Open to AI, ML & data science roles

Ibraheem Taha

AI/ML Engineer & Data Scientist / PhD Candidate

Building production-ready AI infrastructure and ML systems, and using data science to turn complex data into models and insights for business impact. Backed by industry experience at Cadence, Orange Labs and OpenAIRE and PhD research in data engineering for data science.

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  • Aalborg, Denmark
Portrait of Ibraheem Taha, AI/ML Engineer, Data Scientist, and PhD Candidate
  • 80× Faster ML data pipeline
  • 18× Smaller vector indexes
  • 4 Research publications
  • 3× Erasmus Mundus scholar

Worked & studied at

  • Cadence Design Systems
  • Orange Labs
  • OpenAIRE
  • Aalborg University
  • Athena Research Center
  • Institut Polytechnique de Paris
  • Uppsala University

About me

Practical engineering and data science, backed by research depth.

I build production-ready AI, ML, and data science systems that turn complex data into business value.

I am an AI/ML Engineer and Marie Skłodowska-Curie PhD Fellow in Data Engineering for Data Science at Aalborg University and the University of Athens, with industry experience at Cadence Design Systems, Orange Labs, and OpenAIRE. My work spans the full ML lifecycle, from data pipelines and feature engineering to modeling, evaluation, and MLOps, across forecasting, NLP, retrieval, and signal processing.

I have cut ML data preprocessing from four hours to three minutes (80×), built 18× smaller vector indexes for table search, and authored four research publications, including a KDD 2026 workshop paper.

I also co-founded and taught at a technical academy, where I focused on making complex ideas accessible. I thrive in teams that value technical excellence, ownership, and continuous improvement.

Experience

Professional experience

Research and industry roles spanning data science, machine learning, data engineering, and production systems.

  1. Research Assistant, AI & Data Engineer

    Aalborg University · Part-time

    Current September 2026 - Present

    Building a Human Digital Twin platform, toward a future where every person has a digital twin that applications can connect to.

    • Own end-to-end design and development of a Human Digital Twin platform from scratch
    • Architect and build the platform's data layer, covering processing, storage, and management
    • Design a scalable integration architecture that connects applications to each person's digital twin
    • Human Digital Twins
    • Platform Architecture
    • Data Processing
    • Data Storage
    • Application Integration

  2. Researcher in Data Engineering for Data Science

    Aalborg University & Athena Research and Innovation Center

    Current February 2022 - Present

    PhD research focusing on enabling efficient and intelligent interactive data exploration and analytics in large-scale, heterogeneous data lakes.

    • Developed advanced indexing techniques for vector-based table representation learning
    • Optimized table discovery and search systems for data integration and augmentation
    • Contributed to design of expressive exploratory workflows and scalability improvements
    4 publications, including AIDEN at KDD 2026
    • Vector Indexing
    • Table Search
    • Data Lakes
    • Representation Learning
    • Agentic AI

  3. Data Engineer

    OpenAIRE AMKE

    February 2024 - May 2024

    Enriched the OpenAIRE knowledge graph by building a scalable scholarly metadata pipeline.

    • Built a configurable scraping platform covering both static and JavaScript-rendered publisher websites
    • Designed XPath and regex-based extractors that mapped affiliation metadata to publication IDs across dozens of heterogeneous sources
    • Piloted transformer-based NER for automated entity recognition, successfully linking affiliation data for the majority of target publishers
    • Web Scraping
    • XPath & Regex
    • Transformer NER
    • Knowledge Graphs

  4. Co-Founder and Instructor

    HiTechA Academy

    January 2017 - November 2021

    Created a learning environment and facilitated network and systems courses including Python, C++ and CCNA Routing and Switching.

    • Leadership
    • Teaching
    • Python
    • C++
    • CCNA

  5. Machine Learning Engineer

    Orange Labs

    March 2020 - September 2020

    Designed ML-based signal equalizers for long-haul fiber optic transmission at Orange Labs R&D.

