CV

Basics

Name Amgad Madkour
Label Data & Applied Science Manager at Microsoft AI
Url https://amgadmadkour.com
Summary My current work focuses on building large-scale data products that use various artificial intelligence techniques to deliver value to users.

Work

  • 2019.01 - Present

    Redmond, USA

    Data & Applied Science Manager
    Microsoft
    • Autos Marketplace: Technical lead for Automotive Q&A, My Garage, Autos Listings, and Autos AI features that deliver differentiating content to automotive users.
    • Platform for Interactive Concept Learning: Maintained and enhanced the model used by Microsoft Edge for extracting product information form e-Commerce domains.
    • Entity Matching: Enhanced the performance of the entity matching stack by addressing the highly skewed data issues, delta entity matching, and optimizing the blocking technique.
  • 2018.05 - 2018.08

    Redmond, USA

    Data Scientist Intern
    Microsoft
    • Conflation Updates: Designed and implemented a conflation update component that is responsible for speeding up the reflection of conflation changes into the Satori final graph.
  • 2015.05 - 2015.08

    Redmond, USA

    Research Intern
    Microsoft Research
    • Dependency parsing: Conducted a series of experiments ranging from Up-training to Entity Linking to improve the dependency parsing accuracy.
  • 2011.05 - 2011.08

    Sunnyvale, USA

    Research Intern
    Yahoo!
    • Recommendation system: Developed a recommendation system for local businesses.
  • 2006.01 - 2010.07

    Cairo, Egypt

    Research Engineer
    IBM
    • Tag Recommendation Technique: Co-Invented and patented a k-partite graph technique for recommendation of tags during bookmarking of resources.
    • Spam Detection: Proposed a set of features that identify spamming bookmarks in social media and evaluated their feasibility over various machine learning algorithms.
    • Extracting relations from biomedical text: Developed a system that automatically extracts interactions between entities such as proteins, chemicals, and diseases from biomedical text with preliminary focus on protein-protein interactions.
    • Machine Assisted Translation: Developed a system that provides suggestions when translating documents. The system uses a continuous space language models for statistical machine translation.
    • Unstructured Information Management Platform: Participated in a joint development with Watson lab in Yorktown to develop a system that analyzes large volumes of unstructured textual information from the news domain to discover, organize, and deliver relevant knowledge to end-users.

Volunteer

  • 2014.04 - 2015.07

    Cairo, Egypt

    Volunteer
    Egypt Scholars
    Developing software for the visually impaired

Education

Awards

Languages

Arabic
Native speaker
English
Fluent