SHAHRIAR MOMEN

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Sydney,Australia

Summary

Master of Information Technology student at the University of Technology Sydney with a Bachelor of Software Engineering (CGPA 3.75/4.00) and a strong interest in Artificial Intelligence, Machine Learning and Computer Vision. Seeking admission to a 2027 Master by Research at UTS, with a proposed focus on human pose estimation using multi-attention deep learning for robust and real-time human motion analysis. Academic experience includes machine learning, deep learning, data analysis and software development, with particular interest in efficient computer-vision models that remain reliable under occlusion, complex backgrounds and varying environmental conditions.

Overview

years of professional experience

Work History

Part-Time Supervisor, Fresh Convenience Team

Woolworths

Sydney, NSW

09.2024 - Current

Supervised team activities in fast-paced retail environment, ensuring adherence to service and operational standards.
Balanced postgraduate study with communication, teamwork, time management, and problem-solving skills.
Supervised team schedules to ensure adequate staffing at all times.
Trained new employees on company policies and operational procedures.
Monitored workflow to maintain efficiency in store operations.

Education

Master of Information Technology -

University of Technology Sydney (UTS)

Australia

12-2026

Bachelor of Software Engineering -

Daffodil International University

Bangladesh

01-2022

Skills

Programming: Python, Java, Dart
Machine Learning: Scikit-learn, classification, regression, model evaluation, feature engineering
Deep Learning: TensorFlow, PyTorch, Google Colab
Computer Vision: OpenCV, image processing, object detection, human pose estimation

Data Analysis: Pandas, NumPy, Matplotlib
Development: Flutter, mobile application development, software engineering
Tools: Git/GitHub, KNIME, Microsoft Office
Team leadership

RESEARCH INTERESTS

Human Pose Estimation
Human Keypoint Detection
Computer Vision
Deep Learning
Multi-Attention Mechanisms
Human Activity Recognition
Real-Time Computer Vision
Image Processing
Machine Learning
Human Motion Analysis
Object Detection & Tracking

RESEARCH & ACADEMIC PROJECTS

Improving Human Pose Estimation Using Multi-Attention Deep Learning, Proposed Master by Research Topic | 2026–2027
Investigating spatial and channel attention mechanisms to improve human pose-estimation accuracy.
Focusing on challenging conditions including human occlusion, complex backgrounds and varying lighting.
Exploring deep-learning architectures suitable for accurate and computationally efficient real-time pose estimation.
Planning evaluation using public datasets and metrics including AP, AR and PCK, alongside inference speed.
Comparing the proposed approach with established baseline pose-estimation models.
Machine Learning & Data Analytics Projects | UTS Academic Projects
Applied exploratory data analysis and machine-learning techniques to real-world datasets.
Developed and evaluated classification models using Python and machine-learning libraries.
Applied preprocessing, feature analysis and model evaluation using accuracy, precision, recall and F1-score.
Compared model performance and interpreted results to support data-driven conclusions.

ACADEMIC & RESEARCH EXPERIENCE

Conducted literature reviews and evaluated academic research relevant to artificial intelligence and computer vision.
Developed research questions, objectives and preliminary methodologies for technology research projects.
Applied experimental and analytical approaches to train, evaluate and compare machine-learning models.
Used academic databases and research papers to investigate current developments in AI and computer vision.

CERTIFICATION

Flutter Mobile Application Development Certification From BASIS BITM, Bangladesh

Timeline