Experience

  • September 2023 - Present
    Graduate Research Assistant
    University of Calgary - Calgary, Alberta - Canada
  • July 2023 - present
    Teaching Assistant-Data Science
    Correlation-One - Amman, Jordan · Remote
    • - Participating in all live lectures, providing helpful and fast responses via Slack, prepared to host breakout rooms as needed.
    • - Providing 6 hours of individual office hour sessions for Fellows each week.
    • - Hosting review sessions or other support mechanisms to ensure the progress and satisfaction of Fellows.
    • - Participating in the weekly TA meeting
    • - Submitting weekly write-ups summarizing the week’s accomplishments and challenges
    • - Taking attendance during office hours on the TA portal
    • - Grading Fellows’ submissions, providing feedback and ongoing learning support
  • February 2023 - August 2023
    Backend Engineer - Python
    ITG Software Engineering - Cincinnati, Ohio, United States · Remote
    • worked in creating a new site for Kiboko which is a subscription-based service that allows
      organizations and companies to collect and analyze their data from Google Analytics using BigQuery APIs.
  • Oct 2022 - April 2023
    SWE Intern
    Manara - United States , US
    • Selected from amongst 12000 applicants as one of only 200 participants in the program
    • Study under the supervision of world-class instructors from companies such as Google, Meta, Amazon
    • Study problem-solving, soft skills and technical skills with intensive program for 7 months
    • Do job interviews with Google, noon ,RelationalAI,Meta, but I decided to Go and follow my Dream in the Higher Education
    • Manara takes top 1% Engineering and CS students in the Middle East and Make Referrals to them in the High-Tech
  • Jan 2022 - Feb 2023
    AI/ML and Data Science Engineering Intern
    Harri - New York and Ramallah
    • Serving the backend team for Harri, a global leader in frontline employee experience, worked on time series and forecasting projects to predict hiring needs for restaurants and retailers
    • and forecasting projects to predict hiring needs for restaurants and retailers ● Coordinated with data team to create a pipeline for client data, using time series forecasting algorithms; built backend system with Django; created bridge between backend and data science team
    • Worked in R&D of new and customized algorithms and backend solutions to create an employee forecasting product used by 20 clients, which reached hourly prediction intervals; included embedded features for employer clients such as location, type of business, and original data from the last 10 years
    • Reference: Rami Tailakh
  • Sep 2022 - Jan 2023
    Undergraduate Researcher
    Equitech Futures- Chicago, Illinois
    • Applied machine learning techniques to real-world datasets such as predictive algorithms for climate forecasting and wind speed prediction, and gained experience in applied artificial intelligence
    • Developed proficiency in Python through participation in Coding Gym sessions
    • Conducted independent research and team projects; presented climate forecasting research findings and wrote reports, effectively communicating technical information to a diverse audience
    • Collaborated with peers and mentors to design experiments and analyzed and validated results for weather datasets, through Kaggle and other lab results

    • References :

  • Oct 2021 - May 2022
    Undergraduate Researcher
    Future Computing Technologies Lab, Clemson University - South Carolina, USA
    • As part of the research team, worked on real-time emotion recognition using deep learning with Google Colab, Tensorflow, OpenCV, and Dlib to contribute to the success of this approach in recognizing emotions
    • Introduced deep learning techniques (CNN, DNN, and other multimodal methods), to accelerate recognition accuracy; demonstrated general architectural model for building a recognition system with deep learning
    • Aimed to analyze pre- and post-processes involved in the model's methodology; conducted extensive work on image and video as input (Real-Time System) to recognize the emotion
    • Benchmarked different performance parameters in different research to show this sphere's progress
    • Carried out the experimental observation on the Kaggle dataset involving seven emotions, which yielded 97% accuracy in the training set and 57.4% accuracy when applying the Haar cascade technique
    • References : Prof. Melissa Smith & Mikaila Gossman
  • May 2021-Oct 2021
    SWE intern
    Apple Inc - Ramallah, west bank - Palestine
    • As part of the backend development, supported a data stream interface project, building an internal employee system that managed inventories and labs, part of the company's critical supply chain process.
    • Implemented and iterated retrieve/update information using Django and React
    • Reference : Amin Mukhaimar