Ilenna Jones

Research Fellow

Harvard University

Biography

Ilenna Jones is a Research fellow at the Kempner Institute for the Study of Natural and Artificial Intelligence at Harvard. Her research interests include neuronal biophysics and computation, model optimization, and neuroscience for AI. She received her B.A. in Neuroscience in 2015 from Dartmouth College. In 2023 she received her PhD in Neuroscience at the University of Pennsylvania in Konrad Kording’s laboratory. Ilenna began her position as a Research Fellow in the Kempner Institute in 2023.

Interests

Neuronal and Dendritic Computation
Neuron Model Optimization
Neuro-inspired AI

Education

PhD in Neuroscience, 2023
University of Pennsylvania
BA in Neuroscience, 2015
Dartmouth College

Recent Posts

Fellowships and Candidacy: Growing from the Challenge

I learned that I was awarded the 2020 Howard Hughes Medical Institute (HHMI) Gilliam Graduate Fellowship grant. News of the award both revived and resolved some complex emotions.

Ilenna Jones

Jun 18, 2020 17 min read Advice

Fellowships and Candidacy: Growing from the Challenge

A Leap of Faith: Switching to computation from a wet-lab background

Here is the story of my 1st year in grad school training to get a PhD - my path toward understanding machine learning from scratch and what I considered as I was choosing a lab.

Ilenna Jones

Nov 5, 2019 11 min read Advice

A Leap of Faith: Switching to computation from a wet-lab background

Featured Publications

Ilenna Jones, Konrad Kording

May, 2022 Neuroscience

Do Biological Constraints Impair Dendritic Computation?

It is unclear if biological qualities, or constraints, impact a learning and computing neuron model positively, negatively, or at all. We simulate models with and without these constraints. We find models with a combination of biological constraints can outperform models with isolated introduced constraints. Qualitative dendritic properties may contribute inductive biases to neuron models that learn and compute.