Jesseba Fernando

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

Oct 20, 2025	I will be attenting a Renormalization for AI Safety workshop organized by Principles of Intelligent Behavior in Biological and Social Systems (PIBBSS) held in Cambridge, MA!
Sep 03, 2025	Helping organize a satellite at Conference on Complex Systems 2025 in Siena, Italy for Complexity in the Brain!
Sep 02, 2025	Gave a talk on adaptive learning mechanisms in mice and machines at Conference on Complex Systems 2025 in Siena, Italy!

selected publications

2025

ArXiv

Transformer Dynamics: A neuroscientific approach to interpretability of large language models

Jesseba Fernando, and Grigori Guitchounts

2025

arXiv Bib

@article{2025-fernando,
  title = {Transformer Dynamics: A neuroscientific approach to interpretability of large language models},
  author = {Fernando, Jesseba and Guitchounts, Grigori},
  year = {2025},
  publisher = {ArXiv},
}

ArXiv

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

2025

arXiv Bib

@article{2025-nurisso,
  title = {Bound by semanticity: universal laws governing the generalization-identification tradeoff},
  author = {Nurisso, Marco and Fernando, Jesseba and Deshpande, Raj and Perotti, Alan and Marjieh, Raja and Frankland, Steven M. and Lewis, Richard L. and Webb, Taylor W. and Campbell, Declan and Vaccarino, Francesco and Cohen, Jonathan D. and Petri, Giovanni},
  year = {2025},
  publisher = {ArXiv},
}

2024

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

URL Bib

@article{2024-nguyen,
  title = {Cortical reactivations predict future sensory responses},
  author = {Nguyen, Nghia D and Lutas, Andrew and Amsalem, Oren and Fernando, Jesseba and Ahn, Andy Young-Eon and Hakim, Richard and Vergara, Josselyn and McMahon, Justin and Dimidschstein, Jordane and Sabatini, Bernardo L and Andermann, Mark L},
  journal = {Nature},
  volume = {625},
  number = {7993},
  pages = {110--118},
  year = {2024},
  publisher = {Nature Publishing Group UK},
  url = {https://www.nature.com/articles/s41586-023-06810-1}
}

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

URL Bib

@article{2024-fernando,
  title = {Beyond Structured Attributes: Image-Based Predictive Trends for Chest X-Ray Classification},
  author = {Fernando, Jesseba and Hoebel, Katharina V and Lotter, William},
  journal = {Medical Imaging with Deep Learning},
  year = {2024},
  publisher = {MIDL},
  url = {https://proceedings.mlr.press/v250/hoebel24a.html}
}

2023

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

URL Bib

@article{2023-reggiani,
  title = {Brainstem serotonin neurons selectively gate retinal information flow to thalamus},
  author = {Reggiani, Jasmine DS and Jiang, Qiufen and Barbini, Melanie and Lutas, Andrew and Liang, Liang and Fernando, Jesseba and Deng, Fei and Wan, Jinxia and Li, Yulong and Chen, Chinfei and Andermann, Mark L},
  journal = {Neuron},
  volume = {111},
  number = {5},
  pages = {711--726.e11},
  year = {2023},
  publisher = {Elsevier},
  url = {https://www.cell.com/neuron/fulltext/S0896-6273(22)01079-0}
}

2022

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

URL Bib

@article{2022-mcguire,
  title = {Visual association cortex links cues with conjunctions of reward and locomotor contexts},
  author = {McGuire, Kelly L and Amsalem, Oren and Sugden, Arthur U and Ramesh, Rohan N and Fernando, Jesseba and Burgess, Christian R and Andermann, Mark L},
  journal = {Current Biology},
  volume = {32},
  number = {7},
  pages = {1563--1576.e8},
  year = {2022},
  publisher = {Elsevier},
  url = {https://www.cell.com/current-biology/fulltext/S0960-9822(22)00250-0}
}