    • Built RNN-based models to mitigate nonlinear distortion, improving Bit Error Rate (BER) across 1D and 4D signal configurations
    • Reduced data preprocessing time from 4 hours to 3 minutes (80×) through full pipeline redesign
    • Handled the complete data engineering lifecycle: collection, preparation, feature extraction, and model evaluation
    • RNNs
    • Deep Learning
    • Signal Processing
    • Pipeline Optimization

  6. Product Validation & Verification Engineer

    Cadence Design Systems

    December 2016 - August 2018

    Contributed to the Xcelium Parallel Simulator, one of the industry's leading EDA simulation tools.

    • Automated verification workflows using Python, Bash, and SystemVerilog, reducing manual regression effort across simulation targets
    • Validated functional correctness of design modules using industry-standard EDA toolchains
    • Consistently ranked among top-performing engineers across all performance evaluations
    • Python
    • Bash
    • SystemVerilog
    • EDA
    • Test Automation

Projects

Selected projects

Production-minded builds across AI platforms, MLOps, data engineering, forecasting, and NLP.

Enterprise AI · MLOps Platform Jan 2026 – Present

Enterprise AI Workflow Platform

Self-Initiated Project

16+ integrated services

  • Built a reproducible local AI platform with 16+ integrated services.
  • Unified data workflows, APIs, vector search, monitoring, and experiment tracking.
  • Designed for modular RAG, agent workflows, and production AI delivery.
  • AI Platforms
  • MLOps
  • Orchestration
  • RAG Systems
DataOps · Renewable ML Sep 2024 – Oct 2024

DataOps and MLOps: Wind Turbine Power Prediction

Aalborg University

15-minute & 1-hour forecasts

  • Built a forecasting pipeline for 15 minute and 1 hour prediction.
  • Automated end-to-end ML pipeline with low-latency inference and real-time model serving.
  • Monitored drift, model quality, and pipeline performance across the lifecycle.
  • DataOps
  • MLOps
  • Airflow
  • MLflow
Data Engineering · Open Science Feb 2024 – Apr 2024

Secondment (Internship) - Data Engineer at OpenAIRE

OpenAIRE AMKE

Knowledge graph enrichment

  • Built scraping pipelines for static and dynamic publisher websites.
  • Mapped affiliation records to publications across heterogeneous sources.
  • Contributed reusable tooling for knowledge graph enrichment workflows.
  • Data Eng
  • Scraping
  • Metadata
  • NLP
Machine Learning · High-Performance Data Pipelines Mar 2020 – Sep 2020

Machine Learning for Optical Signal Processing and Pipeline Optimization

Orange

80× faster: 4 hours → 3 minutes

  • Applied machine learning techniques to improve optical signal quality
  • Optimized data loading and preprocessing, cutting runtime by 80× from 4 hours to 3 minutes.
  • Improved model evaluation efficiency across large-scale 1D and 4D signal datasets.
  • Machine Learning
  • Python
  • Data Pipelines
  • Performance Optimization
NLP · Music Recommender Mar 2019 – Jun 2019

DionySongs - Content-Based Music Recommender for Song Analysis, Classification & YouTube Query System

National & Kapodistrian University of Athens

57k+ songs indexed

  • Built a lyrics-driven music recommender across 57k+ songs.
  • Scaled similarity search with MinHash LSH and parallel processing.
  • Delivered Android search, playback, and live song recommendations.
  • NLP
  • LSH
  • Android
  • MinHash
NLP · Big Data Analytics Nov 2018 – Feb 2019

Large-Scale Text Mining & Multi-Mode Classifier Design for Document Analysis (Big Data Analytics)

National & Kapodistrian University of Athens

96.77% accuracy · 35 h → 9.5 h runtime

  • Built a multiprocessing pipeline for large-scale text processing, cutting runtime from 35 to 9.5 hours.
  • Designed a scalable text classification pipeline for noisy documents.
  • Achieved 96.77% accuracy with tuned SVM and TF-IDF features.
  • NLP
  • SVM
  • TF-IDF
  • Word2Vec

Skills

Professional skills

The tools and practices I use to analyze data, build models, and take AI and data systems from prototype to production.

