About me

I'm a PhD candidate at the Max Planck Institute for Neurobiology of Behavior working with Marcel Oberlaender. Currently, I'm investigating to what degree are cellular properties of GABAergic interneurons informative of their in vivo activity function.

Originally trained as an Electrical Engineer, I then specialized in Machine Learning, and worked for 3 years in software engineering. During my undergrad studies I constructed an electric vehicle, and did internships at The ABB Group, MIT, and Inria Paris-Saclay.

CV Publications Communication Email

What are the organizing principles of cortical interneurons?

My approach to cast this question is as follows:

  1. Dataset creation. I standardized and curated a large representative sample of cortical interneurons.

  2. Robust classification. I assigned neurons into highly accurate classes (i.e., cell types) based on a rich multi-modal characterization of each cell.

  3. Flexible model development. I designed a generative self-supervised model to learn the statistics of a representative dataset across the entire cortical depth of the somatosensory cortex.

This methodology allows the identification of depth-dependent relationships between phenotypic properties, and can be readily applied to downstream tasks such as multi-modal in vivo predictions and cross-species analysis of cell types.

Publications

Large language models surpass human experts in predicting neuroscience results
Xiaoliang Luo*, Akilles Rechardt*, Guangzhi Sun*, Kevin K. Nejad*, Felipe Yáñez*, Bati Yilmaz*, ..., and Bradley C. Love*
arXiv 2024 [Hugging Face] [code] [website]
* indicates major contributions

Simulation-based inference for efficient identification of generative models in computational connectomics
Jan Boelts, Philipp Harth, Richard Gao, Daniel Udvary, Felipe Yáñez, Daniel Baum, Hans-Christian Hege, Marcel Oberlaender, and Jakob H. Macke
PLoS Comput. Biol. 2023 [bioRxiv] [code]

A hidden parameter network that explains topological properties observed in neocortex
Felipe Yáñez, Daniel Udvary, and Marcel Oberlaender
ICLR Generalization Workshop 2021 [poster]

Primal-Dual Algorithms for Non-negative Matrix Factorization with the Kullback-Leibler Divergence
Felipe Yáñez, and Francis Bach
IEEE ICASSP 2017 (oral presentation) [slides] [arXiv] [code]

Quantitative Susceptibility Map Reconstruction via a Total Generalized Variation regularization
Felipe Yáñez, Audrey Fan, Berkin Bilgic, Carlos Milovic, Elfar Adalsteinsson, and Pablo Irarrázaval
PRNI 2013

Teaching & outreach

  • Deep Learning Indaba

    As a mentor, I actively share my skills and experiences with early career researchers from the African AI community.

  • Wilbe Science

    As a BSF fellow, I bounce ideas, contribute to shared resources, and interact with a community of aspiring science entrepreneurs.

  • PUC Chile & Uni Frankfurt

    As a TA and lecturer, I deliver a wide range of courses including Machine Learning, Pattern Recognition, Computational Neuroscience, Imaging, MRI Laboratory, Fluid Mechanics, and Calculus.

    Sample materials of other courses:

    Differential Equations Signals & Systems Linear Algebra

  • Volta UC

    As an electrical engineering undergrad, I helped developing a 60kW electric vehicle and producing the first technological documentary made in Chile.


Selected presentations & talks

Hopkins and DC

I headed to Johns Hopkins University to give a talk on the organizing principles of cortical interneurons. Then, I presented the conclusion of my PhD project at Neuroscience 2023.


Details

Rehacking time in Granada

After learning about NWB and the DANDI Archive, I reanalyzed published data to explore how my proposed principles of cortical interneurons operate across different species and cortex areas. I'm thankful to The Kavli Foundation for funding my travel and accommodation.


Hacking neuro data!

I attended the NWB users and developers meeting in July 2023. It was an incredible experience where I had the chance to work on the standarization of intracellular electrophysiology and start getting involved in the integration of LLMs that assist in the identification of dandisets relevant to a scientific question. I'm thankful to Janelia for covering all the costs of my visit including flight.



Neuroscience in sunny San Diego

In November 2022, I gave a talk about robust cell type prediction of in vivo cortical interneurons at the XXXV Barrels meeting. Then, at Neuroscience 2022, I presented my core project on organizing principles of cortical interneurons, i.e., highly accurate classification of a large representative sample of cortical interneurons, followed by applications to multi-modal in vivo predictions and cross-species analysis of cell types.


Details

Back to Paris

After a long while I had the chance to meet with old friends, colleagues, and mentors at the FENS Forum 2022 in Paris. I presented a procedure to robustly cluster a large representative sample of cortical interneurons. I also showed that my methodology can be readily applied to multi-modal in vivo predictions and cross-species analysis of cell types.


Details

Talk @EPFL

During the summer of 2022, I gave a talk at EPFL about organizing principles of cortical interneurons.



Interview with Mel Nuesch (in Spanish)

I was invited to talk about my research on the development of robust technologies to understand structural properties of the brain.



Virtual presentation


Northwestern + SfN

In October 2019, I traveled to Chicago to present my work on depth-specific relationships between phenotypic properties of cortical interneurons at Northwestern University and Neuroscience 2019.


Details

Let's get in touch!

If you think we should work together, discuss about research, or have an informal conversation, just drop me a line.