Dr. Sina Safari ๐ is a dynamic Senior Research Associate in Data Science for Material Engineering at the University of Bristol ๐ฌ๐ง, specializing in nonlinear dynamics, structural integrity, and AI/ML applications in engineering ๐ก๐ค. With a Ph.D. in Dynamics and Control from the University of Exeter and a Global Talent Visa, he has authored numerous impactful publications ๐ in top-tier journals and conferences. His research integrates physics-informed machine learning, multiscale modeling, and fatigue testing to address real-world engineering challenges ๐ฌโ๏ธ. A passionate educator ๐จโ๐ซ and Associate Fellow of the Higher Education Academy, he has also contributed to multiple high-profile research projects including SINDRI and ADDISONIC partnerships. Dr. Safariโs international collaborations, innovation in structural modeling, and leadership in research bids make him a rising force in computational and experimental mechanics ๐๐๏ธ.
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๐ Education
Dr. Sina Safari holds a Ph.D. in Dynamics and Control from the University of Exeter, UK ๐ฌ๐ง, where his research focused on data-driven, physics-informed modeling of nonlinear dynamical systems from vibration data ๐๐ฌ. Prior to this, he earned an M.S. in Hydraulic Structures from the University of Tabriz, Iran ๐ฎ๐ท, where he specialized in vibration control and fluid-structure interaction ๐๐๏ธ. He also holds a B.S. in Civil Engineering from Azarbaijan Shahid Madani University, focusing on structural design and earthquake engineering ๐๏ธ๐. His academic journey showcases a solid foundation in structural mechanics, coupled with advanced analytical techniques and interdisciplinary knowledge, preparing him for high-level research in modern mechanical and civil engineering domains. His global education trajectory reflects both depth and diversity in the fields of engineering and applied sciences ๐๐ง .
๐ผ Professional Experience
Dr. Sina Safari has built a rich professional portfolio across academia, industry, and research sectors ๐. Currently a Senior Research Associate at the University of Bristol ๐ฌ๐ง, he contributes to the SINDRI Partnership with EDF on data-driven structural integrity assessment ๐งช๐ง. Previously, he served as a postdoctoral researcher at Bournemouth University, leading fellowship bids and industrial consultancy projects. His earlier roles include research assistantships, teaching assistant positions at the University of Exeter, and engineering roles in Iran ๐๏ธ. From MATLAB instruction to technical site engineering and structural design, his career spans hands-on construction to high-impact computational research. With consistent involvement in collaborative, cross-disciplinary environments, Dr. Safari combines engineering intuition, academic rigor, and project leadership, bridging the gap between traditional structural mechanics and modern computational intelligence ๐ค๐ก.
๐ฌ Research Interests
Dr. Safari’s research is driven by a passion for solving complex engineering problems through intelligent modeling and data science ๐๐. His core interests include nonlinear system identification, structural dynamics, fatigue testing, and multiscale modeling of materials and assemblies ๐งฉโ๏ธ. He integrates machine learning and artificial intelligenceโespecially physics-informed neural networks and recurrent neural operatorsโinto engineering workflows for predictive diagnostics and design optimization ๐ค๐ ๏ธ. Additionally, he works on shape optimization, vibration-based structural health monitoring, and uncertainty quantification of bolted joints. His research aligns with pressing challenges in aerospace, nuclear, and civil sectors, contributing toward digital twins and smart engineering systems. With a balance of experimental insight and data-driven innovation, Dr. Safari is advancing the frontier of next-generation materials and structures ๐๏ธ๐๐.
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Awards and Honors
Dr. Sina Safari was awarded a fully funded Ph.D. studentship at the University of Exeter, recognizing his potential in advanced structural dynamics research ๐๐. He is a recipient of the prestigious UK Global Talent Visa, which honors individuals making significant contributions to science and innovation on an international scale ๐๐. His selection as a key researcher within UK-funded initiatives like the SINDRI and ADDISONIC projects reflects peer recognition of his scientific excellence and leadership. Moreover, his roles in winning and leading high-level fellowship proposals, including submissions to the Royal Academy of Engineering and Leverhulme Trust, highlight his proactive contribution to competitive research landscapes ๐งช๐. These accolades underscore Dr. Safariโs outstanding scholarly impact, cross-border relevance, and dedication to transformative engineering research ๐ก๐.
๐ ๏ธ Research Skills
Dr. Safari possesses a robust arsenal of technical and analytical skills that empower his research in both experimental and computational domains ๐ง ๐ป. He is proficient in MATLAB, Simulink, Python, LabVIEW, and C programming for advanced simulations and modeling tasks ๐๐ฌ. His expertise spans finite element tools such as ABAQUS, ANSYS, OpenSees, and SAP2000, enabling precise modeling of complex materials and assemblies ๐๏ธ๐งช. Skilled in vibration testing, signal processing (using tools like MEscope, SeismoSignal), and data analysis, he tackles problems in structural health monitoring and nonlinear dynamics with confidence ๐๐. His experience also includes digital image correlation, machine learning implementation, and optimization techniques for structural design. With strong communication and collaborative research project management, Dr. Safari demonstrates both technical depth and practical innovation across multiple domains ๐งฐ๐.
