Fatemeh Zare

About

I am a Software Engineering graduate student with a strong interest in Artificial Intelligence, particularly in developing intelligent systems that can interact with and support humans in meaningful ways . My research background is mainly in Deep Learning, Computer Vision, and Image Analysis . Through my academic and professional experiences, I have worked on designing AI-driven solutions while considering both technical performance and real-world usability. I am especially interested in trustworthy and human-centered AI, where models are not only accurate but also reliable, understandable, and beneficial for users. I am currently seeking opportunities to contribute to research groups working on Computer Vision, multimodal learning, and intelligent systems, with applications in areas such as Healthcare, Education, and Human-AI interaction.

Education

M.Sc. in Software Engineering

2023-2025

Islamic Azad University- Estahban Branch, Estahban, Iran

GPA: 18.67/20.0

Courses:

Deep learning, Big Data Analysis, Advanced Database, Parallel Algorithms, Advanced Operating Systems

Thesis:

Detection of Face Anti-Spoofing Attacks using DeepLabV3

Developed a face anti-spoofing framework using DeepLabV3 with ResNet101 backbone by formulating spoof detection as a pixel-level segmentation task, achieving high performance on accuracy, AUC, and HTER.

Supervisors:

Dr. Mohammadjavad Hosseinpoor, Dr. Alireza Akhavanpour

B.Sc. in Software Engineering

2016-2020

Shahid Rajaee Teacher Training University, Tehran, Iran

GPA: 17.34/20.0

Courses:

Basics of Computational Intelligence, Basics of Computer Vision,Principles of Robotics, Signals & Systems, Basics of Speech & Language Processing

Highlights:

Ranked 8th among 45 students (2020) , Recipient of the Governmental full scholarship (2016-2020)

Thesis:

Setting up an inter-enterprise VoIP network

Supervisors:

Dr. Maasoomeh Safkhani, Dr. Gholamreza Hasani

Skills

Programming Languages

I use Python extensively for machine learning and deep learning research, including model development, training, and evaluation. I also have professional experience with JavaScript/TypeScript through frontend development projects and web application development.

Machine Learning

My machine learning experience includes CNNs, Vision Transformers, transfer learning, semantic segmentation, data augmentation, hyperparameter tuning, and model evaluation. I have applied these techniques in projects involving face anti-spoofing, biometric AI, and medical image classification.

Research Expertise

My research focuses on Computer Vision, Explainable AI (XAI), and trustworthy AI systems. I have experience in face recognition, face anti-spoofing, object tracking, and medical image analysis. My recent work includes deep learning-based chest X-ray classification and explainability methods such as Grad-CAM, Integrated Gradients, and LRP.

Research Tools & Frameworks

I work with PyTorch, TensorFlow, Scikit-learn, OpenCV, NumPy, Pandas, Matplotlib, and Jupyter Notebook for AI research and experimentation. I also have experience with GPU/CUDA computing, Google Colab, Kaggle, and Git-based version control.

Software Development

I have professional frontend development experience with Vue.js, Nuxt.js, HTML, CSS, and Tailwind CSS. I have developed responsive web applications, integrated RESTful APIs and LLM APIs, and collaborated using tools such as Jira, Bitbucket, and Trello.

Teaching & Communication Skills

I have several years of experience teaching computer science, which strengthened my ability to explain technical concepts and communicate complex ideas effectively. I use English for academic communication, research, and technical writing (IELTS Academic overall: 7.5).

For detailed information, Go to Experience page

Publications

Zare, F., Yousefzade, H., Akhavanpour, A., & Hosseinpoor, M. (Final Editing) . DEEPFAS: An interpretable framework to detect Face Anti-Spoofing Attacks using DeepLabV3 and Vision Transformer . (in progress) .
Zare, F., & Hosseinpoor, M. (2025) . Detection of Face Anti-Spoofing Attacks Using DeepLabV3 . Proceedings of the 6th International Conference on Soft Computing .
Zare, F., & Hosseinpoor, M. (2025) . Comparison between distributed databases: Cockroach DB, Amazon Aurora, and Google Spanner . Proceedings of the 25th International Conference on Information Technology .
Hosseinpoor, M., & Zare, F. (2024) . A review of aspect-oriented evaluation methods in software engineering . Proceedings of the 19th National Conference of Applied Researches in Electrical, Computer and Medical Engineering Sciences .
Hosseinpoor, M., & Zare, F. (2024) . An overview of task scheduling methods in cloud computing . Proceedings of the 19th National Conference of Applied Researches in Electrical, Computer and Medical Engineering Sciences .
Naseri, H., & Zare, F. (2024) . Dynamic integrated process planning, scheduling, and due date allocation using ant colony optimization . Proceedings of the 18th National Conference of Applied Researches in Electrical, Computer and Medical Engineering Sciences .
Hosseinpoor, M., Zare, F., Salim, Z., & Izadimazidi, A. (2023) . An overview of several facial recognition methods using deep learning . Proceedings of the 17th National Conference of Applied Researches in Electrical, Computer and Medical Engineering Sciences .