Alborz Rezazadeh, Ph.D.

Leader in Applied Machine Learning and A with 11 years of research and product experience | 8 years of experience in Healthcare, Drug Discovery and Biotechnology | Author of over 20 peer-reviewed papers and patents with over 500 citations and an h-index of 10.

Research Expertise

Brain-computer Interfaces
Artificial Intelligence
Machine Learning
Computer Vision
Electrical and Electronic Engineering
Computational Mathematics
Acoustics and Ultrasonics
Computer Networks and Communications
Biomedical Engineering
Cellular and Molecular Neuroscience
Behavioral Neuroscience
Human-Computer Interaction
Psychiatry and Mental health
Neuropsychology and Physiological Psychology
Neurology
Biological Psychiatry

About

Alborz Rezazadeh is a distinguished leader in the fields of AI, machine learning (ML), and computer vision (CV). In his current role as the Director of Applied CV at Recursion, a biotechnology company dedicated to revolutionizing drug discovery through AI, he has developed the applied CV/ML department, overseeing a team of over 10 ML scientists and engineers. Under his visionary leadership, the team has achieved remarkable success in foundational CV models, video analysis, multimodal learning, and the integration of large language models to expedite drug discovery processes. Alborz's leadership has fostered innovation and cost savings in the biotechnology sector. Before joining Recursion, Alborz spent two years as the Team Lead and Staff AI Scientist at LG AI Research Lab, where he led a team of eight ML scientists and engineers, successfully delivering projects in object detection, image classification, real-time pose estimation, and few-shot learning for various applications and LG products. Prior to his time at LG, Alborz contributed to pioneering deep-learning research for smartphones and appliances during his two-year tenure at Samsung AI Research Center. He also published multiple papers in prestigious AI conferences. Before entering the world of AI and ML, from 2012 to 2014, Alborz served as an Electrical Engineer at North Inc, where he was one of the initial two employees and played a pivotal role in the company's transformation into a unicorn startup. Alborz holds a PhD in Biomedical Eng. from the University of Toronto (2014-2018), where he developed groundbreaking brain-computer interfaces. His research earned him the "Best PhD Thesis" award from the University. He obtained his master's degree in Electrical Eng. (EE) from the University of Waterloo (2010-2012) and his B.Sc. degree in EE from Sharif University. Throughout his career, Alborz has demonstrated a passion for technology, visionary leadership, and a commitment to pushing the boundaries of AI.

Legacy Map

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Publications

EEG Classification of Covert Speech Using Regularized Neural Networks
IEEE/ACM Transactions on Audio, Speech, and Language Processing
2017
Online EEG Classification of Covert Speech for Brain–Computer Interfacing
International Journal of Neural Systems
2017
Online classification of imagined speech using functional near-infrared spectroscopy signals
Journal of Neural Engineering
2018
Development of a ternary hybrid fNIRS-EEG brain–computer interface based on imagined speech
Brain-Computer Interfaces
2019
VASTA
Proceedings of the 25th International Conference on Intelligent User Interfaces
2020
Exploiting error-related potentials in cognitive task based BCI
Biomedical Physics & Engineering Express
2018
Development of a robust asynchronous brain-switch using ErrP-based error correction
Journal of Neural Engineering
2019
RxRx1: A Dataset for Evaluating Experimental Batch Correction Methods
2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
2023
Online detection of error-related potentials in multi-class cognitive task-based BCIs
Brain-Computer Interfaces
2019
A pipeline of spatio-temporal filtering for predicting the laterality of self-initiated fine movements from single trial readiness potentials
Journal of Neural Engineering
2016
DATNet: Dense Auxiliary Tasks for Object Detection
2020 IEEE Winter Conference on Applications of Computer Vision (WACV)
2020
A Ternary Brain-Computer Interface Based on Single-Trial Readiness Potentials of Self-initiated Fine Movements: A Diversified Classification Scheme
Frontiers in Human Neuroscience
2017
A novel concept for post-fabrication tuning of microwave filters
2013 IEEE MTT-S International Microwave Symposium Digest (MTT)
2013
Isolated Persian digit recognition using a hybrid HMM-SVM
2008 International Symposium on Intelligent Signal Processing and Communications Systems
2009

Education

University of Toronto

Ph.D., Biomedical Engineering / August, 2018

Toronto, Ontario, Canada

University of Waterloo

M.Sc., Electrical and Computer Engineering / October, 2012

Waterloo, Ontario, Canada

Sharif University of Technology

B.Sc., Electrical Engineering / July, 2009

Tehran

Experience

Amazon

Senior Applied Scientist (L6) / January, 2024Present

Recursion

Director of Applied Machine Learning / January, 2022October, 2023

Drug Discovery, Biotechnology, Machine Learning, Deep Learning

LG

Team Lead - Staff AI Research Scientist / January, 2020January, 2022

AI, Machine Learning, Home Appliances

Samsung

AI Research Scientist / July, 2018January, 2020

AI, Machine Learning, Home Appliances, Mobile Devices

Bloorview Research Institute

Graduate Research Assistant / May, 2014July, 2018

Brain-computer interfaces, AI, ML, Rehabilitation, Biomedical Engineering

Thalmic Labs (North Inc)

Electrical Engineer / November, 2012May, 2014

Signal Processing, Electronics, Circuits

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