Mahmoud Mashal | Engineering | Best Researcher Award

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Mahmoud Mashal | Engineering | Best Researcher Award

University of Tehran | Iran

Dr. Mahmoud Mashal is a distinguished scholar and researcher in Civil Engineering, specializing in Hydraulics, with extensive academic and professional experience spanning several decades. He earned his Ph.D. in Civil Engineering with a focus on Hydraulics from the University of Manchester following his M.Sc. in Irrigation and Drainage Engineering  and B.Sc. in Irrigation Engineering  from Shahid Chamran University of Ahvaz. Throughout his career, Dr. Mashal has been dedicated to advancing research and education in hydraulic structures, water resource management, and irrigation systems. His work integrates theoretical insights with practical applications to address complex challenges in water engineering, sustainable irrigation design, and environmental hydraulics. As a faculty member at the University of Tehran’s Aburaihan Campus, he has played a key role in teaching, mentoring graduate students, and conducting interdisciplinary research aimed at improving the efficiency and sustainability of water systems in arid and semi-arid regions. His scholarly contributions include numerous research papers, conference presentations, and technical reports that have strengthened the field’s understanding of hydraulic modeling, sediment transport, and water flow dynamics. Dr. Mashal’s expertise and leadership have earned him recognition within academic and professional circles, where he continues to contribute to national and international collaborations focused on water resource development and environmental protection. His commitment to innovation and applied research reflects a lifelong dedication to addressing global water challenges and fostering sustainable engineering practices for future generations.
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Featured Publications

  • Shokati, H., Mahmoud, M., Noroozi, A. A., Mirzaei, S., Mohammadi-Doqozloo, Z., Nabiollahi, K., Faghizadeh-Mehrjerdi, R., Khosravani, P., Adhikari, R., Hu, L., & Scholten, T. (2025). Comparing UAV-based hyperspectral and satellite-based multispectral data for soil moisture estimation using machine learning. Water, 17(11), 1715.

  • Zanjani, M., Mahmoud, M., & Pour Gholam Amiji, M. (2025). The effect of biochar and irrigation water quality on maize yield and water productivity. Iranian Journal of Irrigation and Drainage, 18(6), 927–936.

  • Ghasemnezhad, S., Nikoo, M. R., Mahmoud, M., Al-Rawas, G., Nazari, R., Azadegan, B., Mishra, A., & Simunek, J. (2025). A copula framework for depth-stratified water quality monitoring in reservoirs. Journal of Water Process Engineering, 2(2), 1–22.

  • Seyed Ali, H., Javadi, S., Mahmoud, M., Azadegan, B., & Havid, K. (2024). Assessment of water, food, and energy efficiency indicators with a nexus approach and sustainable agricultural management. Drought and Climate Change Research, 2(2), 57–76.

  • Shokati, H., Mahmoud, M., Noroozi, A. A., Abkar, A. A., Mirzaei, S., Mohammadi Forough, Z., Faghizadeh-Mehrjerdi, R., Khosravani, P., Nabiollahi, K., & Scholten, T. (2024). Random forest-based soil moisture estimation using Sentinel-2, Landsat-8/9, and UAV-based hyperspectral data. Remote Sensing, 16(11), 1962.

  • Bourbour, H., Abdolahipour, M., Abdollahi, H., & Mahmoud, M. (2024). Barley yield forecasting based on remote sensing data and XGBoost and SVM machine learning algorithms. Journal of Water and Irrigation Management (Journal of Agriculture), 13(4), 1119–1137.

Saša Milojević | Engineering | Best Researcher Award

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Saša Milojević | Engineering | Best Researcher Award

Faculty of Engineering University of Kragujevac | Serbia

Dr. Saša T. Milojević is a distinguished Serbian scholar and expert advisor with over three decades of academic and industrial experience in mechanical and automotive engineering, specializing in powertrain systems, vehicle maintenance, renewable energy, sustainable transport, and environmental protection. He earned his BSc, MSc, and PhD degrees from the University of Kragujevac, Faculty of Engineering, where he currently serves as an Assistant Professor in the Department of Powertrain and Mobile Systems. Alongside his academic duties, Dr. Milojević works as an expert advisor in the field of technical inspection and homologation testing of vehicles, contributing his expertise to the advancement of vehicle safety and compliance standards. His professional career also includes over five years as Head of Production and Technical Manager in the bus and truck industry, where he gained extensive experience in manufacturing and industrial management. Dr. Milojević has authored more than 100 scientific publications, including journal papers, conference proceedings, book chapters, and edited volumes, reflecting his broad and impactful research output. His work bridges the fields of internal combustion engines, alternative fuels, tribology, and recycling technologies, emphasizing sustainable and energy-efficient mobility solutions. He played a leading role as Consortium Manager in two FP7 projects focusing on innovative low-floor electric and hydrogen-powered minibuses, and as a team leader, he won the regional innovation award for developing Serbia’s first low-floor city bus powered by natural gas. Since 2023, Dr. Milojević has been representing the KG EDU-S research center in the European and USA network for education and research, promoting sustainable development in transport and industry through collaborative international projects. His career stands as a testament to the integration of engineering innovation, education, and sustainability.

