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Raeha H. AI, Machine Learning and Generative AI Platforms

My name is Raeha H. and I have over 3 years of experience in the tech industry. I specialize in the following technologies: Machine Learning, Deep Learning, Computer Vision, Natural Language Processing, Generative AI, etc.. I hold a degree in Bachelor of Science (BS). Some of the notable projects I've worked on include: ISign Authentication using Machine Learning, Physics Informed Neural Network (PINN) for Wind Turbine Prediction, GenAI based FastAPI Integration ( Computer Vision ), HR-Vatar, RL Based Time Management Assistant, etc.. I am based in Islamabad, Pakistan. I've successfully completed 9 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

  • AI, Machine Learning and Generative AI Platforms

    3 years

  • Machine Learning

    2 Years

  • Deep Learning

    1 Year

  • Computer Vision

    2 Years

Additional skills

Direct hire

Potentially possible

Previous Company

HyperBaraaq

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Experience Highlights

ISign Authentication using Machine Learning

This project leverages machine learning to distinguish between fake and authentic signatures with high precision. By analyzing unique features in signature strokes, pressure patterns, and movement dyn

Physics Informed Neural Network (PINN) for Wind Turbine Prediction

The project uses (PINN) to predict wind turbine power output. It involved integrating physical laws directly into the neural network framework to enhance prediction accuracy. The PINN was trained with

GenAI based FastAPI Integration ( Computer Vision )

GenAI-based API, designed to revolutionize visual data processing capabilities. The API offers features including YOLO for real-time object detection, transforming images into detailed sketches, and e

HR-Vatar

HR-Vatar is an AI-based HR system that digitizes the hiring process. It features advanced resume parsing for swift candidate profiling. AI-simulated interviews, with an HR avatar that lip-syncs to gen

RL Based Time Management Assistant

A model based on RL to manage tasks of users aiding in time management Personalized Scheduling: - Utilizes reinforcement learning algorithms to continuously improve scheduling efficiency. Dynamic

Education

  • Air University

    Bachelor of Science (BS) in Artificial Intelligence

    2020-01-01-2024-01-01

Languages

  • English (Fluent)✓
  • Urdu (Native or Bilingual)