Jesseba Fernando

Network Science Institute @ Northeastern University.

IMG_2895.jpg

I’m Jesseba, a Network Science PhD student at Northeastern University. I’m advised by Dr. Sam Scarpino. I’m broadly interested in learning and adaptation in both biological and artificial systems and how one can inform the other.

My research focuses on understanding how networks reorganize during learning and adaptation, bridging neuroscience and artificial intelligence through the lens of network science and information theory. I’m particularly interested in how information sharing patterns and network motifs evolve during learning and what governs this reorganization process.

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. This interdisciplinary background, combining neuroscience, machine learning, and network science, has shaped my current approach to understanding complex adaptive systems.

Feel free to reach out if you’d like to discuss potential collaborations or just chat about network science!

news

Sep 04, 2025 Helping organize a satellite at Conference on Complex Systems 2025 in Siena, Italy for Complexity in the Brain!
May 06, 2025 I’ll be attending a working group at the Santa Fe Institute on the Foundations of Adaptive Networks.
Mar 14, 2025 Organizing a Research Symposium at the Network Science Institute! Come visit me at my poster, “Adaptive Learning Mechanisms in Mice and Machines”

selected publications

2025

  1. ArXiv
    spiral_unit_2_mpl_slow.gif
    Transformer Dynamics: A neuroscientific approach to interpretability of large language models
    Jesseba Fernando, and Grigori Guitchounts
    2025

2024

  1. Nature
    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
  2. MIDL
    Beyond Structured Attributes: Image-Based Predictive Trends for Chest X-Ray Classification
    Jesseba Fernando, Katharina V Hoebel, and William Lotter
    Medical Imaging with Deep Learning, 2024

2023

  1. Neuron
    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

2022

  1. Current Biology
    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