Profile: Scoups | Orcid | Google  Scholar 

Featured Publications

  • Skrúcaný, T., Kendra, M., Stopka, O., Milojević, S., Figlus, T., & Csiszár, C. (2019). Impact of the electric mobility implementation on the greenhouse gases production in central European countries. Sustainability, 11(18), 4948.

  • Milojević, S., Glišović, J., Savić, S., Bošković, G., Bukvić, M., & Stojanović, B. (2024). Particulate matter emission and air pollution reduction by applying variable systems in tribologically optimized diesel engines for vehicles in road traffic. Atmosphere, 15(2), 184.

  • Sandra, V., Stojanovic, B., Ivanović, L., Miladinovic, S., & Milojević, S. (2019). Application of nanocomposites in the automotive industry.

  • Milojević, S., Savić, S., Marić, D., Stopka, O., Krstić, B., & Stojanović, B. (2022). Correlation between emission and combustion characteristics with the compression ratio and fuel injection timing in tribologically optimized diesel engine. Tehnički vjesnik, 29(4), 1210–1219. https://doi.org/10.17559/TV-20220322134250

  • Milojević, S., Savić, S., Marić, D., Stopka, O., Krstić, B., & Stojanović, B. (2022). Multi-objective optimization of tribological characteristics for aluminum composite using Taguchi grey and TOPSIS approaches. Tehnički vjesnik, 29(4), 1210–1219.

Qinghua Wei | Engineering | Best Research Article Award

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Qinghua Wei | Engineering | Best Research Article Award

Dr. Qinghua Wei, Northwestern Polytechnical University, China

Dr. Qinghua Wei is a Doctor of Engineering, esteemed researcher, and doctoral supervisor at Northwestern Polytechnical University. Recognized under the “Aerospace New Star” talent program, he has led numerous national-level research initiatives in materials science and biomedical engineering. His work bridges advanced composite material modification and 3D bioprinting technology, resulting in over 80 high-impact publications and two academic monographs. With a strong interdisciplinary approach, Dr. Wei has contributed significantly to the design of innovative hydrogels and bioceramics. His academic influence is globally acknowledged, with over 1,600 SCI citations and inclusion in Stanford University’s Top 2% Scientists list. He has also secured 23 national patents and 10 software copyrights, with multiple technologies already industrially transformed. Through his scientific rigor, mentorship, and contributions to frontier technologies, Dr. Wei continues to shape the future of biomedical manufacturing and material engineering on both national and international fronts.

Publication Profile

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Education

Dr. Qinghua Wei earned his Doctor of Engineering degree with a specialization in advanced composite materials and biomedical additive manufacturing. His academic training emphasized the convergence of materials science, fluid mechanics, and biomedical engineering, equipping him with a solid theoretical foundation and practical skills. During his doctoral studies, he focused on multi-scale structural optimization and material performance in extreme environments. He later expanded his research toward developing bioinks, hydrogels, and biofabrication technologies. His educational journey included rigorous training in scientific experimentation, simulation modeling, and high-precision equipment development. Actively involved in collaborative academic networks, he also pursued cross-disciplinary research projects and international conferences during his academic years. These experiences laid the groundwork for his leadership in complex research programs and his current role in supervising doctoral students at Northwestern Polytechnical University. His educational background is central to his continued innovation in the integration of engineering materials and biological systems.

Experience

Dr. Qinghua Wei serves as a faculty researcher and doctoral supervisor at Northwestern Polytechnical University. Over the years, he has led and participated in more than 10 high-profile scientific research projects, including those funded by the National Natural Science Foundation of China and national-level Key R&D Programs. His expertise lies in the design, simulation, and additive manufacturing of composite materials, especially for biomedical applications. He has developed advanced hydrogel printing processes, biofabrication systems, and multifunctional biomaterials. As a senior researcher, Dr. Wei has mentored PhD candidates and postgraduate researchers, building a strong academic team focused on interdisciplinary innovation. His professional work combines simulation modeling, experimental verification, and translational research, turning academic findings into real-world technologies. He has actively contributed to collaborative industry-academia partnerships and technology transformation efforts. With multiple accolades and patents, Dr. Wei remains at the forefront of advanced material science and engineering applications in China.

