]

  • Dennler N., van Schaik A., Schmuker M. (2024). Nature Machine Intelligence — Limitations in odour recognition and generalization in a neuromorphic olfactory circuit.
    [DOI] [arXiv]

  • Schmuker M., Pfeil T., Nawrot M.P. (2014). PNAS — A neuromorphic network for generic multivariate data classification.
    [DOI]

  • Schmuker M., Schneider G. (2007). PNAS — Processing and classification of chemical data inspired by insect olfaction.
    [DOI]

  • Rajendran B. et al., Schmuker M. (2019). IEEE Signal Processing Magazine — Low-power neuromorphic hardware for signal processing applications.
    [DOI] [arXiv]

  • Parma V. et al. incl. Schmuker M. (2020). Chemical Senses — More than smell: COVID-19 chemosensory impairment.
    [DOI]

➡ Full list: Google Scholar profile