Hello, I'm
Iman Zohra
Innovative and analytical AI Engineer skilled in Machine Learning, Deep Learning, and GANs. Passionate about building intelligent systems that merge AI research and real-world impact.
Passionate About Technology
I'm a Software Engineer with 1 year of hands-on experience in web development, AI, and deep learning projects.
I have completed an internship and multiple projects focused on deep learning, GANs, and full-stack development. My work lies at the intersection of artificial intelligence and web technologies, creating experiences that are not only intelligent but also visually compelling.
Currently exploring the frontiers of generative AI and building tools that push the boundaries of what's possible with machine learning and modern web frameworks.
1+
Years Experience
3+
Projects Completed
10+
Technologies
Goal-Oriented
Focused on delivering high-quality solutions that meet project requirements
Innovative
Always exploring new technologies and methodologies to improve
Fast Learner
Quick to adapt and learn new frameworks, languages, and tools
Quality Driven
Committed to writing clean, maintainable, and efficient code
Technical Expertise
A comprehensive toolkit spanning AI, machine learning, web development, and data science
All Technologies
Featured Projects
A showcase of my work in AI, systems programming, desktop applications, and web development
Showing 5 of 5 projects
Synthetic Cancer Image Generation using GANs
Advanced GAN models for medical image synthesis at AID Lab, FAST-NUCES
Developed Generative Adversarial Networks for generating synthetic cancer histopathology images. Implemented DCGAN and WGAN models with TensorFlow/Keras and PyTorch, focusing on improving image realism. Conducted data augmentation, normalization, and loss stabilization techniques. Achieved realistic image generation results and improved dataset size by 40%. Analyzed model outputs using Inception Score (IS) and Frechet Inception Distance (FID) metrics.
Multi-Core Neural Network Simulation
OS-level neural network with process-based layers and thread-based neurons
Each neural network layer runs as a separate process, neurons execute as threads showcasing IPC, synchronization, and multi-core parallelism. Built with C++ (POSIX) on Linux, integrated a Flask backend with a React frontend for live execution, visualization, and automated evaluation. Completed as part of Operating Systems course at FAST-NUCES.
SafarPak - Route Planning Application
Optimal travel path computation across Pakistan with interactive visualization
Computes optimal travel paths across Pakistan using custom Dijkstra's Algorithm with min-heap priority queue. Features Haversine formula for accurate distance computation, interactive map visualization with animated routes, multi-modal routing, travel time estimation, fuel cost estimation, nearby places discovery, and offline export. Dark/Light/Color-Blind accessible themes and responsive UI. Developed as part of DAA coursework at FAST-NUCES.
Social Media Management System
OOP-based platform for managing posts, comments, and engagement
A Social Media Management System developed using OOP concepts like encapsulation, inheritance, and polymorphism. The system supports uploading posts, adding comments, and managing likes, with a focus on clean code architecture and Object-Oriented Programming principles. A simple and efficient platform to schedule posts, manage content, and track engagement across multiple social media platforms. Built to help users streamline their social media workflow. Associated with National University of Computer and Emerging Sciences.
Event Management System
JavaFX-based system with MySQL integration for complete event management
A JavaFX-based Event Management System featuring event viewing and filtering, user registration and authentication, and a complete budget tracking module. Designed for seamless user interaction with intuitive UI and integrated MySQL support. Developed a feature-rich Event Management System using Java, JavaFX, and SQL. Implemented user registration and authentication, budget tracking, and detailed event viewing with filtering options for a comprehensive event management experience.
Work History
My professional journey in AI research and software development
AI Engineer Intern
Designed and trained DCGAN and WGAN architectures for synthetic cancer image generation, improving dataset diversity. Implemented deep learning pipelines using TensorFlow and PyTorch for medical image synthesis and augmentation. Optimized model stability with gradient penalty, Wasserstein loss, and hyperparameter tuning. Analyzed model outputs using Inception Score (IS) and Fréchet Inception Distance (FID) metrics. Collaborated with faculty and researchers to produce high-quality research results.
Key Achievements:
- Developed Generative Adversarial Networks for generating synthetic cancer histopathology images
- Implemented DCGAN and WGAN models with TensorFlow/Keras and PyTorch
- Achieved realistic image generation and improved dataset size by 40%
- Conducted data augmentation, normalization, and loss stabilization techniques
Academic Background
My educational journey and certifications
Bachelor of Science in Computer Science
Specializing in Artificial Intelligence and Software Engineering. Completed coursework in Operating Systems, Design and Analysis of Algorithms, Deep Learning, and Full-Stack Development.
Key Achievements
- Operating Systems coursework - Multi-Core Neural Network Simulation
- DAA coursework - SafarPak Route Planning Application
- Deep Learning projects - GAN-based image generation
Certifications & Courses
Deep Learning Specialization
Online Course
Full-Stack Web Development
Online Course
Get In Touch
Have a project in mind or want to discuss opportunities? I'd love to hear from you.