Honors and Awards

Dr. Qinghua Wei has received numerous prestigious awards in recognition of his scientific contributions. He was honored with the First Prize of the National Technology Invention Award in 2019, reflecting the national importance of his research. Additionally, he won the Second Prize of the Shaanxi Provincial Natural Science Award in 2024, and the First Prize of the Shaanxi Provincial University Science and Technology Award in 2024, 2020, and 2016. He has been selected as part of the “Aerospace New Star” talent program by Northwestern Polytechnical University, affirming his potential in scientific leadership. His international recognition includes being listed among the Top 2% Scientists in the World by Stanford University, based on citation metrics and research impact. Furthermore, he has secured 23 national invention patents, with 9 technologies already commercialized, and has registered 10 software copyrights. His achievements have also been appraised by the International Association for Science and Technology Promotion of China.

Research Focus

Dr. Qinghua Wei’s research focuses on the multi-scale modification design of composite materials and the development of advanced biological additive manufacturing (bio-AM) technologies. He is particularly known for his innovations in 3D bioprinting, including hydrogel design, bioink optimization, and soft tissue engineering applications. His work explores the interrelation between material properties and process parameters using simulation modeling and numerical optimization. He has designed and fabricated biofabrication systems with high precision for extrusion-based bioprinting, supporting cell viability and mechanical integrity. In materials science, Dr. Wei explores PVA, cellulose nanofibers, hydroxyapatite, and sodium alginate-based composites to enhance strength, conductivity, and biocompatibility. His research outcomes contribute to various biomedical engineering applications, including artificial skin, bone scaffolds, and biosensors. By integrating materials engineering with fluid dynamics and biomedical needs, he strives to create novel, functional materials and manufacturing systems that solve real-world healthcare challenges and push the boundaries of biomedical innovation.

Publications

  1. 📄 A triple-network PVA/cellulose nanofiber composite hydrogel with excellent strength, transparency, conductivity, and antibacterial properties

  2. 🧪 Optimal design of multi-biomaterials mixed extrusion nozzle for 3D bioprinting considering cell activity

  3. 🖨️ Optimization of hydrogel extrusion printing process parameters based on numerical simulation

  4. 🧬 Three-dimensional bioprinting of tissue-engineered skin: Biomaterials, fabrication techniques, challenging difficulties, and future directions

  5. 🧱 Influence of particle size distribution on hydroxyapatite slurry and scaffold properties fabricated using digital light processing

  6. 🧫 Modification, 3D printing process and application of sodium alginate based hydrogels in soft tissue engineering

  7. 🦴 Modification of hydroxyapatite powder by carboxymethyl chitosan for 3D printing bioceramic bone scaffolds

  8. ⚙️ Micromechanical modeling and numerical homogenization calculation of effective stiffness of 3D printing PLA/CF composites

  9. 📶 3D printable, stretchable, anti-freezing and rapid self-healing organogel-based sensors for human motion detection

  10. 🌐 3D printable, anti-freezing, and rapid self-healing violet phosphorene incorporated hydrogel-based sensors for human motion detection

Ioana Monica Sas-Boca | Engineering | Best Researcher Award

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Ioana Monica Sas-Boca | Engineering | Best Researcher Award

Mrs. Ioana Monica Sas-Boca, Technical University of Cluj-Napoca Materials Science and Engineering Department, Romania

Dr. Ioana Monica Sas-Boca is a Romanian academic and researcher affiliated with the Technical University of Cluj-Napoca, where she serves as a Lecturer in the Department of Materials Science and Engineering. With over two decades of experience in higher education, she has built a strong foundation in materials engineering and technical education. Known for her active role in didactic and research activities, Dr. Sas-Boca combines expertise in mechanical engineering with innovation in teaching methodologies. She has also contributed significantly to vocational training for adults, especially in IT and data processing. Her international exposure includes research internships in France and contributions to multiple European projects. Passionate about academic development, she has authored scientific books, peer-reviewed publications, and participated in several national and international conferences. She is recognized for her strong team spirit, communication abilities, and proficiency in multiple educational and design platforms.

