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Maria Zafar

Deep Learning Engineer at SensViz & Upwork | Machine Learning | Graduate Teaching Assistant at Institute of Business Administration

Basic Info
  • Career Track: NA
  • Public Username: maria-zafar
  • LinkedIn: View
About

I’m interested in leveraging Deep Learning capability for applications in Computer Vision and Natural Language Processing. In my graduate program and later in professional experience, with a focus on applications in Machine Learning, I explored ML and DL tasks such as product development using deep learning and chatbot development, attribute based classification and question answering, as well as the use of semi-supervised learning to generate robust representations. Having experienced both research and development, I find the process of identifying problems of interest, curating solutions by rethinking traditional models and engineering them into systems as a uniquely wonderful experience. I have a fascination with cross-disciplinary sciences and love weaving different domains together to generate something more transformative. Competencies: Machine learning, Deep Learning, NLP.

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  • Go-Getter

Experiences

  • Senior Python Developer

    01 Jun 2022 - 01 Oct 2022 4 Months

    Devaj Technology

  • Machine Learning Engineer

    01 Apr 2022 - Currently Working 2 Years

    Upwork

  • Deep Learning Engineer

    01 Sep 2021 - Currently Working 3 Years

    SensViz

  • Digital Analyst Trainee

    01 Sep 2021 - 01 Feb 2022 5 Months

    MarketLytics

  • Graduate Teaching Assistant

    01 Sep 2021 - 01 Dec 2021 3 Months

    Institute of Business Administration

Education

  • Master's degree(MS) - Others

    January, 2019 - June, 2021

    Institute of Business Administration

  • Bachelor of Science (B.Sc.(Hons)) - Others

    January, 2009 - June, 2013

    Kinnaird College for Women

  • A level - Others

    January, 2006 - June, 2008

    Beaconhouse School System

Publications

  • Developing Smart Conversation Agent ECOM-BOT for Ecommerce Applications using Deep Learning and Pattern Matching

    Research Area: -

  • CBSF: A Framework for Accurate Simulation of Appliance Data for Future Smart Grid Applications

    Research Area: -

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