Dr. Siamak Pedrammehr
Tabriz Islamic Arts University, Tabrīz, Āz̄arbāyjān-e Sharqī, Iran
+2
Man know thyself; then thou shalt know the universe and God
'%3e%3cpath%20d='M22.1642%2019.0924C21.7317%2018.068%2021.1041%2017.1375%2020.3163%2016.3527C19.5309%2015.5656%2018.6006%2014.9381%2017.5766%2014.5048C17.5674%2014.5002%2017.5582%2014.4979%2017.5491%2014.4933C18.9774%2013.4616%2019.9059%2011.7811%2019.9059%209.88504C19.9059%206.74408%2017.3611%204.19922%2014.2201%204.19922C11.0792%204.19922%208.53429%206.74408%208.53429%209.88504C8.53429%2011.7811%209.46282%2013.4616%2010.8912%2014.4956C10.882%2014.5002%2010.8728%2014.5025%2010.8636%2014.5071C9.83652%2014.9404%208.91487%2015.5617%208.1239%2016.355C7.33685%2017.1404%206.70933%2018.0707%206.276%2019.0947C5.85031%2020.0972%205.62072%2021.172%205.59967%2022.2609C5.59905%2022.2853%205.60335%2022.3097%205.61229%2022.3325C5.62123%2022.3553%205.63465%2022.376%205.65174%2022.3935C5.66883%2022.4111%205.68926%2022.425%205.71182%2022.4345C5.73437%2022.444%205.7586%2022.4489%205.78308%2022.4489H7.15868C7.25956%2022.4489%207.3398%2022.3686%207.3421%2022.2701C7.38795%2020.5001%208.09868%2018.8425%209.35506%2017.5861C10.655%2016.2862%2012.3814%2015.5709%2014.2201%2015.5709C16.0588%2015.5709%2017.7852%2016.2862%2019.0852%2017.5861C20.3415%2018.8425%2021.0523%2020.5001%2021.0981%2022.2701C21.1004%2022.3709%2021.1807%2022.4489%2021.2815%2022.4489H22.6571C22.6816%2022.4489%2022.7058%2022.444%2022.7284%2022.4345C22.751%2022.425%2022.7714%2022.4111%2022.7885%2022.3935C22.8056%2022.376%2022.819%2022.3553%2022.8279%2022.3325C22.8369%2022.3097%2022.8412%2022.2853%2022.8406%2022.2609C22.8176%2021.165%2022.5907%2020.0989%2022.1642%2019.0924ZM14.2201%2013.8284C13.1678%2013.8284%2012.1773%2013.418%2011.4322%2012.6729C10.6871%2011.9278%2010.2767%2010.9374%2010.2767%209.88504C10.2767%208.83271%2010.6871%207.84227%2011.4322%207.09715C12.1773%206.35204%2013.1678%205.94165%2014.2201%205.94165C15.2724%205.94165%2016.2629%206.35204%2017.008%207.09715C17.7531%207.84227%2018.1635%208.83271%2018.1635%209.88504C18.1635%2010.9374%2017.7531%2011.9278%2017.008%2012.6729C16.2629%2013.418%2015.2724%2013.8284%2014.2201%2013.8284Z'%20fill='%238590A2'/%3e%3c/g%3e%3c/svg%3e)
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Academic Career Length
16Years (2011-Present)
(Calculated once Scilit publication data is synced: current year − year of first publication + 1)
Representative Publications
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Journal Article
MKMahdieh Taiyeb Khosroshahi
Mahdieh Taiyeb KhosroshahiSMSoroush Morsali
Soroush MorsaliSGSohrab Gharakhanlou
Sohrab GharakhanlouAAAlireza Motamedi Alanagh
Alireza Motamedi AlanaghSHSaeid Hassanbaghlou
Saeid Hassanbaghlou
Ali Jafarizadeh +3
Alzheimer’s disease (AD) remains a significant global health challenge, affecting millions worldwide and imposing substantial burdens on healthcare systems. Advances in artificial intelligence (AI), particularly in deep learning and machine learning, have revolutionized neuroimaging-based AD diagnosis. However, the complexity and lack of interpretability of these models limit their clinical applicability. Explainable Artificial Intelligence (XAI) addresses this challenge by providing insights into model decision-making, enhancing transparency, and fostering trust in AI-driven diagnostics. This review explores the role of XAI in AD neuroimaging, highlighting key techniques such as SHAP, LIME, Grad-CAM, and Layer-wise Relevance Propagation (LRP). We examine their applications in identifying critical biomarkers, tracking disease progression, and distinguishing AD stages using various imaging modalities, including MRI and PET. Additionally, we discuss current challenges, including dataset limitations, regulatory concerns, and standardization issues, and propose future research directions to improve XAI’s integration into clinical practice. By bridging the gap between AI and clinical interpretability, XAI holds the potential to refine AD diagnostics, personalize treatment strategies, and advance neuroimaging-based research.
