Dr. Nicolai Waniek
Scholar

Dr. Nicolai Waniek

Google Scholar ID: l48ORlAAAAAJ
Department of Mathematical Sciences, NTNU
Computational NeuroscienceMachine LearningSelf-Organization and EmergenceNatural Computing
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Citations & Impact
All-time
Citations
166
 
H-index
6
 
i10-index
6
 
Publications
20
 
Co-authors
0
 
Contact
Emailinfo@rochus.netCVOpen ↗TwitterOpen ↗GitHubOpen ↗LinkedInOpen ↗
Publications
20 items
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
  • - Publications:
  • - 2025 Preprint: S. Storesund, K. V. Aars, R. Dietrich, N. Waniek. Predictive Spike Timing Enables Distributed Shortest Path Computation in Spiking Neural Networks.
  • - 2025 Preprint: R. Dietrich, T. Fischer, N. Waniek, N. Reeb, M. Milford, A. Knoll, A.D. Hines. Threshold Adaptation in Spiking Networks Enables Shortest Path Finding and Place Disambiguation.
  • - 2024 Paper: R. Dietrich, N. Waniek, M. Stemmler, A. Knoll. Grid Codes versus Multi-Scale, Multi-Field Place Codes for Space.
  • - Patents: Contributions in computational neuroscience, machine learning, and neuromorphic computing
Research Experience
  • - Current Research: Neural computations underlying whisker behaviors and spatial navigation in rodents, and adaptive camouflage in cuttlefish, with a focus on uncovering the algorithmic logic embedded in population dynamics
  • - Past Research: Developed a spiking neural network model that implements optimal shortest-path search using only local spike-timing rules, and a computational theory of grid cells as optimal multi-scale search algorithms
  • - Applications: Applied these principles to practical problems in robotics, leading development of a perception framework for manipulation and a sim2real rendering pipeline
Education
  • - PhD: Computer Science (Neural and Neuromorphic Computing), TU Munich, Germany
  • - Advisor: Not explicitly mentioned
  • - Degree Time: Not explicitly mentioned
  • - Master's Degree: Computer Science, Ulm University, Germany
  • - Work Experience: Fully-qualified professional software developer at Celos Computer GmbH
Background
  • - Research Interests: How brains implement algorithms
  • - Professional Field: Formal Algorithmic Neurodynamics, Computational Neuroscience, Machine Learning, Neuromorphic Computing
  • - Introduction: Studies how computational operations emerge from continuous neural dynamics, spike timing, oscillatory coupling, and distributed circuit interactions across brain regions. Develops computational models based on first principles to identify algorithmic primitives and data structures realized in neural circuits, and to understand how these compose into complex behaviors.
Miscellany
  • - Teaching: Teaches courses
  • - Organizing Activities: Co-organizes summer schools
  • - Mentoring Program: Initiated a progressive mentoring program that introduces reverse mentoring to executive leadership
Co-authors
0 total
Co-authors: 0 (list not available)