About Me
Hi there! This is Maryam Hashemi’s personal page.
I’m an AI scientist based in Sydney. Currently, I work as a Data Scientist at the City Futures Research Centre, where I analyze large-scale datasets related to urban development in Australia and apply large language models (LLMs) and machine learning techniques to extract insights.
My expertise lies in Artificial Intelligence (AI), Machine Learning (ML), and the development of intelligent systems. I am particularly passionate about transparent and trustworthy AI, leveraging AI for social good, and solving real-world problems.
The best way to reach me is via email, which you can find at the bottom left of this page. To stay updated with my latest work and activities, please visit the “News” section at the bottom of the page.
Computer Skills
Python
C++
HTML
MATLAB
TensorFlow
PyTorch
Keras
Scikit-Learn
Transformers
OpenCV
Gym
Windows
Linux
Python
C++
HTML
Android
TensorFlow
PyTorch
Keras
Scikit-Learn
Transormers
OpenCV
Gym
Windows
Linux
Publications
1- Driver Safety Development: Real-Time Driver Drowsiness Detection System Based on Convolutional Neural Network. Maryam Hashemi, Alireza Mirrashid and Aliasghar Beheshti Shirazi, SN Computer Science Journal, Springer, 2020. 2- Towards Safer Roads: A Deep Learning-Based Multimodal Fatigue Monitoring System. Maryam Hashemi, Bahar Farahani and Farshad Firouzi, International Conference on Omni-layer Intelligent Systems (COINS), IEEE, 2020. 3- Detection and identification of defects in 3D-printed dielectric structures via thermographic inspection and deep neural networks. Barbara Szymanik, Grzegorz Psuj, Maryam Hashemi, and Przemyslaw Lopato, Materials Journal, MDPI, 2021. 4- Delve into Multiple Sclerosis (MS) Lesion Exploration: A Modified Attention U-Net for MS Lesion Segmentation in Brain MRI. Maryam Hashemi, Mahsa Akhbari, and Christian Jutten, Computers in Biology and Medicine Journal, Pergamon, 2022. 5- Understanding User Preferences in Explainable Artificial Intelligence: A Survey and a Mapping Function Proposal. Maryam Hashemi, Ali Darejeh, and Francisco Cruz, 2024. 6- A User-Centric Exploration of Axiomatic Explainable AI in Participatory Budgeting. Maryam Hashemi, Ali Darejeh, and Francisco Cruz, 2024.Education
• University of Isfahan, Isfahan, Iran.
• Iran University of Science and Technology (IUST), Tehran, Iran.
West Pomeranian University of Technology (ZUT), Szczecin, Poland.
• University of New South Wales (UNSW), Sydney, Australia.
• Iran University of Science and Technology (IUST), Tehran, Iran.
• Thesis Title: Deep learning-based Driver Distraction and Drowsiness Detection.
• Description: Analysis of driver's face to find risky situations (e.g., sleeping) through designing deep neural networks for real-time tasks.
• University of Isfahan, Isfahan, Iran.
• Thesis Title: Designing an Android application to have an Intelligent Greenhouse.
• Description: Control of vital conditions of plants by Internet Of Things with an Android application.
• University of New South Wales (UNSW), Sydney, Australia.
• Thesis Title: Toward a transparent world: axiomatic explainable artificial intelligence.
• Description: Developing algorithms that can make automated justification and reasoning for AI systems based on axioms.