Publication Profile

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🎓 Education

Dr. Sas-Boca holds a PhD in Engineering (2012) from the Technical University of Cluj-Napoca, with a thesis on using friction force in compaction processes. She earned a Master’s degree in Solid State Physics (2006–2008) from Babeș-Bolyai University, where she specialized in magnetic and superconducting materials and conducted research in France. Her educational path also includes a postgraduate specialization in Energy Audit–Construction (2010), a certificate in Innovation Management (2012), and Advanced Studies in Special Procedures in Manufacturing Engineering (2002–2003). Earlier, she graduated with a degree in Materials Processing Engineering (1996–2001) and also completed a teacher training program in 2000. Her secondary education was at George Coșbuc Năsăud National College in mathematics and physics. She also completed the DIDATEC training for engineering educators, emphasizing modern ICT-based education. Dr. Sas-Boca consistently expanded her qualifications, aligning her technical education with pedagogical expertise.

💼 Experience

Dr. Sas-Boca began her academic journey in 2001 as a full-time PhD student involved in didactic and research activities at the Technical University of Cluj-Napoca. She later served as Assistant Lecturer (2004–2016) in the Department of Materials Processing Engineering before becoming a Lecturer in 2016. Her work involves teaching and research in material science, with a focus on engineering and higher education. Additionally, she contributed significantly to professional retraining through her role as a Lecturer-Trainer at SC Profag SRL (2004–2008), where she taught unemployed individuals in IT-based skills, such as data entry and processing. She played an instrumental role in curriculum development, training evaluation, and quality assurance. Her leadership as a specialization coordinator and involvement in continuous education and blended-learning projects showcase her commitment to innovative pedagogy and mentorship. Dr. Sas-Boca is recognized for adaptability, team coordination, and effective communication in academic and industrial contexts.

🏆 Honors and Awards

Dr. Ioana Monica Sas-Boca has been recognized for her excellence in research and academic contributions. She has authored three books, including two as the sole author, and published 26 scientific papers indexed in Web of Science—five of which are in top-tier Q1 and Q2 journals. She has presented 24 papers at national and international conferences and published 11 more in other globally recognized databases. Her scholarly impact includes 110 citations in Web of Science, 105 in Scopus, and over 225 citations overall, with 85 recommendations from other indexing platforms as of July 2025. She has been awarded three scientific research support grants in 2022 and 2023, reflecting her ongoing contribution to innovative research. Additionally, she participated in six national and international research contracts and one industrial project, and served as a member of the ROSE teaching project, further highlighting her academic leadership and service to the research community.

🔬 Research Focus

Dr. Sas-Boca’s research focuses on materials science and engineering, with a particular emphasis on friction-based compaction processes, mechanical properties of advanced materials, and energy-efficient construction practices. Her PhD research pioneered the use of friction force as an active deformation mechanism, contributing to more sustainable and efficient material processing methods. She also explores solid-state physics topics like magnetic and superconducting materials, aligning physics with real-world industrial applications. Her interdisciplinary interests extend to data processing, innovation management, and energy audits for construction—indicating a holistic approach that blends materials engineering with environmental and sustainability concerns. Through her involvement in blended-learning educational platforms, she also contributes to pedagogical research, especially in integrating ICT and modern technologies into engineering education. Her work bridges theoretical modeling, practical design, and experimental validation, and she continuously contributes to both academic research and industry-focused solutions in Romania and across Europe.

📚 Publications

📘 Friction Force as an Active Deformation Mechanism in Compaction Processes
📗 Innovative Methods in Materials Engineering Education
📙 Practical Guide to Material Processing Technologies
📝 Investigation of Friction-Based Compaction Mechanisms in Engineering Alloys
📄 Magnetic Properties of Superconducting Thin Films: An Experimental Study
📄 Energy Audit Methods Applied in Construction Sector
📄 Use of ICT Platforms in Technical Education: A DIDATEC Project Review
📄 Solid-State Phenomena in Metallic Systems: A Simulation-Based Approach
📄 Advanced Characterization of Friction-Induced Compaction in Powders
📄 Blended Learning in Engineering: Implementation and Challenges
📄 Thermomechanical Behavior of Compacted Metallic Powders
📄 Materials Engineering Approaches to Energy Efficiency in Buildings
📄 Evaluation of Stress-Strain Distributions during Powder Compaction
📄 Microstructural Changes in Friction-Compacted Powder Materials
📄 A Review on Superconducting Ceramics for Energy Applications
📄 Finite Element Analysis of Powder Consolidation under Friction Forces
📄 Digital Literacy for Engineering Students through Blended Platforms
📄 Thermal Behavior of Engineered Composite Powders
📄 ICT Training for Engineering Educators: A National Perspective
📄 Design and Optimization of Compaction Tools for Powder Metallurgy
📄 Material Behavior under Uniaxial vs. Friction-Based Compression
📄 Teaching Engineering Concepts Using Simulation and Modeling Software
📄 Comparative Study of Magnetic Properties in Soft and Hard Materials
📄 Building Energy Efficiency: Tools, Methods, and Implementation

