About Me
Hi there! This is Maryam Hashemi's personal page.
I’m a developer and researcher based in University of New South Wales (UNSW), 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.
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.