Bahareh Tolooshams

Area of Study / Keywords

Artificial Intelligence Machine Learning Representation Learning Generative Models Interpretability Inverse Problems NeuroAI Signal Processing Software Engineering and Intelligent Systems

About

I am the PI of NeuBahar Lab (Neuro–Bayesian AI for Human-interpretable Abstractions and Representation Learning).

We are hiring. Check out the lab's website.

Education

- PhD, Electrical Engineering Engineering Sciences, Harvard University, 2023

- BASc, Electrical Engineering, University of Waterloo, 2017

Past employment (since 2019)

- Postdoc, California Institute of Technology (Caltech), 2023 - 2025

- Research Intern, Microsoft, 2021

- Applied Scientist Intern, Amazon AI - AWS, 2019

How to pronounce my name? (Check here)

Research

Check out the lab website https://sites.ualberta.ca/~toloosha

My research group is recruiting MSc and PhD students for Fall 2026.

ECE 447 - Data Analysis and Machine Learning for Engineers

The course introduces basic concepts and techniques of data analysis and machine learning. Topics include: data preprocessing techniques, decision trees, nearest neighbor algorithms, linear and logistic regressions, clustering, dimensionality reduction, model evaluation, deployment methods, and emerging topics. Prerequisites: ECE 220 or CMPUT 275, and ECE 342 or STAT 235, or consent of instructor.

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