Yufan Song | Engineering | Best Paper Award

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Yufan Song | Engineering | Best Paper Award

Dr. Yufan Song, Nanjing University of Aeronautics and Astronautics, China

Yufan Song, born in 1999 in Hebei, China, is a Ph.D. student specializing in Information and Communication Engineering at Nanjing University of Aeronautics and Astronautics (NUAA). With a strong academic foundation from the University of Electronic Science and Technology of China (UESTC), she has swiftly become a rising researcher in the field of synthetic aperture radar (SAR) and remote sensing image processing. Her work is driven by the ambition to push the boundaries of microwave imaging techniques and data interpretation from SAR platforms. Yufan’s research is marked by innovation and technical depth, leading to the publication of eight SCI-indexed journal articles and 14 patents. She holds memberships in prestigious professional organizations such as IEEE and CSIG. Through rigorous academic training and a passion for solving complex imaging challenges, Yufan continues to contribute significantly to advancements in SAR-based Earth observation technologies.

Publication Profile

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🎓 Education

Yufan Song commenced her academic journey at the University of Electronic Science and Technology of China (UESTC), Chengdu, where she earned her Bachelor’s degree from the College of Information and Communication Engineering in 2020. During her undergraduate studies, she developed a keen interest in signal processing and microwave technologies. Building on that foundation, she pursued doctoral studies at Nanjing University of Aeronautics and Astronautics (NUAA), where she is currently enrolled in the Ph.D. program in Information and Communication Engineering. Her education is marked by a consistent focus on research and development, particularly in advanced remote sensing technologies and synthetic aperture radar (SAR) systems. Throughout her academic path, Yufan has cultivated in-depth technical knowledge, hands-on experience with SAR data analysis, and expertise in image reconstruction, ambiguity suppression, and sparse signal processing. Her education reflects both strong theoretical grounding and applied research excellence.

💼 Experience

Yufan Song’s experience is anchored in academic research with a strong focus on microwave imaging and SAR technologies. As a Ph.D. student at NUAA, she has undertaken six significant research projects related to sparse imaging, SAR signal processing, and ambiguity reduction in sliding spotlight SAR systems. Her practical contributions include developing innovative algorithms for moving and stationary target separation, squint-mode SAR phase correction, and compressive sensing-based SAR imaging. With eight SCI-indexed journal publications and 14 patent submissions, her experience reflects both depth and breadth in remote sensing innovation. While she has not yet participated in industry consultancy projects, her academic research has strong potential for real-world applications in aerospace, defense, and environmental monitoring. Yufan is also an active member of professional societies including IEEE, CSIG, and the Chinese Institute of Electronics, where she stays updated with emerging technologies and research trends.

🏆 Honors and Awards

While formal award records are not explicitly listed, Yufan Song’s research achievements reflect distinguished academic excellence deserving of recognition. Her selection as a Best Paper Award nominee underscores the significance of her contributions to SAR imaging and remote sensing. Publishing in high-impact journals such as IEEE Transactions on Geoscience and Remote Sensing demonstrates peer-validated recognition of her work. In addition to her scientific publications, the acceptance and processing of 14 patents highlight her capacity for innovation and applied engineering. Furthermore, her active membership in leading academic societies—IEEE, CSIG, and the China Society of Image and Graphics—speaks to her standing in the research community. Her groundbreaking approach in azimuth ambiguity suppression using compressive sensing, especially in the context of PRF-reduced sliding spotlight SAR, is a notable milestone that reinforces her role as a promising young researcher. These accomplishments collectively position her as a strong contender for research-based awards.

🔬 Research Focus

Yufan Song’s research is centered on Synthetic Aperture Radar (SAR), Sparse Microwave Imaging, and Remote Sensing Image Processing. Her work explores high-resolution SAR imaging techniques with an emphasis on ambiguity suppression, phase error correction, and sparse signal reconstruction. She has developed algorithms capable of separating moving and stationary targets in complex imaging scenes. One of her key innovations involves a joint sparse imaging model for spaceborne PRF-reduced sliding spotlight SAR, which incorporates compressive sensing to manage azimuth ambiguity—a challenge that significantly affects image clarity and accuracy. Her research blends mathematical rigor with practical application, particularly in spaceborne imaging platforms. With a growing number of journal articles and patents, she aims to enhance the reliability and efficiency of remote sensing systems, making significant contributions to environmental monitoring, surveillance, and Earth observation technologies. Her focus is not only on developing theoretical frameworks but also ensuring these solutions are scalable and applicable in real-world scenarios.

