Zeyang Zhou | Engineering | Most Cited Article Award

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

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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

Ismail Fidan | Engineering | Innovative Research Award

Ismail Fidan | Engineering | Innovative Research Award

Dr Ismail Fidan, Tennessee Tech University, United States

Dr. I. Fidan is a Mechanical Engineer, Researcher, and Educator with expertise in robotics, automation, additive manufacturing, and energy systems. With over 30 years of experience, he has contributed significantly to engineering research, education, and innovation. He currently serves as a Professor at Tennessee Technological University (TTU), mentoring students and leading research in smart materials and machine learning applications. He has worked as a Visiting Scholar at Pasadena City College (2022) and an ORISE Research Scientist at Oak Ridge National Laboratory (2013–2014). Dr. Fidan has received over 40 prestigious awards, including the 2024 TTU Outstanding Faculty Award and the 2020 TTU Caplenor Research Award. A Senior Member of IEEE and SME, he actively contributes to technological advancements and engineering education. His research spans carbon-fiber composites, functionally graded metamaterials, and computational optimization techniques, shaping the future of manufacturing and automation.

Publication Profile

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Education 🎓

Dr. I. Fidan earned his Ph.D. in Mechanical Engineering from Rensselaer Polytechnic Institute, USA (1996), specializing in robotics and automation. His dissertation focused on developing an automated rework cell for surface-mounted devices (SMDs), advancing manufacturing efficiency and automation techniques. Prior to that, he completed his M.Sc. in Mechanical Engineering at Istanbul Technical University, Türkiye (1991), where he conducted research on heat transfer through ultra-fine powders, contributing to energy and thermal system advancements. He obtained his B.Sc. in Mechanical Engineering from Anadolu University, Türkiye (1988), focusing on hydraulic machines, with a graduation project on vertical flow ventilators and venturi meters. During his academic journey, he also gained practical industry experience through internships at Kutahya Sugar Production Plant (1987) and TULOMSAS-Eskisehir Train Assembly Plant (1986), where he honed his technical skills in industrial manufacturing and mechanical systems.

Experience

Dr. I. Fidan is a Professor at Tennessee Technological University (TTU), where he leads cutting-edge research in additive manufacturing, machine learning, and smart materials. He is deeply involved in mentoring students and advancing engineering education through innovative curricula and hands-on research projects. In 2022, he served as a Visiting Scholar at Pasadena City College, where he developed machine learning educational resources and supported undergraduate research initiatives. From 2013 to 2014, Dr. Fidan was an ORISE Research Scientist at Oak Ridge National Laboratory, where he contributed to energy-efficient technologies, including modeling next-generation heat pump water heaters and simulating Zero Energy-Campbell Creek Houses. Beyond academia, he has collaborated with industry as a researcher and consultant, developing AI-driven solutions for HVAC and heat pumps and integrating additive manufacturing with alternative energy systems, contributing to sustainable and efficient engineering innovations.

Awards & Honors

Dr. I. Fidan has been widely recognized for his outstanding contributions to teaching, research, and innovation. In 2024, he received the TTU Outstanding Faculty Award for Teaching, followed by the ASEE National Engineering Technology Teaching Award in 2023. His research excellence was honored with the TTU WINGS UP 100 Research Achievement Award in 2022 and the JMMP Best Paper Award in 2021. In 2020, he earned the TTU Caplenor Research Award, the highest faculty distinction at TTU. His dedication to mentoring and academic leadership was acknowledged with the SME Distinguished Faculty Advisor Award in 2018 and the TTU College of Engineering Teacher Scholar Award in 2016. Dr. Fidan’s early career accomplishments include the National Academy of Engineering FOEE Award in 2013, the US Fulbright Senior Scholar Award in 2010, and the SME Jiri Tlusty Outstanding Young Manufacturing Engineer Award in 2003. With over 40 additional awards, he remains a leader in engineering education and research.

Research Focus

Dr. Fidan’s research focuses on advanced manufacturing, robotics, energy systems, and computational modeling, driving innovation in multiple engineering fields. His expertise spans additive manufacturing and 3D printing, where he pioneers smart materials and composite structures. In automation and robotics, he enhances efficiency in manufacturing processes. His work in material science and metamaterials explores functionally graded materials and nanotechnology applications. Leveraging machine learning in engineering, he develops AI-driven solutions for HVAC and heat pump systems. His contributions to sustainable energy systems involve alternative energy applications and energy-efficient designs. Additionally, his research in computational optimization applies simulated annealing and genetic algorithms to improve drilling processes. Through interdisciplinary collaborations, Dr. Fidan has produced high-impact publications in top-tier journals, contributing to significant advancements in manufacturing, automation, and smart materials.

Publication Top Notes

1️⃣ Optimum Cutting Parameters for CFRP Composites – Processes (2024) 📖
2️⃣ Functionally Graded Metamaterials: Fabrication & Modeling – (2024) 🏗️
3️⃣ Energy Efficiency in HVAC Systems Using AI – (2023) ❄️
4️⃣ Advancements in 3D-Printed Smart Materials – (2023) 🏭
5️⃣ Machine Learning in Additive Manufacturing – (2023) 🤖
6️⃣ Simulation of Zero-Energy Buildings – (2022) 🏡
7️⃣ AI-Based Predictive Maintenance for Heat Pumps – (2022) 🔥