Pooyan Abouzar, Ph.D.

Principal ML Engineer at Sway AI
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Contact Information
us****@****om
(386) 825-5501
Location
San Francisco, California, United States, US

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Bio

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Credentials

  • Natural Language Processing
    DeepLearning.AI
    Feb, 2023
    - Nov, 2024

Experience

    • United States
    • Software Development
    • 1 - 100 Employee
    • Principal ML Engineer
      • Sep 2023 - Present

    • United States
    • Biotechnology Research
    • 200 - 300 Employee
    • Data Scientist/Senior Software Engineer
      • Feb 2020 - Feb 2023

    • United States
    • IT Services and IT Consulting
    • Senior Software ML Engineer
      • Apr 2019 - Feb 2020

      ImpactVision is a machine learning company, applying hyperspectral imaging technology to food supply chains to deliver consistent food quality, generate premium products and reduce supply chain waste. ImpactVision is a machine learning company, applying hyperspectral imaging technology to food supply chains to deliver consistent food quality, generate premium products and reduce supply chain waste.

  • Medical Cytometrix Inc.
    • Vancouver, Canada Area
    • Software ML Engineer
      • Apr 2017 - Apr 2019

      I used C++, OpenCV, machine learning, and tensorflow to develop tools which could help hematologists achieve more efficiency in blood smear image analysis. I used C++, OpenCV, machine learning, and tensorflow to develop tools which could help hematologists achieve more efficiency in blood smear image analysis.

    • Canada
    • Research Services
    • 200 - 300 Employee
    • Consultant
      • Feb 2017 - Apr 2017

      Proposed wireless communication solutions for forest operational data acquisition Proposed wireless communication solutions for forest operational data acquisition

    • Canada
    • Higher Education
    • 700 & Above Employee
    • Research Assistant
      • Jun 2010 - Aug 2016

      My Ph.D. was focused on algorithm and deployment guideline design for communications in wireless sensor networks. The proposed routing, scheduling, localization and node placement techniques take channel propagation and path loss into account in order to decrease power consumption of higher communication layers. The algorithm design involves mathematical modelling of higher communication layer problems and devising solutions, which encompass signal processing and machine learning techniques… Show more My Ph.D. was focused on algorithm and deployment guideline design for communications in wireless sensor networks. The proposed routing, scheduling, localization and node placement techniques take channel propagation and path loss into account in order to decrease power consumption of higher communication layers. The algorithm design involves mathematical modelling of higher communication layer problems and devising solutions, which encompass signal processing and machine learning techniques such as Bayesian estimation, naive Bayes classifiers, etc. The solutions will lead to improvement of IEEE 802.15.6 and IEEE 802.15.4 specifications for two particular applications of study; wireless body area networks and precision agriculture. Show less My Ph.D. was focused on algorithm and deployment guideline design for communications in wireless sensor networks. The proposed routing, scheduling, localization and node placement techniques take channel propagation and path loss into account in order to decrease power consumption of higher communication layers. The algorithm design involves mathematical modelling of higher communication layer problems and devising solutions, which encompass signal processing and machine learning techniques… Show more My Ph.D. was focused on algorithm and deployment guideline design for communications in wireless sensor networks. The proposed routing, scheduling, localization and node placement techniques take channel propagation and path loss into account in order to decrease power consumption of higher communication layers. The algorithm design involves mathematical modelling of higher communication layer problems and devising solutions, which encompass signal processing and machine learning techniques such as Bayesian estimation, naive Bayes classifiers, etc. The solutions will lead to improvement of IEEE 802.15.6 and IEEE 802.15.4 specifications for two particular applications of study; wireless body area networks and precision agriculture. Show less

    • Wireless Sensor Networks Consultant
      • May 2012 - Sep 2014

      - Provided technical advice regarding deployment and communication algorithm design for wireless sensor networks in the farms (SemiosBio) SemiosBio is a pioneer in pheromone based pest control solutions. They have deployed wireless sensor networks across thousands of acres of farms in many countries. http://www.semiosbio.com/home

    • RF Data Acquisition Team Lead
      • Jun 2012 - Sep 2013

      - Conducted Precision Agriculture project for three RF data acquisition campaigns in Okanagan, BC - Provided mentorship for summer students at Radio Science Lab for RF data acquisition in orchards - Developed mathematical path loss model for industrial, scientific and medical (ISM) radio bands

    • Cellular Network Site Consultant
      • Apr 2012 - Jun 2012

      - Practiced consulting for cell towers in Langley, BC (Rhombic consulting group) Rhombic is a Canadian-based consultant for public and private Landowners/Strata councils and building managers providing guidance on cell site and wireless communication related issues. http://www.rhombic.ca/

    • Switzerland
    • Higher Education
    • 700 & Above Employee
    • exchange student
      • 2007 - 2008

Education

  • The University of British Columbia / UBC
    Doctor of Philosophy (Ph.D.), Electrical, Electronics and Communications Engineering
    2010 - 2016
  • Chalmers University of Technology
    Master of Science (M.Sc.), Telecommunications Engineering
    2006 - 2008
  • University of Tehran
    Bachelor of Science (B.Sc.), Electrical, Electronics and Communications Engineering
    2001 - 2006

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