Mohamed Ziyan Zaid

Hello, I'm Ziyan

Computer Science Graduate | Data Analytics & AI Specialist

Recent Computer Science graduate with specialization in Data Analytics. Passionate about leveraging AI, Computer Vision, and Graphics Design to solve real-world problems.

View My Skills Get In Touch

About Me

Get to know my background and expertise.

I'm a recent Computer Science graduate with a specialization in Data Analytics, passionate about the intersection of data, artificial intelligence, and creative design. My academic journey has equipped me with strong analytical skills and a deep understanding of modern technologies.

My expertise spans across Data Analytics, Computer Vision, AI technologies, and Graphics Design. I enjoy transforming complex data into meaningful insights and creating visually appealing solutions that bridge the gap between technology and user experience.

My Journey

Education

2023-2025

Bachelor of Science (Honors) in Computer Science

Data Analytics Asia Pacific University Malaysia
2020-2022

Diploma in Information and Communication Technology

Data Informatics CGPA 3.71 Asia Pacific University Malaysia
2013-2015

Secondary Education

Dharumavantha School

Skills & Technologies

My technical toolkit and expertise

Data Analytics

Data Visualization
Statistical Analysis
Python
SQL
Excel & Spreadsheets
R Programming

AI & Computer Vision

Machine Learning
Deep Learning
Computer Vision
TensorFlow & PyTorch
Neural Networks
Image Processing

Graphics Design

Photoshop
Illustrator
Premiere Pro
After Effects
Affinity
DaVinci Resolve

My Projects

Showcasing my recent work and research.

01

Multi-Model Deep Learning for Surveillance Anomaly Detection

Computer Vision Deep Learning Python

Developed a comprehensive anomaly detection system for surveillance videos that identifies and classifies 13 different types of security threats including theft, violence, and vandalism in near real-time.

93.8%
Accuracy
4.73ms
Inference Time
25-30
FPS

Impact

Addresses SDG 16 (Peace, Justice and Strong Institutions) by enhancing public safety through automated threat detection.

Technical Approach
  • Implemented and evaluated 5 different deep learning architectures: DenseNet121, EfficientGRU, DenseRNN, ViT-Temporal Transformer, and CNN-LSTM with Attention
  • Selected CNN-LSTM with Attention as the optimal model, balancing 93.80% accuracy with 4.73ms inference time
  • Integrated YOLO object detection for enhanced situational awareness
  • Built a multi-camera desktop application using PyQt6 for real-time monitoring
Key Features
  • Processes 25-30 fps on standard hardware (NVIDIA RTX 4060)
  • Temporal smoothing to reduce false positives
  • Dual-interface system with live monitoring and analytics dashboard
  • Supports multiple concurrent camera feeds
  • Intrusion detection mode with person-specific alerts
02

Histopathological Cancer Classification with Deep Learning

Medical AI Deep Learning Healthcare

Developed deep learning models for automated cancer detection in tissue samples, achieving 99.55% accuracy in distinguishing between benign and malignant tissues from lung and colon samples.

99.55%
Accuracy
98.8%
Precision
5
Tissue Classes

Clinical Relevance

Demonstrates potential for AI-assisted pathology to reduce diagnostic time and improve consistency in cancer detection, addressing the 10-30% disagreement rate among pathologists.

Technical Approach
  • Implemented two architectures: Custom CNN and Hybrid CNN-LSTM
  • CNN model achieved superior performance (99.55% test accuracy)
  • Hybrid CNN-LSTM achieved 98.80% accuracy with attention mechanisms
  • Comprehensive hyperparameter optimization using focused random search
Key Achievements
  • Perfect classification (100% precision/recall) for colon tissues
  • 98%+ accuracy for challenging lung cancer subtype differentiation
  • Balanced performance across all 5 tissue classes
  • Efficient processing of 768×768 pixel histopathological images

Get In Touch

Let's connect and discuss opportunities.

I'm always interested in hearing about new projects and collaborations.

Email

m.ziyan4572@gmail.com

Location

Male', Maldives