About me

Research scientist experience in Machine Learning. Experienced in converting intriguing high level questions into full fledged Machine Learning solutions. Working with different stakeholders to understand requirements, design solutions, hands-on and deliver production code. Experienced managing and delivering high quality software solutions for ML. Experience in cloud computing for ML (Dockers, Kubelfow .. etc.).

I like statistics and I build data pipelines to analyze data and train models.

News

  • 09/2023: Successfully defended my PhD dissertation!
  • 08/2023: New paper published in the Journal IEEE Access (IF: 3.476) [PDF] [LINK]
  • 12/2022: Joined Best Buy as a Senior Machine Learning Scientist!
  • 12/2022: New paper published in the Journal IEEE Access (IF: 3.476) [PDF] [LINK]
  • 07/2022: Final version of our IEEE Transactions of Power Systems paper is out (IF: 7.326) [PDF] [LINK]
  • 01/2022: Last Day at IKEA USA!
  • 12/2021: We Moved to Seattle !!
  • 08/2020: Started Working at IKEA USA as a Data Scientist
  • 07/2020: Last day at Kulicke and Soffa! Thank you for a great 5 years.

Resume

Education

  1. Temple University, Philadephia, PA

    PhD 2018 — 2023

    Dissertation: "Learning from Multi-modal Spatiotemporal Data: Machine Learning Applications to Advance Resilience in Smart Grids".

  2. State University of New York at Binghamton

    Msc 2013 — 2015

    Thesis: "A Scalabe Hybrid Model for Health Care Insurance Fraud Detection Using Association Rules And Random Forest"

  3. Jordan University of Sciece and Technology

    Bsc 2007 — 2012

    Senior project: “Arabic Voice Control System for Mozilla Firefox”

Experience

  1. Senior Machine Learning Scientist

    Best Buy, Seattle, WA

    12/2022 — Now
    1. Leading Projects in the language models for enhancing the digital customer experience.

    2. Projects: customer review topic extraction and summarization. Replace a 3rd party solution. Question generation and answering through retrieval augmented generation (RAG).

    3. - Leading a project topic extraction and review summarization using in-house tools and models.

      - Leading and hands-on research for topic extraction including POC while utilizing transformers/LMs

      - Designing production batch-processes using GCP. Delivering code repositories with CI/CD

      - Leading software design, development and review

      - Working on solutions for question generation and answering through retrieval augmented generation (RAG) and LLMs.

    4. Technologies: RAG, GCP, VertixAI, BigQuery, Python, Torch, Transformers, BERTopic and other

  2. Data Scientist

    IKEA Digital, Conshohocken, PA

    08/2020 — 01/2022
    1. Delivered projects: forecasting engine (to steer deployments and promotions), basket analysis (product pricing), causality analysis (understand the impact of digital deployments.

    2. End-to-end Data Science:

      - Led a team of 8 people in the design/development of projects (forecasting, basket analysis)

      - Help drive the business in a data-driven fashion and understand the causality of events

      - Working with product and domain leads to define business-critical problems and design solutions o Maintain high-quality code and lead code and design reviews

      - Led the design and implementation of infrastructure solutions (MLOps, Data as a Product-DaaP)

    3. Leadership: building relationships with global stakeholders, tertial planning, technical leading, product ownership, and data science advocacy. Onboarded new team members and held training including product design, documentation, source control, product planning, and execution

    4. Technologies: Python (NumPy, Scikit-Learn, Keras ...), Google Cloud, Dockers, Kubernetes, Kubeflow, BigQuery, Google Analytics, Git, Cloud Functions, Google Data Studio, R

  3. Data Scientist

    Kulicke and Soffa, Fort Washington, PA

    08/2018 — 08/2020
    1. Delivered projects: online semi-supervised outlier detection for manufacturing robotics

    2. End-to-end Data Science: R&D for ML outlier detection for robotics' timeseries data (POC to production)

      - Interact with stakeholders and leadership to collect requirements and communicate results

      - Design and developed real-time novel outlier detection and classification models

      - Handle high-frequency and high-dimensional robotics sensor data

      - Handle model development including POC, implementation (C++/Py/C/Cython) and CICD

    3. Tools Design: design and implement data pipelines and custom ETL for robotics data. Design custom data visualization tools for analyzing ML results-offline

    4. Technologies: Python, C++, Keras, Tensorflow, Pandas, NumPy, SciPy, Matplotlib/Seaborn/Bokeh

  4. Software Engineer

    Kulicke and Soffa, Fort Washington, PA

    07/2015 — 07/2018
    1. Delivered projects: data pipelines for high throughput data, a platform to monitor and analyze robotics, distributed data storage, real-time analytics

    2. Embedded Robotics Data Visualizations

      - Implemented low-level data pipelines for robotics using C++, Python, and NodeJS

      - Implemented customized data visualizations through open-source libraries such as Highcharts using JavaScript and jQuery

      - Implemented a server-client architecture using NodeJS to analyze and visualize real-time and offline data on multi-platforms (Windows, Linux, VxWorks)

    3. Data Analytics: Designed and implemented a python real-time analytics engine for real-time data insights

    4. Data Storage: Designed and implemented NoSQL storage to store real-time streaming data

  5. Software Engineer (Intern)

    iA, Johnson City, NY

    01/2014 — 05/2015

    Design and develop software migration automation tools (C#) for legacy code. Object-oriented redesign.

  6. Research Assistant

    Binghamton University, Vestal, NY

    08/2013 — 12/2013

    Research in analytics techniques, and data mining

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