📚 Publications

  • 📄 A Compressive Sensing-Based Sparse Imaging Method for PRF-Reduced Sliding Spotlight SAR

  • 📄 Separation of Moving and Stationary Targets in SAR via Doppler Parameter Estimation

  • 📄 Squint-Mode SAR Imaging Based on Azimuth Phase Error Correction and Sparse Reconstruction

  • 📄 Joint Imaging Model for Azimuth Ambiguity Suppression in Compressive Sensing SAR Systems

  • 📄 Phase Error Estimation Using Gradient Descent for Sliding Spotlight SAR

  • 📄 Sparse Reconstruction-Based Image Enhancement for Remote Sensing Scenes

  • 📄 Azimuth Time-Domain Compensation Method in Squint SAR Imaging

  • 📄 An Improved Sparse Microwave Imaging Algorithm for Spaceborne SAR Applications

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

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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

Hamna Baig | Engineering | Young Researcher Award

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Hamna Baig | Engineering | Young Researcher Award

Ms. Hamna Baig, COMSATS University Islamabad, Attock Campus, Pakistan

Hamna Baig is a passionate and accomplished Electrical Engineering graduate from COMSATS University Islamabad, Attock Campus. A Gold Medalist with a stellar CGPA of 3.66/4, she blends academic brilliance with innovation and creativity. Her work spans artificial intelligence, robotics, and smart systems—areas where she has made significant strides through hands-on projects, impactful research, and active involvement in technical writing. Hamna’s proactive participation in conferences, internships, and AI-based research projects has not only sharpened her technical expertise but also highlighted her commitment to using technology for social and environmental betterment. Adept in Python, MATLAB, LabVIEW, and embedded systems, she continues to evolve in her pursuit of excellence. Fluent in English, Urdu, and Punjabi, Hamna is driven by her curiosity, resilience, and desire to solve real-world problems through sustainable technology and intelligent systems. She is currently engaged in research and technical writing, aiming to make a lasting impact in the field.

Publication Profile

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Education

Hamna Baig completed her Bachelor of Science in Electrical Engineering from COMSATS University Islamabad, Attock Campus (2020–2024), graduating with distinction and securing a Gold Medal. Her final CGPA of 3.66/4 (91.5%) reflects her unwavering dedication and academic rigor. During her studies, she actively explored artificial intelligence, robotics, and embedded systems, with her thesis titled: “Enhancing Home Comfort with an Artificial Intelligence-based Environmental Control Model”. Hamna supplemented her academic journey with multiple certified online courses, including Machine Learning Specialization and Generative AI for Everyone offered by Stanford University via Coursera. Her technical training spans MATLAB, LabVIEW, Arduino, KEIL, Proteus, and microcontroller-based systems, showcasing both breadth and depth. Driven by curiosity and innovation, Hamna transformed theoretical knowledge into practical, real-world solutions through capstone projects and internships. Her continuous pursuit of learning makes her a standout in the evolving field of intelligent systems and energy-efficient technologies.

Experience

Hamna Baig has gained diverse experience through internships, research positions, and technical writing roles. She is currently an Internee at the Department of Electrical and Computer Engineering, COMSATS University Islamabad under the PEC GIT program, where she supports research on intelligent systems. Previously, she interned at the Ghazi-Barotha Hydro Power Plant (WAPDA) in 2023, gaining field exposure to power systems and operational technologies. Additionally, she works as a Technical Writer (Electrical & Electronics) with CDR Professionals, where she contributes research-based content and technical documentation. Hamna’s practical expertise includes projects in AI-driven sensing systems, robotic control, and smart energy applications. Her collaborative work on software-defined RF sensing and machine learning models demonstrates her ability to blend theoretical knowledge with real-time implementation. From smart home innovations to robotic arms and biomedical sensing, Hamna has exhibited both vision and versatility, positioning herself as a promising young engineer in AI, robotics, and embedded control.

Awards and Honors

Hamna Baig has been recognized for her academic excellence, research presentations, and contributions to intelligent systems. She earned a Gold Medal for outstanding academic performance during her Bachelor’s degree. She received Certificates of Gratitude for presenting papers at major conferences including the International Conference on Innovations in Computing Technologies (UET Peshawar), ICCSI (University of Haripur), and ICCIS (Kohat University). Her research presentations on AI-based fan control, robotic fruit harvesting, and end effector position estimation have been acknowledged for their innovation and technical depth. Additionally, she earned certifications from Coursera in prestigious Stanford-offered courses like Machine Learning Specialization and Generative AI for Everyone, showcasing her commitment to continuous learning. Her accolades reflect her dedication to cutting-edge research and meaningful contributions to the engineering community. These awards and recognitions not only celebrate her achievements but also affirm her potential as a leading innovator in AI-driven electrical and robotic systems.

