Reza Ebrahimi is an AI Researcher at Qualcomm and a PhD candidate at the University of Toronto. His expertise is in machine learning, probabilistic modeling, and generative models, with a focus on applications in compression and out-of-distribution detection. He earned his Master of Science from the University of Tehran.
His past research at CAMH involved applying machine learning to fMRI data to better understand the neural pathophysiology of Schizophrenia Spectrum Disorders.
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Experience
11 Years
Current Role
AI Researcher
Location
Toronto, Ontario, Canada
Personality Overview
How Reza shows up
Precise
ROI Driven
Objective Thinker
They don’t appreciate bells and whistles unless backed by data. They enjoy working alone and do not rely on others very often. They prefer to do logical analysis and value evidence over emotions.
Priorities
Topics Reza cares about
Generative Models
His PhD research and special interests focus on generative models and their applications in data compression and out-of-distribution detection.
Large Language Models
He has researched length generalization in LLMs at Qualcomm's Neural Reasoning Team and published papers on the limitations of transformers.
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Career
Work history
8-2024
AI Researcher
Qualcomm
9-2018 - 8-2024
PhD Candidate
University of Toronto
6-2023 - 10-2023
AI Research Intern
Qualcomm
9-2016 - 9-2018
Senior Research And Development Engineer
Sarveen Technologies Inc.
9-2013 - 9-2016
Research Assistance
Wireless Multimedia Communication Lab
In the press
Media appearances
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Calculativeness (C) reflects the degree to which a person is likely to be cautious, systematic and analytical. Those scoring high tend to emphasise quality and accuracy.
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