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Sajjad Abdoli

Ph.D. Machine Learning Scientist

Ubenwa health

Biography

Hi! My name is Sajjad Abdoli. I am a machine learning scientist at Ubenwa health. We are a startup company based in Mila - Quebec AI Institute at Montreal focusing on using the machine learning tools to discover neurological insights and physical needs solely from baby cry sound analysis. I finished my PhD in machine learning in 2021 at École de technologie supérieure, Montreal, Canada. I am interested in various machine learning projects including but not limited to audio/speech processing, visual object recognition and localization, domain adaptation, and also machine learning security and safety.

Beyond my research, I like running, hiking and photography!

Interests

  • Audio and Speech Processing
  • Music Information Retrieval
  • Adversarial Machine Learning
  • Object localization and classification
  • Domain Adaptation

Education

  • PhD in Artificial Intelligence, 2017 - 2021

    École de technologie supérieure, Université du Québec

  • MEng in Computer Engineering, 2017

    Azad University, Qazvin Branch

  • BSc in Computer Engineering, 2013

    Azad University, Central Tehran Branch

Publications

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End-to-end environmental sound classification using a 1D convolutional neural network

We present an end-to-end approach for environmental sound classification based on a 1D Convolution Neural Network (CNN) that learns a …

Universal Adversarial Audio Perturbations

We demonstrate the existence of universal adversarial perturbations, which can fool a family of audio classification architectures, for …

Iranian Traditional Music Dastgah Classification

In this study, a system for Iranian traditional music Dastgah classification is presented.

Talks

Speaker Detection in adverse scenarios with single microphone Project

Closing ceremony final presentation at JSALT 2019 workshop.