3
31 May 2012 in The International Journal of Advanced Manufacturing Technology
Journal Article
29 March 2012 in Journal of Mechanical Science and Technology
Journal Article
29 April 2014 in Robotica
Journal Article
MQMohammad Reza Chalak Qazani
Mohammad Reza Chalak Qazani
Siamak PedrammehrARArash Rahmani
Arash Rahmani
BDBehzad Danaei
Behzad Danaei
MEMir Mohammad Ettefagh
Mir Mohammad EttefaghHAHamid Abdi
Hamid Abdi
+1
SUMMARY: Parallel mechanisms possess several advantages such as the possibilities for high acceleration and high accuracy positioning of the end effector. However, most of the proposed parallel manipulators suffer from a limited workspace. In this paper, a novel 6-DOF parallel manipulator with coaxial actuated arms is introduced. Since parallel mechanisms have more workspace limitations compared to that of serial mechanisms, determination of the workspace in parallel manipulators is of the utmost importance. For finding position, angular velocity, and acceleration, in this paper, inverse and forward kinematics of the mechanism are studied and after presenting the workspace limitations, workspace analysis of the hexarot manipulator is performed by using MATLAB software. Next, using the obtained cloud of points from simulation, the overall borders of the workspace are illustrated. Finally, it is shown that this manipulator has the important benefits of combining a large positional workspace in relation to its footprint with a sizable range of platform rotations.
1 February 2019
Conference Paper
Siamak PedrammehrMQMohammad Reza Chalak Qazani
Mohammad Reza Chalak Qazani
HAHoushyar Asadi
Houshyar Asadi
SNSaeid Nahavandi
Saeid Nahavandi
Hexarot is a popular member of the axisymmetric parallel mechanisms family. One of the challenges in hexarot manipulators is to analyze their manipulability. In this paper, the kinematics of hexarot mechanisms is addressed. The manipulating ability of hexarot mechanism in positioning and orienting of the end effector is investigated. The manipulability of hexarot mechanism is formulated and illustrated within the different sections of the mechanism workspace using the kinematic formulation and manipulability index relations.
11 April 2018 in International Journal of Precision Engineering and Manufacturing
Journal Article
Mohammad Reza Chalak QazaniSiamak PedrammehrMNMohammad Javad Nategh
Mohammad Javad NateghAbout Me
I am an Assistant Professor of Engineering at Tabriz Islamic Art University with a Ph.D. in Engineering from Deakin University, Australia. My academic background spans mechanical engineering, intelligent systems, and systems engineering, with research experience in both Australia and Iran, including postdoctoral and research fellow positions.
My research focuses on the application of artificial intelligence and data-driven approaches to complex engineering and cyber-physical systems. In particular, I work on developing intelligent modeling, optimization, and control frameworks that support decision-making and performance enhancement in multidisciplinary engineering systems. My work bridges traditional engineering disciplines with computational intelligence to address real-world, system-level challenges.
I have authored over 100 peer-reviewed journal and conference publications and have received several research and teaching excellence awards in recent years, including Research Excellence Awards (2024–2025) and national recognition as a Young Assistant Professor. I actively contribute to the academic community as a reviewer and editor for international journals and welcome collaborations in systems-oriented and interdisciplinary engineering research.
Research Interests:
Systems Engineering and Engineering Systems,
Artificial Intelligence in Engineering,
Data-Driven Modeling,
Complex Systems,
Cyber-Physical Systems
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