Nicole Sandra-Yaffa Dumont
Zürich, Switzerland Email: nidumon@ini.uzh.ch Website: nsdumont.github.io LinkedIn: nicole-dumont Github: nsdumont Scholar: 2hnh9gkAAAAJ ORCID: 0000-0001-5041-1527
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Academic Appointments

Postdoctoral Researcher
Institute of Neuroinformatics (University of Zurich & ETH Zurich)
Dec 2025 – Present Zürich, Switzerland
  • Supervisor: Prof. Katharina Wilmes
  • Awarded the UZH Postdoc Grant, beginning December 2026.
  • Predictive Coding (PC) & Models of Perception and Learning in Cortex
    • Comparing prediction error modulation by learned uncertainty signals and how this mechanism differs from top-down, goal-conditioned attentional modulation.
    • Developing PC networks for multi-sensory integration to better understand integration circuits in the brain.

Education

Ph.D in Computer Science
Diploma in Theoretical Neuroscience
University of Waterloo
Sept 2019 – April 2025 Waterloo, Canada
  • Supervisors: Prof. Chris Eliasmith and Prof. Jeff Orchard
  • Dissertation: Symbols, Dynamics, and Maps: A Neurosymbolic Approach to Spatial Cognition [Link]
  • Neuro-Symbolic Modeling for Spatial Representation & Mapping
    • Developed Spatial Semantic Pointers (SSPs) as a grid cell-inspired representation of continuous features, enabling the integration of symbolic structure and uncertainty in biologically plausible neural models.
    • Built spiking neural network models of path integration, cognitive mapping, and SLAM that use neurosymbolic methods to bind continuous and discrete features to create compositional embeddings.
  • Reinforcement Learning (RL) & Action Selection
    • Designed biologically plausible online learning rules for RL in continuous-time settings using State Space Model-based memory systems.
    • Incorporated SSPs into Bayesian Optimization and deep RL frameworks, modeling predictive inference and decision-making under uncertainty.
Computational Mathematics (Masters of Mathematics – Co-op Program)
University of Waterloo
Sept 2017 – April 2019 Waterloo, Canada
Honours Mathematics and Physics (Bachelors of Science)
McMaster University
Sept 2012 – April 2017 Hamilton, Canada

Work Experience

Research Associate
Computational Neuroscience Research Group, University of Waterloo
April 2025 – Nov 2025 Waterloo, Canada
  • Contributed to the incorporation of spatial reasoning and embodiment in Spaun 3.0, a large-scale functional brain model.
Neuromorphic Scientist
Applied Brain Research
Jan 2023 – Jan 2024 Waterloo, Canada
  • Integrated a biologically-inspired SLAM algorithm into a MuJoCo simulation environment and deployed it on low-power neuromorphic hardware (Intel Loihi chip).
Research Associate
Cayuga Research
May 2018 – Aug 2019 Waterloo, Canada
  • Consulting work focused on developing optimization methods and data-driven solutions for industrial applications.
Research Assistant
Ayers Research Group, McMaster University
May 2015 – Aug 2015 Hamilton, Canada

Research

h-index = 7, i10-index = 5, total citations = 171 (Google Scholar on 25/08/2026)

† = These authors contributed equally

Publications & Conference Proceedings

  • Furlong, P.M.†, Dumont, N.S.†, Antonova, R.†, Orchard, J., & Eliasmith, C. (2026). Compositional neurosymbolic representations enable efficient active exploration. Nature Communications. https://doi.org/10.1038/s41467-026-75703-4 [Link]
  • Dumont, N.S., Furlong, P. M., Orchard, J., & Eliasmith, C. (2023). Exploiting semantic information in a spiking neural SLAM system. Frontiers in Neuroscience, 17. [Link]
  • Dumont, N.S.†, Stöckel, A.†, Furlong, P. M.†, Bartlett, M., Eliasmith, C., & Stewart, T. C. (2023). Biologically-Based Computation: How Neural Details and Dynamics Are Suited for Implementing a Variety of Algorithms. Brain Sciences, 13(2). [Link]
  • Voelker, A. R., Blouw, P., Choo, X., Dumont, N.S., Stewart, T. C., & Eliasmith, C. (2021). Simulating and Predicting Dynamical Systems With Spatial Semantic Pointers. Neural Computation, 33(8). [Link]
  • Coleman, T. F., Dumont, N.S., Li, W., Liu, W., & Rubtsov, A. (2021). Optimal Pricing of Climate Risk. Computational Economics. [Link]

