Nayab Ijaz

Dedicated Computer Science student specializing in AI and automation. Experienced in bridging the gap between complex neural architectures (CNNs, LSTMs) and real-world business applications. Proven track record in technical brand development and workflow automation for creative agencies.

Possesses versatile skills in project management, problem-solving, and collaboration. Brings fresh perspective and strong commitment to quality and success. Recognized for adaptability and proactive approach in delivering effective solutions.

Digit Synthesis Architecture (DCGAN)

• Technologies Used: PyTorch, Python, Deep Learning, Generative Models
• Designed and implemented a Deep Convolutional Generative Adversarial Network (DCGAN) for digital forensics and image synthesis tasks.
• Optimized generator and discriminator loss functions, ensuring high-fidelity structural generation while stabilizing neural network training.

Intelligent Chess Engine Agent

• Technologies Used: Python, Algorithms, Adversarial Search
• Developed a functional chess engine utilizing the Minimax algorithm enhanced with Alpha-Beta Pruning to optimize decision-making depth.
• Implemented custom evaluation metrics to assess board states, significantly reducing computational search tree space while maintaining high strategic accuracy.