Zeyang Zhou | Engineering | Most Cited Article Award

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Zeyang Zhou | Engineering | Most Cited Article Award

Dr. Zeyang Zhou, Tianjin University, China

Dr. Zeyang Zhou is an Assistant Researcher at the School of Mechanical Engineering, Tianjin University, China. He specializes in surgical navigation, virtual/mixed reality (VR/MR)-assisted precision surgery, and intelligent medical image processing. With extensive experience in developing advanced technologies for minimally invasive surgery, he has led and contributed to multiple high-impact publications in biomedical engineering journals. His academic journey includes a Ph.D., M.S., and B.S. in Mechanical Engineering from Tianjin University, and a stint as a visiting Ph.D. student at the University of Cambridge. Dr. Zhou’s interdisciplinary expertise bridges engineering, computer science, and medicine, making significant strides in image-guided surgeries and personalized surgical simulations. His work integrates AI, MR, and machine learning into real-time clinical applications. Recognized for his impactful research and academic contributions, Dr. Zhou represents a new generation of researchers driving innovation in the integration of mechanical engineering with healthcare technologies.

Publication Profile

scopus

Education

Dr. Zeyang Zhou completed his entire higher education in Mechanical Engineering at Tianjin University, China, one of the country’s leading engineering institutions. He earned his Bachelor’s degree between 2013 and 2017, followed by a Master’s degree from 2017 to 2019, where he delved deeper into biomedical engineering applications. From 2019 to 2023, he pursued his Ph.D., focusing on surgical navigation systems and VR/MR applications in surgery. As part of his doctoral training, he was a visiting Ph.D. student at the University of Cambridge, UK, where he gained international exposure and collaborated with leading experts in the field. His academic training reflects a strong foundation in mechanical design, computational methods, and medical image processing, equipping him with the tools to innovate in precision medicine and minimally invasive surgical technology. This diverse and robust academic background fuels his interdisciplinary research approach.

Experience

Dr. Zeyang Zhou currently holds the position of Assistant Researcher at the School of Mechanical Engineering, Tianjin University since July 2023, where he is involved in cutting-edge research in surgical technologies. Before that, he served as a Postdoctoral Research Fellow in the same department, continuing his work on intelligent surgical systems and image-guided navigation from July 2023 onward. His early experience includes contributing to multidisciplinary teams focused on VR/MR-enhanced surgery, where he applied advanced mechanical and computational methods to solve real-world clinical problems. His collaborative work with surgeons, radiologists, and computer scientists has resulted in multiple peer-reviewed publications in top journals. Through continuous engagement in academia and research, Dr. Zhou has cultivated expertise in modeling soft-tissue mechanics, image registration, and neural network applications in surgery. His experience reflects a commitment to innovation, research excellence, and impactful medical technology development.

Awards and Honors

While specific awards are not listed in the provided profile, Dr. Zeyang Zhou’s selection as a Visiting Ph.D. Student at the University of Cambridge highlights significant academic recognition and trust in his research capabilities. This prestigious opportunity is typically granted to outstanding doctoral candidates showing exceptional promise in their fields. Additionally, his multiple first-author publications in top-tier international journals, including Medical Physics, Computers in Biology and Medicine, and Expert Systems with Applications, underscore his recognition within the research community. His continued progression from Ph.D. student to postdoc and now Assistant Researcher at Tianjin University further reflects institutional recognition of his contributions and research excellence. It is expected that Dr. Zhou has received internal university fellowships or academic performance-based honors, often common among top research scholars in China. As his career progresses, he is well-positioned to receive international research awards and fellowships in medical robotics and computational medicine.

Research Focus

Dr. Zeyang Zhou’s research is centered on surgical navigation systems, VR/MR-assisted precision surgery, and minimally invasive surgical robotics. His work aims to enhance the accuracy and efficiency of complex surgical procedures through intelligent systems that merge real-time imaging, machine learning, and 3D visualization technologies. One of his major focuses is on mixed reality-based navigation platforms for procedures like glioma resection and hypertensive intracerebral hemorrhage treatment, improving spatial awareness and decision-making in the operating room. He also explores neural network-based respiratory motion modeling, needle insertion planning, and automated medical image segmentation using AI techniques. His interdisciplinary approach integrates mechanical engineering, biomedical imaging, and artificial intelligence, with a strong emphasis on translating theoretical frameworks into clinically viable tools. Dr. Zhou’s research not only improves patient safety and surgical precision but also provides virtual training environments for clinicians using simulation technologies.

Publication Top Notes

  • 🧠 Segmentation of Brain Tumor Resections In Intraoperative 3D Ultrasound Images Using a Semi-supervised Cross nnSU-Net

  • 🪡 A method for predicting needle insertion deflection in soft tissue based on cutting force identification

  • 🫁 A back propagation neural network based respiratory motion modelling method

  • 🤖 A high-dimensional respiratory motion modeling method based on machine learning

  • 🧪 Personalized virtual reality simulation training system for percutaneous needle insertion and comparison of zSpace and vive

  • 🧠 Augmented reality surgical navigation system based on the spatial drift compensation method for glioma resection surgery

  • 🧠 Validation of a surgical navigation system for hypertensive intracerebral hemorrhage based on mixed reality using an automatic registration method

  • 🧠 Design and validation of a navigation system of multimodal medical images for neurosurgery based on mixed reality

  • 🧠 Surgical Navigation System for Hypertensive Intracerebral Hemorrhage Based on Mixed Reality

  • 🎯 DVH-based inverse planning for LDR pancreatic brachytherapy

  • 🧠 Surgical navigation system for brachytherapy based on mixed reality using a novel stereo registration method

Ibna Kawsar | Engineering | Excellence in Citation Achievement Award

Published on by Citation Awards

Ibna Kawsar | Engineering | Excellence in Citation Achievement Award

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

  • 📦 Deep-learning-based inverse structural design of a battery-pack system – Reliability Engineering & System Safety (2023)

  • 🚗 Combined recurrent neural networks and particle-swarm optimization for sideslip-angle estimation – Multibody System Dynamics (2024)

  • 🔋 Trajectory optimization of an electric vehicle with minimum energy consumption – Mechanism and Machine Theory (2023)

  • 🚦 Enhanced traffic safety and efficiency via DNN-APF for accelerated lane-change decisions – Measurement (2023)

  • 🛣️ Longitudinal predictive control for vehicle-following collision avoidance in autonomous driving – Sensors (2022)