Personal profile
Biography
Mr. Hesam (Sam) Hosseini was born in Mashhad, Iran. He received the BSc’s degree in Computer Engineering from Islamic Azad University (IAU), Mashhad Branch, Mashhad, Iran (Jul. 2021). He passed 152 credits in three years instead of four years with CGPA is 19.04/20 (4 out of 4) which is equivalent to High Distinction in Australian education system and Top-Ranked Student in each term. His B.Sc thesis with excellent grade was entitle “Lung Cancer Detection Based on Deep Learning”. While working at IAU as a Teaching Assistant (TA), he was responsible for helping with lesson plans, monitoring students, and assisting students with study skills and special assignments. As someone with three years of experience as a teaching assistant, he understands the importance of creating a challenging, fun, and safe environment for students.
Therefore, he was admitted at Ferdowsi University of Mashhad (FUM) as exceptional talent in Oct 2021 for the master of science degree in Artificial Intelligence without requiring an entrance exam, which is a routine process for getting admitted for postgraduate studies. He successfully pass 23 credits with CGPA of 16.53/20 (3.51 out of 4), he obtained forth rank in the class among 15 students. His MSC thesis with excellent grade was entitle “PE diagnosis Using Deep Neural Network” in Sep 2023. He was Tutor in Digital Image processing (MSC Course) and Computer vision (BSC Course) at FUM. Also, he was elected Head of the Executive Committee at the 12th International Conference on Computer and Knowledge Engineering (ICCKE2022).
Currently, he is a PhD candidate at Curtin Medical School,Perth, Australia and researcher at Harry Perkins Institute of Medical Research South.
His main research topic is efficient deep learning computing. He has also been contributing to a wide span of applications in Machine Learning and Computer Vision. Apart from academic, he is a music enthusiast and have been playing guitar since 15 years old.
Education/Academic qualification
Health of Science - AI, PhD, Automated Frailty Assessment Using Deep Learning for Predicting Outcomes Following Surgery and Aortic Valve Replacement
3 Sept 2025 → …
Award Date: 6 Nov 2024
Artificial Intelligence and Robotics, MSc, Diagnosis of Pulmonary Embolism Area using Deep Neural Network , Ferdowsi University of Mashhad
Oct 2021 → Sept 2023
Award Date: 1 Oct 2021
Computer Engineering, BSc, Lung Cancer Diagnosis based on Deep Learning , Islamic Azad University
Sept 2018 → Jul 2021
Research expertise keywords
- Deep learning
- Medical Image Processing
- machine learning
- Image Processing
- Computer vision
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
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SDG 3 Good Health and Well-being
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Collaborations and top research areas from the last five years
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An effective hybrid algorithm for locating splicing forgery image
Hosseini, S., Vatanparast, A. & Taherinia, A. H., 18 Feb 2024, 14th International Conference on Computer and Knowledge Engineering (ICCKE 2024). IEEE, Institute of Electrical and Electronics Engineers, p. 259-266 8 p. (2024 14th International Conference on Computer and Knowledge Engineering, ICCKE 2024).Research output: Chapter in Book/Conference paper › Conference paper › peer-review
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Deep learning applications for lung cancer diagnosis: A systematic review
Hosseini, S., Monsefi, R. & Shadroo, S., 2024, In: Multimedia Tools and Applications. 83, 5, p. 14305–14335 31 p.Research output: Contribution to journal › Article › peer-review
53 Link opens in a new tab Citations (Scopus) -
Deep learning and traditional-based CAD schemes for the pulmonary embolism diagnosis: A survey
Hosseini, S., Taherinia, A. H. & Saadatmand, M., Dec 2023, (Submitted) arXiv, (Multim. Tools Appl.).Research output: Working paper › Preprint
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Diagnosis of Pulmonary Embolism Area using Deep Neural Network
Hosseini, S., 10 Sept 2023, (Unpublished) 95 p.Research output: Thesis › Non-UWA Thesis
Datasets
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Ferdowsi University of Mashhad Pulmonary Embolism (FUMPE)
Hosseini, S. (Creator), Masoudi, M. (Creator), Saadatmand, M. (Creator) & Pezeshki Rad, M. (Creator), Ferdowsi University of Mashhad, 2018
DOI: 10.6084/m9.figshare.c.4107803, https://figshare.com/collections/FUMPE/4107803
Dataset
Prizes
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Auckland University of Technology Doctoral Fees Scholarship
Hosseini, S. (Recipient), Sept 2024
Prize: Award