Jesseba Fernando

Network Science Institute @ Northeastern University.

about me

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I’m Jesseba, a Network Science PhD student at Northeastern University. I’m advised by Dr. Sam Scarpino. My research bridges neuroscience and artificial intelligence through network science and information theory.

I study how learning and adaptation reshape networks in brains and machines. My motivation is identifying the principles that predict when networks reconfigure and how those changes affect information flow and function.

Before joining Northeastern, I explored problems in systems neuroscience, studying how motivational states influence attention to sensory cues in the Andermann Lab. I investigated domain adaptation of medical imaging models with William Lotter at Dana Farber Cancer Institute.

news

Jun 12, 2026 Session chair for the neural theory session at Seventh International Conference on Mathematics of Neuroscience and AI.
Mar 16, 2026 Co-organizing the CoSyNe 2026 workshop on Renormalization Principles in Neural Systems with Andrea Santoro and Giovanni Petri.
Jan 16, 2026 Awarded the AccelNet-MultiNet Fellowship. Collaborating with Giovanni Petri, Andrea Brovelli, and Alain Barrat on neural dynamics in Marseille and London this summer.

publications

2026

  1. Bound by semanticity: universal laws governing the generalization-identification tradeoff
    Marco Nurisso, Jesseba Fernando, Raj Deshpande, Alan Perotti, Raja Marjieh, Steven M. Frankland, and 6 more authors
    International Conference on Learning Representations, 2026
    URL arXiv
  2. Dynamics of the Transformer Residual Stream: Coupling Spectral Geometry to Network Topology
    Jesseba Fernando, and Grigori Guitchounts
    arXiv preprint, 2026
    URL arXiv

2025

  1. Transformer Dynamics: A neuroscientific approach to interpretability of large language models
    Jesseba Fernando, and Grigori Guitchounts
    arXiv preprint, 2025
    URL arXiv

2024

  1. Cortical reactivations predict future sensory responses
    Nghia D Nguyen, Andrew Lutas, Oren Amsalem, Jesseba Fernando, Andy Young-Eon Ahn, Richard Hakim, and 5 more authors
    Nature, 2024
    URL
  2. Beyond Structured Attributes: Image-Based Predictive Trends for Chest X-Ray Classification
    Jesseba Fernando, Katharina V Hoebel, and William Lotter
    Proceedings of Machine Learning Research, 250:610–640 , 2024
    URL

2023

  1. Brainstem serotonin neurons selectively gate retinal information flow to thalamus
    Jasmine DS Reggiani, Qiufen Jiang, Melanie Barbini, Andrew Lutas, Liang Liang, Jesseba Fernando, and 5 more authors
    Neuron, 2023
    URL

2022

  1. Visual association cortex links cues with conjunctions of reward and locomotor contexts
    Kelly L McGuire, Oren Amsalem, Arthur U Sugden, Rohan N Ramesh, Jesseba Fernando, Christian R Burgess, and 1 more author
    Current Biology, 2022
    URL