Saad Bayezeed

Saad Bayezeed

About

Detail

Head of Revenue Operations & Enablement at Easygenerator (We are hiring!)
Dubai, United Arab Emirates

Timeline


work
Job
school
Education
auto_stories
Publication

Résumé


Jobs verified_user 0% verified
  • RevOps Coop
    Member
    RevOps Coop
    Apr 2022 - Current (4 years 7 months)
  • Easygenerator
    Head of Revenue Operations & Enablement
    Easygenerator
    Nov 2021 - Current (5 years)
  • RevOps
    Revenue Operations & Enablement - Strategic Consultant
    RevOps
    May 2020 - Oct 2021 (1 year 6 months)
    Highlights:

    - Channel Framework Development Project
    Foodics - August 2021 - October 2021

    - Regional Sales Foundation & Expansion Project
    Lyve Global - May 2020 - July 2021
  • F
    External Advisor
    FUNDENIC SOS
    May 2020 - Current (6 years 6 months)
  • R
    Sales Operations & Enablement Manager
    Repeat App
    May 2019 - Apr 2020 (1 year)
  • Foodics
    Business Development Manager - EU & APAC
    Foodics
    May 2018 - Apr 2019 (1 year)
  • S
    Senior Account Executive
    Sapaad Pte Ltd
    May 2017 - Apr 2018 (1 year)
  • S
    Account Executive
    Sapaad Pte Ltd
    May 2016 - Apr 2017 (1 year)
  • Sutherland
    Senior Business Development Representative
    Sutherland
    Nov 2015 - Apr 2016 (6 months)
  • Sutherland
    Business Development Representative
    Sutherland
    Aug 2014 - Oct 2015 (1 year 3 months)
Education verified_user 0% verified
  • Birla Institute of Technology and Science Pilani
    Bachelor’s Degree, Computer Engineering
    Birla Institute of Technology and Science Pilani
Awards verified_user 0% verified
  • Microsoft
    Microsoft Student Partner - Lead
    Microsoft
    Managed Entire MSP Program, Organized and attended several conferences for Microsoft in the education sector.
  • Microsoft
    Imagine Cup Top 5 Finalists
    Microsoft
Publications verified_user 0% verified
  • W
    Secure Fingerprint Authentication Using Deep Learning and Minutiae Verification
    Walter de Gruyter GmbH BerlinBoston Journal of Intelligent Systems
    Mar 2019
    Nowadays, there has been an increase in security concerns regarding fingerprint biometrics. This problem arises due to technological advancements in bypassing and hacking methodologies. This has sparked the need for a more secure platform for identification. In this paper, we have used a deep Convolutional Neural Network as a pre-verification filter to filter out bad or malicious fingerprints. As deep learning allows the system to be more accurate at detecting and reducing false identification by training itself again and again with test samples, the proposed method improves the security and accuracy by multiple folds. The implementation of a novel secure fingerprint verification platform that takes the optical image of a fingerprint as inp
This is a community-created genome.