Mr Ibna Kawsar, Chongqing University, China
An emerging researcher in mechanical and vehicle engineering, [Name] currently serves as a Research Assistant at the Vehicle Dynamics and Intelligent Control Lab in Chongqing, China, and a reviewer for Annals of Robotics and Automation. With a strong background in crashworthiness, EV safety, and intelligent vehicle systems, [Name] has authored multiple peer-reviewed publications and contributed to leading journals such as Reliability Engineering & System Safety and Multibody System Dynamics. Their work emphasizes structural innovation and safety performance using advanced simulation techniques like FEA and AI-based optimization. A passionate contributor to the academic community, they are also recognized for their participation in international conferences and their reviewership in robotics and automation. Their growing influence is reflected by Google Scholar metrics with 130 citations, h-index of 3, and i10-index of 1. [Name] continues to push the boundaries of smart mobility and energy-efficient vehicle technologies.
Publication Profile
Google scholar
Education
He earned a Master’s degree in Mechanical and Vehicle Engineering from Chongqing University, China (2022–Present), where they maintained a GPA of 89.40. Their thesis focused on improving side-impact safety of battery pack systems using multi-cell square tube structures and a hybrid MCDM approach. During this research, they successfully reduced deformation by up to 48%, enhancing crashworthiness.
Previously, they completed a Bachelor’s degree in Mechanical Design, Manufacturing, and Automation at Chongqing Jiaotong University (2018–2022), also with a GPA of 89.00. Their undergraduate thesis centered on designing a versatile electric battery lift table for efficient EV battery handling, integrating mechanical durability and equipment design principles.
Their academic training includes strong fundamentals in mechanical theory, machine design, and impact mechanics. Supplementary certifications from MIPT and Udemy further enriched their expertise in material mechanics and CAE tools like Abaqus and Hypermesh.
Experience
Since January 2024, [Name] has served as a Reviewer for Annals of Robotics and Automation, evaluating manuscripts on robotics, automation, and structural optimization. As a Research Assistant at the Vehicle Dynamics and Intelligent Control Lab (Nov 2023–Present), they authored pioneering work on EV battery crashworthiness, achieving a 45% reduction in shell intrusion through FEA, now under review in the European Journal of Mechanics / A Solids.
Additionally, their comprehensive review on EV battery safety, emphasizing mechanical reliability under vibration and collisions, is under review in eTransportation. They have also presented their work at leading automotive conferences including China-SAE and FISITA Intelligent Safety Conference.
Their expertise spans advanced simulation, machine learning, and crash-resistant structural design, contributing to multidisciplinary innovation in autonomous driving, EV safety, and intelligent systems.
Awards and Honors
He has been recognized for academic and research excellence with prestigious awards. In September 2023, they received the Excellence in Energy Development and Environmental Safety Award from the Chongqing Energy Research Society, acknowledging their contribution to sustainable vehicle safety innovations.
In August 2022, they were honored with the China Government Scholarship (CGS) by the China Scholarship Council (CSC), awarded to outstanding students for academic distinction and research potential.
These accolades reflect their dedication to advancing clean and intelligent vehicle technologies.
Additionally, their work has been showcased at major industry events such as the China Society of Automotive Engineers (China-SAE) Conference (Oct 2024) and the FISITA Intelligent Safety Conference (July 2023), underlining their active involvement and recognition within the global research community.
Research Focus
He is research centers on electric vehicle (EV) safety, crashworthiness, intelligent control systems, and structural optimization. Their master’s thesis explores side-impact crash resistance using multi-cell square tube structures, integrating a hybrid Multi-Criteria Decision-Making (MCDM) approach.
They employ Finite Element Analysis (FEA), deep learning, and machine learning tools to enhance the mechanical integrity of EV battery packs under various impact scenarios, such as vibration, collision, and shock.
Beyond structural resilience, they explore data-driven safety enhancement using vehicle multibody dynamics and neural network algorithms.
This multidisciplinary focus bridges mechanical design with smart technologies, targeting real-world safety issues in autonomous driving and energy efficiency. Their contributions aim to redefine vehicle structure optimization for next-gen transportation systems.
Publication Top Notes
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📦 Deep-learning-based inverse structural design of a battery-pack system – Reliability Engineering & System Safety (2023)
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🚗 Combined recurrent neural networks and particle-swarm optimization for sideslip-angle estimation – Multibody System Dynamics (2024)
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🔋 Trajectory optimization of an electric vehicle with minimum energy consumption – Mechanism and Machine Theory (2023)
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🚦 Enhanced traffic safety and efficiency via DNN-APF for accelerated lane-change decisions – Measurement (2023)
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🛣️ Longitudinal predictive control for vehicle-following collision avoidance in autonomous driving – Sensors (2022)