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Helina T. Web, Backend and General Development

My name is Helina T. and I have over 2 years of experience in the tech industry. I specialize in the following technologies: Beautiful Soup, Python, Web Scraping, CSS, Bootstrap, etc.. I hold a degree in Master of Engineering (MEng), Bachelor of Computer Science (BCompSc). Some of the notable projects I’ve worked on include: Bidirectional Cross modal Attention for Video Question Answering model, Yellow Pages Scraper – Multi-Site Data Extraction Desktop App, HateSpeech detection, Brain Tumor Detection and Classification. I am based in Adama, Ethiopia. I've successfully completed 4 projects while developing at Softaims.

I specialize in architecting and developing scalable, distributed systems that handle high demands and complex information flows. My focus is on building fault-tolerant infrastructure using modern cloud practices and modular patterns. I excel at diagnosing and resolving intricate concurrency and scaling issues across large platforms.

Collaboration is central to my success; I enjoy working with fellow technical experts and product managers to define clear technical roadmaps. This structured approach allows the team at Softaims to consistently deliver high-availability solutions that can easily adapt to exponential growth.

I maintain a proactive approach to security and performance, treating them as integral components of the design process, not as afterthoughts. My ultimate goal is to build the foundational technology that powers client success and innovation.

Main technologies

  • Web, Backend and General Development

    2 years

  • Beautiful Soup

    1 Year

  • Python

    1 Year

  • Web Scraping

    1 Year

Additional skills

Direct hire

Potentially possible

Previous Company

Addis Software

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Experience Highlights

Bidirectional Cross modal Attention for Video Question Answering model

Developed a Bidirectional Cross-Modal Attention model for a Video Question Answering (VQA) system in Amharic and English. The system jointly processes visual (CLIP, TimeSformer, FastRCNN) and textual (BERT) features, aligning them using bidirectional attention layers to improve answer accuracy. This approach enhanced fine-grained visual-text alignment, outperforming baseline VQA models, especially in low-resource language settings.

Yellow Pages Scraper – Multi-Site Data Extraction Desktop App

i have developed a powerful desktop application to scrape detailed business information from multiple Yellow Pages websites. The tool extracts key details such as business names, addresses, phone numbers, emails, websites, and more. Implemented efficient web scraping techniques, anti-bot measures, and a user-friendly interface for easy operation. It features a secure verification system to control access and prevent unauthorized use.

Brain Tumor Detection and Classification

The Brain Tumor Detection and Classification System incorporates a comprehensive set of features to deliver a robust and user-friendly experience Beginning with the integration of medical imaging data, the project meticulously preprocesses and augments datasets to optimize the model's generalization capabilities. Leveraging TensorFlow and Keras, a sophisticated Convolutional Neural Network (CNN) architecture is crafted, aiming for high accuracy, sensitivity, and specificity in the detection and classification of brain tumors.

Education

  • Adama Science and Technology University

    Master of Engineering (MEng) in

    2023-01-01-2025-01-01

  • Adama Science and Technology University

    Bachelor of Computer Science (BCompSc) in Computer science

    2018-01-01-2023-01-01

Languages

  • Amharic
  • English

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