• 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
• Publications:
  • 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
  • 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
  • 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

• Writing verification environment scripts using Python, NLP, Bash, Linux and Git
• Verifying design function using System Verilog simulators
• Received best possible performance reviews and ranked among top engineers

• Designed and implemented robust web scraping platform for static and dynamic content
• Developed configurable XPath and regex-based extractors for affiliation metadata
• Mapped extracted data to publication IDs across heterogeneous publisher websites
• Explored ML models (transformer-based) for automated entity recognition
• Successfully extracted and linked affiliation data for majority of publisher sources

• Applied RNNs and deep learning for signal processing in optical communications
• Reduced preprocessing time from 4 hours to 3 minutes through optimization
• Data engineering, preparation, optimization, processing, and analysis
• Improved BER (Bit Error Rate) using regression-based RNN models

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