Mo Shakiba · NeuroAI researcher

Mo Shakiba


I didn’t start in code. I started in the wet lab, but the more I understood the components, the more I became obsessed with the computation.

Exploring…

  • How much of biological learning is already encoded in cortical wiring?
  • Can cortical circuit design improve artificial intelligence?

Timeline

2018 — 2021

System Initialization

Completed high school majoring in Natural Sciences. Cultivated early algorithmic logic by learning Python and building an Arduino-based automation system.

DiplomaProgrammingNODET
2021 — 2023

Parallel Compilation

Entered Ferdowsi University of Mashhad as a Cell and Molecular Biology major. Built a parallel self-taught curriculum by completing Harvard University’s Computer Science courses and online data science bootcamps. Also, sharpened teaching and language skills as an English language teacher.

Data ScienceCS50Language Teaching
2023 — 2024

Feature Extraction

Joined Dr. Fatemeh B. Rassouli’s cancer research lab, introducing machine learning and mixed-effects workflows to analyze anticancer compound efficacy, yielding two peer-reviewed publications ‹a, b›. Also, deepened mathematical foundations by completing graduate-level machine learning courses at Sharif University of Technology.

a. Joining up the scattered anticancer knowledge…
b. Illuminating new possibilities: Effects of copper oxide…

BioinformaticsMathematicsMachine Learning
2024 — 2026

Manifolds & Cortical RNNs

Discovered the convergence of code and biology through Neuromatch Academy, quickly transitioning from student to teaching assistant. Initiated a two-year research collaboration with MIT N3HUB under Dr. Nima Dehghani. Mapped low-dimensional neural sleep state manifolds using CEBRA and utilized MICrONS connectomics data to build anatomically and functionally constrained bio-inspired RNNs, presenting abstracts at major conferences ‹c, d› and co-authoring a preprint on arXiv ‹e›. Also, graduated top of the class with a direct MSc offer. Admitted to Tarbiat Modares University’s Biophysics program.

c. 34th Annual Computational Neuroscience Meeting…
d. Anatomically and Functionally Constrained…
e. Harnessing cortical geometry, wiring, and function…

Computational NeuroscienceSpatially Embedded RNNBachelor of Science
2026 — Present

Continual Learning

Started MSc research at the Université de Montréal. Bridging functional connectomics and AI within the Systems Neuroscience and AI Lab under the supervision of Dr. Shahab Bakhtiari. Studying continual learning in neuromorphic architectures.

mila.quebecSNAIL LabNeuroAI