About Me
Hi there! This is Maryam Hashemi's personal page.
I’m an AI scientist based on Sydney. My expertise lies in Artificial Intelligence (AI), Machine Learning (ML), and developing algorithms for intelligent systems. I am passionate about promoting transparent AI, AI for good, and solving real-world problems.
The best way to reach me is through my email, which you can find on the left side at the bottom of the page. To stay updated with the latest news, please refer to the 'News' section at the bottom of the page.
Computer Skills
Python
90%
C++
65%
HTML
65%
MATLAB
60%
Android
60%
LaTeX
100%
TensorFlow
90%
Keras
80%
Scikit-Learn
90%
OpenCV
100%
PyTorch
50%
Gym
80%
Windows
80%
Linux
40%
Python
90%
C++
65%
HTML
65%
Android
60%
LaTeX
100%
TensorFlow
90%
Keras
80%
Scikit-Learn
90%
OpenCV
100%
PyTorch
50%
Gym
80%
Windows
80%
Linux
40%
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
•
Bachelor of science in Electrical Engineering, 2013-2017.
• University of Isfahan, Isfahan, Iran.
• University of Isfahan, Isfahan, Iran.
•
Master of science in Information Technology, 2017-2020.
• Iran University of Science and Technology (IUST), Tehran, Iran.
• Iran University of Science and Technology (IUST), Tehran, Iran.
•
Researcher at school of electrical engineering, 2019-2020.
West Pomeranian University of Technology (ZUT), Szczecin, Poland.
West Pomeranian University of Technology (ZUT), Szczecin, Poland.
•
Ph.D. candidate at school of computer science and engineering, 2021-2025.
• University of New South Wales (UNSW), Sydney, Australia.
• University of New South Wales (UNSW), Sydney, Australia.
•
Master of science in Information Technology, 2017-2020.
• 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.
• 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.
•
Bachelor of science in Electrical Engineering, 2013-2017.
• 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 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.
•
Ph.D. candidate at school of computer science and engineering, 2021-2025.
• 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.
• 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.
CV
To see my CV in more detail, click here.
However, for an up-to-date one, please send me an email.