Research Focus

Hamna Baig’s research is centered around Artificial Intelligence, Machine Learning, Robotics, and Wireless Sensing Systems. Her projects emphasize the application of deep learning and AI models for real-world problem-solving, particularly in healthcare monitoring, smart energy systems, and precision robotics. She has developed RF sensing platforms for gait monitoring in Parkinson’s patients, designed AI-based systems for environmental control, and contributed to machine learning-driven robotic arm control for fruit harvesting and biopsy systems. Hamna’s work also explores adaptive fan control for residential energy efficiency and wireless sensing to prevent bedsores, reflecting her commitment to tech-driven well-being. With a blend of academic rigor and engineering intuition, she is passionate about pushing the boundaries of intelligent systems to improve quality of life. Hamna continues to refine her skills in AI integration with embedded hardware, and her ongoing research contributes to the advancement of energy-aware, health-supportive, and human-centric technologies.

Publication Top Notes

  • 📘 Intelligent Frozen Gait Monitoring using Software Defined Radio Frequency Sensing – Electronics (2025)

  • 🤖 Machine Learning-Based Estimation of End Effector Position in Three-Dimension Robotic Workspace – IJIST Journal (2024)

  • 🍊 A Robotic Approach for Fruit Harvesting with Machine Learning based Joint Angles Prediction – ICCSI Conference (2024)

  • 🌬️ Artificial Intelligence based Adaptive Fan Control in Office Settings for Energy Efficiency – ICCIS Conference / Springer (2024)

  • 🦾 A Robotic Arm Based Intelligent Biopsy System – ICCIS Conference / Springer (2024)

  • 🛏️ Design of an Intelligent Wireless Channel State Information Sensing System to Prevent Bedsores – IEEE Sensors (Under Review)

  • 🏠 Enhancing Home Comfort and Energy Consumption with an AI-based Environmental Sensing Control Model – PeerJ (Under Review)

  • 🌬️ Breathing Techniques Redefined: Pros and Cons of Traditional Methods & the Promise of SDRF Sensing – Elsevier, Digital Communications and Networks (Under Review)

Ibna Kawsar | Engineering | Excellence in Citation Achievement Award

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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)

Oguzhan Yilmaz | Engineering | Best Researcher Award

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Oguzhan Yilmaz | Engineering | Best Researcher Award

Prof. Dr Oguzhan Yilmaz, Gazi University, Turkey

Professor Oğuzhan Yılmaz is a distinguished mechanical engineering expert specializing in machine elements, computer-aided design and manufacturing, and non-traditional manufacturing methods. He is a professor at Gazi University, Turkey, contributing extensively to research and education in advanced manufacturing. He completed his doctorate at the University of Nottingham, UK, further enhancing his expertise in manufacturing engineering and operations management. With a career spanning over two decades, he has held editorial roles in prestigious scientific journals and actively participates in peer reviewing for high-impact publications. His research focuses on innovative and sustainable manufacturing techniques, integrating modern computational tools into engineering solutions. Prof. Yılmaz has received multiple awards for his contributions to research, peer reviewing, and academic leadership. He continues to influence the global engineering community through his editorial work, research collaborations, and mentorship of future engineers. His dedication to advancing mechanical engineering makes him a key figure in the field.

Publication Profile

google scholar

Education

Professor Oğuzhan Yılmaz holds a Doctorate (2002-2006) from the University of Nottingham, UK, where he specialized in Manufacturing Engineering and Operations Management, focusing on advanced production techniques. He completed his Postgraduate studies (1997-1999) at Gaziantep University, Turkey, in the Faculty of Engineering, Department of Mechanical Engineering (English), where he specialized in mechanical system design and material processing. His academic journey began with a Bachelor’s degree (1992-1997) from the same institution, where he built a strong foundation in mechanical systems, machine elements, and computational engineering. With a career spanning international institutions and advanced research in manufacturing and mechanical design, he has demonstrated a strong commitment to innovation, sustainability, and technological advancements in mechanical engineering. His diverse educational background has equipped him with the expertise to contribute significantly to the field of advanced manufacturing and engineering solutions.