๐Publications Top Note
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Parametric Study of Stochastic Seismic Responses of Base-Isolated Liquid Storage Tanks under Near-Fault and Far-Fault Ground Motions
Authors: S. Safari, R. Tarinejad
Year: 2018
Citations: 38
Published in: Journal of Vibration and Control, Vol. 24, Issue 24, pp. 5747โ5764
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Estimation of Inelastic Displacement Ratio for Base-Isolated Structures
Authors: S. Yaghmaei-Sabegh, S. Safari, K.A. Ghayouri
Year: 2018
Citations: 28
Published in: Earthquake Engineering & Structural Dynamics, Vol. 47, Issue 3, pp. 634โ659
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Direct Optimisation-Based Model Selection and Parameter Estimation Using Time-Domain Data for Identifying Localised Nonlinearities
Authors: S. Safari, J.M.L. Monsalve
Year: 2021
Citations: 19
Published in: Journal of Sound and Vibration, Vol. 501, Article 116056
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Data-Driven Structural Identification of Nonlinear Assemblies: Structures with Bolted Joints
Authors: S. Safari, J.M.L. Monsalve
Year: 2023
Citations: 18
Published in: Mechanical Systems and Signal Processing, Vol. 195, Article 110296
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Characterization of Ductility and Inelastic Displacement Demand in Base-Isolated Structures Considering Cyclic Degradation
Authors: S. Yaghmaei-Sabegh, S. Safari, K.A. Ghayouri
Year: 2019
Citations: 18
Published in: Journal of Earthquake Engineering, Vol. 23, Issue 4, pp. 557โ591
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Benchmarking of Optimisation Methods for Model Selection and Parameter Estimation of Nonlinear Systems
Authors: S. Safari, J.L. Monsalve
Year: 2021
Citations: 4
Published in: Vibration, Vol. 4, Issue 3, pp. 648โ665
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Nonlinear Function Selection and Parameter Estimation of Structures with Localised Nonlinearities โ Part I: Numerical Analysis
Authors: S. Safari, J.M.L. Monsalve
Year: 2020
Citations: 3
Published in: Nonlinear Structures and Systems, Proceedings of the 38th IMAC Conference on Structural Dynamics
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Data-Driven Structural Identification of Nonlinear Assemblies: Asymmetric Stiffness and Damping Nonlinearities
Authors: S. Safari, J.M.L. Monsalve
Year: 2025
Citations: 2
Published in: Mechanical Systems and Signal Processing, Vol. 222, Article 111745
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Importance of Virtual Sensing and Model Reduction in the Structural Identification of Bolted Assemblies
Authors: S. Safari, J.M. Londoรฑo Monsalve
Year: 2023
Citations: 1
Published in: Proceedings of the Society for Experimental Mechanics Annual Conference, pp. 33โ36
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Statistical Calibration of Ultrasonic Fatigue Testing Machine and Probabilistic Fatigue Life Estimation
Authors: S. Safari, D. Montalvรฃo, P.R. da Costa, L. Reis, M. Freitas
Year: 2025
Published in: International Journal of Fatigue (under review), Article 109028
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Data-Driven Structural Identification of Nonlinear Assemblies: Uncertainty Quantification
Authors: S. Safari, D. Montalvรฃo, J.M.L. Monsalve
Year: 2025
Published in: International Journal of Non-Linear Mechanics, Vol. 170, Article 105002
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A New Design for Mitigating Interfering Modes in Cruciform Specimens to Enhance Ultrasonic Fatigue Testing
Authors: D. Montalvรฃo, S. Safari, W. Chidzikwe, P. Sewell, P. Costa, L. Reis, M. Freitas
Year: 2025
Published in: Procedia Structural Integrity, Vol. 68, pp. 472โ479
๐ Conclusion
Dr. Sina Safari is a forward-thinking, globally engaged researcher whose work bridges structural mechanics and intelligent computing ๐ค๐ง . With a solid foundation in civil and mechanical engineering, advanced training in nonlinear system dynamics, and cutting-edge applications of AI/ML in modeling and diagnostics, he exemplifies the modern multidisciplinary engineer of the future ๐๐ง. His dedication to scientific innovation, impactful teaching, and international collaboration positions him as a strong leader in the evolving fields of smart structures and material intelligence ๐๐ก. As he continues his journey at the University of Bristol and beyond, Dr. Safari is poised to make transformative contributions to digital engineering, helping shape a safer, smarter, and more sustainable world ๐โ๏ธ๐.