Conference Proceedings & Posters

  • Dumont, N.S. & Wilmes, K. A. (2026). Multi-sensory Integration in Predictive Processing. [Accepted, poster presentation scheduled for Bernstein Conference, Sep 28 – Oct 1, 2026].
  • Simone, K., Steffen, L. C., Dumont, N.S., Yu, S., Ly, H., Damberger, G., & Eliasmith, C. (2026). Semantic map learning and externalization in an embodied neural agent: A comparison to human behavioral and neural data. CogSci, 48(48).[Link]
  • Furlong, P. M., Simone, K., Dumont, N.S., Bartlett, M., Stewart, T. C., Orchard, J., & Eliasmith, C. (2024). Biologically-Plausible Markov Chain Monte Carlo Sampling from Vector Symbolic Algebra-Encoded Distributions. ICANN. [Link]
  • Furlong, P. M., Dumont, N.S., & Orchard, J. (2024). A Recurrent Dynamic Model for Efficient Bayesian Optimization. NICE. [Link]
  • Bartlett, M., Simone, K., Dumont, N.S., Eliasmith, C., & Orchard, J. (2023). Improving reinforcement learning with biologically motivated continuous state representations. ICCM. [Link]
  • Dumont, N.S., Orchard, J., & Eliasmith, C. (2022). A model of path integration that connects neural and symbolic representation. CogSci, 44(44). [Link]
  • Bartlett, M.†, Dumont, N.S.†, Furlong, M. P., & Stewart, T. C. (2022). Biologically-Plausible Memory for Continuous Time Reinforcement Learning. ICCM. [Link]
  • Dumont, N.S., Stewart, T. C., & Eliasmith, C. (2021). Spiking neural network model of simultaneous localization and mapping with Spatial Semantic Pointers. [Poster presented at CoSyNe, February 23–26, 2021]. [Link]
  • Dumont, N.S. & Eliasmith, C. (2020). Accurate representation for spatial cognition using grid cells. CogSci. [Link]

Manuscripts

  • Sainz Villalba, L., Furlong, P. M., Bartlett, M., & Dumont, N.S. (2026). Neural Representational Geometry of Feature Binding Operations. bioRxiv. [Link]

Patents

  • Voelker, A. R., Eliasmith, C. D., Blouw, P., Stewart, T., & Dumont, N.S. (pending, filed November 5, 2021). Methods and systems for simulating and predicting dynamical systems with vector-symbolic representations. [US Patent App. 17/520,379] Google Patents. [Link]

Teaching and Supervision

  • Masters supervision (2026-present): Supervising a masters student thesis project on learning compositional neural representation for planning and reasoning with tree diffusion.
  • Student supervision (2020): Supervised an undergraduate research assistant during a four-month project developing a novel algorithm for learning successor features for reinforcement learning.
  • Introduction to Computational Mathematics (2022): Sole instructor for two sections of this course, teaching over 120 students. Planned course content and developed lectures, assignments, and exams.
  • Logic and Computation (2020): Served as an Instructional Apprentice for an introductory course in mathematical logic. Led tutorials, graded assignments, and provided assistance during office hours.
  • Teaching Assistantships (2017-2022): Served as a TA in six undergraduate courses in mathematics and computer science.

Academic Service

  • Leadership & Organization
    • Topic Area Leader, Spatiotemporal Dynamics in Neural Computation, Telluride Neuromorphic AI Workshop (2026)
    • Topic Area Leader, Language and Thought, Telluride Neuromorphic Cognition Engineering Workshop (2025): Successfully proposed and led a topic area; delivered tutorials on cognitive mapping models; mentored PhD-level researchers through the full project lifecycle from conceptualization to demonstrations for the public.
    • Invited Speaker & Co-Organizer, Telluride Neuromorphic Cognition Engineering Workshop (2024)
  • Instruction & Training
    • Instructor, Nengo Summer School (2023, 2024, 2025): Led tutorials and mentored participants developing neural models using the Nengo framework.
  • Peer Review: Reviewer for Nature Communications, Communications Biology, CogSci 2025, and Frontiers in Computational Neuroscience

Awards & Distinctions

  • UZH Postdoc Grant (2026)
  • Marie Skłodowska-Curie Postdoctoral Fellowship (MSCA-PF) Seal of Excellence (2026)
  • Best New Neuromorph, Telluride Neuromorphic Cognition Engineering Workshop (2024)
  • European Neural Network Society Best Paper Award (2024)
  • Barbara Hayes-Roth Award for Women in Math and Computer Science (2022)
  • GO-Bell Scholarship (2019–2021)
  • Provost Doctoral Entrance Award for Women (2019)
  • Keith & Debbie Geddes Graduate Scholarship (2019)
  • University of Waterloo Graduate Scholarship (2018–2019)
  • Emanuel Williams Scholarship in Physics (2014)