Experience

Professor Oğuzhan Yılmaz is a distinguished faculty member at Gazi University, Turkey, where he leads research and teaches courses in mechanical design, manufacturing, and computational engineering. His expertise extends beyond academia, as he plays a significant role in the scientific publishing community, holding editorial positions in SCI-indexed journals, including the Journal of Materials Processing Technology and the International Journal of Advanced Manufacturing Technology. Since 2021, he has been a committee member for the Journal of Additive Manufacturing Technology, contributing to advancements in additive and digital manufacturing. He has also served as Assistant Editor/Section Editor (2017-Present) for Makina Tasarım ve İmalat Dergisi and as First Editor (2015-Present) for the Journal of the Faculty of Engineering and Architecture of Gazi University. Additionally, he collaborates with international institutions to drive innovation in manufacturing technologies and automation, further cementing his influence in the modern engineering landscape.

Awards & Honors

Professor Oğuzhan Yılmaz has received numerous accolades for his outstanding contributions to engineering research, particularly in mechanical design and advanced manufacturing. He has been honored with the Outstanding Contribution to Engineering Research Award for his pioneering studies that have significantly influenced the field. His dedication to academic publishing and peer review has earned him the Top Reviewer Award, recognizing his excellence in evaluating manuscripts for leading SCI-indexed journals. Additionally, he has received the Editorial Excellence Award for his significant contributions to journal editing and manuscript evaluation. His innovative research has been acknowledged with the Best Research Paper Award, highlighting his groundbreaking work in manufacturing technologies. As a dedicated educator, he has also been recognized with the Distinguished Faculty Award, celebrating his exceptional teaching, mentorship, and academic leadership. His achievements underscore his commitment to research innovation, scholarly contributions, and academic excellence in mechanical engineering.

Research Focus

Professor Oğuzhan Yılmaz’s research spans several critical areas in mechanical and manufacturing engineering, with a strong emphasis on innovation and sustainability. His expertise in Machine Elements involves the advanced design and analysis of mechanical components for industrial applications, optimizing performance and durability. He is also deeply involved in Computer-Aided Design and Manufacturing (CAD/CAM), where he integrates software tools to enhance precision engineering and automation. His work in Non-Traditional Manufacturing Methods explores innovative fabrication techniques beyond conventional machining, pushing the boundaries of modern engineering. Additionally, his research in Advanced Manufacturing Technologies focuses on high-precision, cost-effective production methodologies that drive industrial efficiency. With a commitment to Sustainable Engineering Solutions, he develops environmentally friendly and energy-efficient manufacturing processes. His research aims to redefine modern manufacturing by seamlessly integrating automation, sustainability, and precision engineering to meet the evolving demands of the industry.

Publication Top Notes

📜Wire Arc Additive Manufacturing (Metal Inert Gas-Cold Metal Transfer) of ER70S-6: Experimental and Computational Analysis on Process, Microstructure, and Mechanical Property Relationships
🔥 Thermal Behavior in Wire Arc Additive Manufacturing: A Comparative Study of the Conventional Process and Infrared Heater Use
🔬 Surface Characteristics of Additively Manufactured γ-TiAl Intermetallic Alloys Post-Processed by Electrochemical Machining
⚙️ Directed Energy Deposition of PH 13–8Mo Stainless Steel: Microstructure and Mechanical Property Analysis
💡 Enhancement of Surface Characteristics of Additively Manufactured γ-TiAl and IN939 Alloys after Laser Shock Processing
🛠️ Influence of Laser Polishing Process Parameters on Surface Integrity and Morphology of Ti-6Al-4V Parts Produced via Electron Beam Melting
🔍 Electrochemical Machining of Additively Manufactured γ-TiAl Parts: Post-Processing Technique to Reduce Surface Roughness
📏 A Deposition Strategy for Wire Arc Additive Manufacturing Based on Temperature Variance Analysis to Minimize Overflow and Distortion
🔥 The Effect of Evaporation and Recoil Pressure on Energy Loss and Melt Pool Profile in Selective Electron Beam Melting
🧪 Computational Evaluation of Temperature-Dependent Microstructural Transformations of Ti-6Al-4V for Laser Powder Bed Fusion Process
🔬 Micromechanical Characterization of Additively Manufactured Ti-6Al-4V Parts Produced by Electron Beam Melting
🌡️ Volumetric Heat Source Model for Laser-Based Powder Bed Fusion Process in Additive Manufacturing
📐 Radially Graded Porous Structure Design for Laser Powder Bed Fusion Additive Manufacturing of Ti-6Al-4V Alloy
💎 Surface Characteristics of Laser Polished Ti-6Al-4V Parts Produced by Electron Beam Melting Additive Manufacturing Process
🛠️ Wire Arc Additive Manufacturing of High-Strength Low Alloy Steels: Study of Process Parameters and Their Influence on the Bead Geometry and Mechanical Characteristics

Ismail Fidan | Engineering | Innovative Research Award

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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

orcid

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) 🔥