Machine Learning & AI

  • LLMs
  • RAG Pipelines
  • Deep Learning
  • Agentic AI Tools
  • LangChain
  • Statistical Learning
  • Feature Engineering & Model Evaluation
  • Time-Series Forecasting
  • NLP
  • Experiment Tracking (MLflow)

Data Engineering

  • ETL / ELT Pipelines
  • Data Lakes
  • Apache Spark
  • Data Modeling
  • dbt
  • PostgreSQL
  • NoSQL (Redis, MongoDB, Elasticsearch)
  • Workflow Orchestration (Airflow)
  • Hadoop Ecosystem

MLOps & Deployment

  • Docker
  • FastAPI
  • CI/CD Pipelines
  • Model Serving (API-based)
  • Streamlit
  • Cloud (AWS, GCP)

Programming & Core Foundations

  • Python
  • C / C++
  • Linux
  • SQL
  • Git

Certifications & Networking

  • CCNA
  • CCNP
  • Networking Fundamentals

Research

Research & publications

PhD research on efficient, intelligent exploration and analytics over large-scale, heterogeneous data lakes: table search, vector indexing, and agentic assistants.

  • Dual PhD: Aalborg University & University of Athens
  • Marie Skłodowska-Curie PhD Fellowship
  • 18× smaller vector indexes
  1. 2026Workshop

    AIDEN: An Agentic Intention-Driven Assistant for Exploration and Navigation of Data Lakes

    I. Taha

    In KDD 2026 Workshop SciSoc Agents & LLMs, KDD, 2026

  2. 2026Book chapter

    Table Search in Data Lakes: Methods, Indexing Techniques, and Research Challenges

    I. Taha, M. Lissandrini, A. Simitsis, T. B. Pedersen, Y. Ioannidis

    In Data Engineering for Data Science, Springer, 2026

  3. 2025Journal

    Comparative Analysis of Indexing Techniques for Table Search in Data Lakes

    I. Taha, M. Lissandrini, A. Simitsis, Y. Ioannidis

    International Journal of Semantic Computing, 2025

  4. 2024Conference

    A Study on Efficient Indexing for Table Search in Data Lakes

    I. Taha, M. Lissandrini, A. Simitsis, Y. Ioannidis

    In IEEE International Conference on Semantic Computing (ICSC), 2024

Education

Education

Degrees and exchanges across Denmark, Greece, France, Sweden, and Palestine.

Dual PhD Degree June 2022 - Present

Data Engineering for Data Science

Aalborg University, Denmark & National and Kapodistrian University of Athens, Greece

PhD research on interactive data exploration and analytics in large-scale, heterogeneous data lakes.

  • Academic Engagement: Participated in 5 specialized research and technical schools focused on data engineering, big data, and AI.
  • Industry Experience: Completed data engineering internship at OpenAIRE.
Dual Master's Degree (Erasmus Mundus) October 2018 - September 2020

Big Data Analytics & 5G

Institut Polytechnique de Paris, France & University of Athens, Greece

Specialized in Big Data Management, Data Mining, Data Science, Machine Learning, AI, Deep Learning, and 5G Networks.

  • Developed expertise in scalable architectures, predictive analytics, and neural networks
  • Gained practical knowledge in distributed processing and AI-driven decision-making
  • Master's thesis on machine learning for optical signal processing
  • Completed hands-on projects and internship at Orange Labs
Erasmus Mundus Exchange August 2014 - June 2015

Computer Science

Uppsala University, Sweden

One academic year exchange program covering advanced technical subjects:

  • High Performance Computing and Programming
  • Operating Systems I and Distributed Systems
  • Computer Networks I and Computer Graphics
  • Collaborated with Master's and PhD students, gaining exposure to research-oriented learning
Bachelor of Science June 2011 - August 2016

Computer Engineering

An-Najah National University, Nablus, Palestine

Comprehensive ABET-accredited degree covering algorithms, data structures, operating systems, computer architecture, networks, microprocessors, and digital systems.

  • Completed one-year exchange at Uppsala University
  • Finalized both software and hardware graduation projects
  • Gained strong foundations in computing theory and real-world application

Honors & awards

  • ×3 Erasmus Mundus Scholarship Recipient Recognized for academic excellence in competitive international programs
  • Marie Skłodowska-Curie PhD Fellowship Supporting highly competitive doctoral research training in Europe
  • VLDB Summer School 2025 Scholarship Selected through a competitive reduced-fee award

Contact

Let's build something reliable together.

Hiring for AI/ML engineering, MLOps, or data engineering? Feel free to contact me. I'd be glad to hear from you.

Aalborg, Denmark

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