Prof. Dr. Rasool Baghbani | Biomedical Sensors | Excellence in Research Award
Hamedan University of Technology | Iran
Rasool Baghbani is a dedicated biomedical engineering scholar and faculty member at Hamedan University of Technology whose work bridges advanced engineering with clinical innovation through the development of intelligent medical devices, embedded microsystems, bioimpedance technologies, and IoMT solutions. His academic background spans electrical engineering, biomedical instrumentation, and bioelectrics, culminating in doctoral research focused on bioimpedance-based lung cancer diagnostics, which led to multiple scientific publications and validated methods for intraoperative assessment. His professional experience includes academic teaching, supervising graduate research, leading departmental initiatives, and contributing to national evaluation of medical equipment in alignment with international safety and performance standards. His research interests encompass biomedical sensors, firmware programming, biophysical signal analysis, medical robotics, bioelectromagnetics, and machine learning for health applications, supported by strong skills in Python, C++, MATLAB, microcontroller programming, PCB design, COMSOL modelling, laboratory instrumentation, and hardware prototyping. His achievements include multiple recognitions in teaching, research excellence, peer-review service for leading journals, and patents in medical technology. Through his interdisciplinary expertise and sustained commitment to innovation, he continues to advance biomedical engineering by designing practical, patient-centered solutions while inspiring future researchers, ultimately aiming to elevate healthcare through technology-driven problem solving.
Baghbani, R., Rad, M. A., & Pourziad, A. (2015). Microwave sensor for non-invasive glucose measurements: Design and implementation of a novel linear method. IET Wireless Sensor Systems, 5(2), 51–57. Citations: 58
Hamouleh-Alipour, A., Forouzeshfard, M., Baghbani, R., & Vafapour, Z. (2022). Blood hemoglobin concentration sensing by optical nano biosensor-based plasmonic metasurface: A feasibility study. IEEE Transactions on Nanotechnology, 1–8. Citations: 49
Baghbani, R., Shadmehr, M. B., Ashoorirad, M., Molaeezadeh, S. F., & Moradi, M. H. (2021). Bioimpedance spectroscopy measurement and classification of lung tissue to identify pulmonary nodules. IEEE Transactions on Instrumentation and Measurement, 70, 1–7. Citations: 45
Alipour, A. H., Khani, S., Ashoorirad, M., & Baghbani, R. (2023). Trapped multimodal resonance in magnetic field enhancement and sensitive THz plasmon sensor for toxic materials accusation. IEEE Sensors Journal, 23(13), 14057–14066. Citations: 35
Assist. Prof. Dr. Beibei Wang | Innovative Materials Design | Best Researcher Award
School of Art and Design | China
Beibei Wang is an accomplished associate professor and master supervisor at Zhejiang Sci-Tech University, recognized for her dynamic work in engineering, sustainable materials and design innovation. She holds a doctoral degree in engineering and has built a strong academic foundation in advanced material development and biomass-based functional materials. Her professional experience spans university teaching, project leadership and active participation in academic societies, with notable involvement in scientific research foundations, curriculum reform initiatives and collaborations integrating artificial intelligence with product design education. Her research interests focus on innovative materials, nanocellulose-based energy storage systems, flexible supercapacitors, virtual reality–empowered design education and sustainable composites. Skilled in experimental materials synthesis, structural characterization, energy storage mechanism analysis, flame-retardant materials development and interdisciplinary design research, she has authored numerous indexed publications, secured patents and guided students toward competitive achievements. Her awards and honors include recognition for innovative patent development, leadership in curriculum reform, successful mentorship outcomes and active roles in professional associations within the forestry and design sectors. Overall, her career reflects a commitment to advancing green materials research, promoting the integration of technology and design, strengthening industry-academia collaboration and contributing meaningfully to the future of sustainable engineering and educational innovation.
Beibei Wang, Weiye Zhang, Cenhuan Lai, Yi Liu, Hongwu Guo, Daihui Zhang, Zanhu Guo, Facile Design of Flexible, Strong, and Highly Conductive MXene-Based Composite Films for Multifunctional Applications. Small, 2023, 19, 2302335.
Beibei Wang, Weiye Zhang, Jingmeng Sun, Chenhuan Lai, Shengbo Ge, Hongwu Guo, Yi Liu, Daihui Zhang. A micro/nano multiscale hierarchical structure strategy to fabricate highly conducting films for electromagnetic interference shielding and energy storage[J]. Journal of Materials Chemistry A, 2023,11, 8656-8669.
Wang Beibei, Li Yanchen, Zhang Weiye, Sun Jingmeng, Zhao Junqi, Xu Yuzhi, Liu Yi, Guo Hongwu, Zhang Daihui. Ultrathin cellulose nanofiber/carbon nanotube/Ti3C2Tx film for electromagnetic interference shielding and energy storage[J]. Carbohydrate Polymers, 2022,286,119302.
Dr. Hong Wang is an accomplished Associate Professor at Hebei University, China, specializing in the field of neuromorphic electronics and low-dimensional ferroelectric materials. With a strong academic foundation in Physics, Integrated Circuits, and Optical Engineering, she has rapidly advanced in her field since earning her doctorate in 2021. Her research has led to 15 SCI-indexed publications as a first author, 8 patents, and over 1300 citations, underscoring her scientific impact. Dr. Wang actively collaborates with leading researchers from institutions such as the National University of Singapore, the Chinese Academy of Sciences, and Jilin University, achieving multiple experimental firsts in ferroelectricity and memristor behavior. Her innovative work bridges material science and cognitive computing, making significant contributions to optoelectronic sensing and neuromorphic systems. She is a member of several prestigious scientific societies, including the Chinese Optical Society. Dr. Wang’s dedication and research excellence make her a standout in cognitive science innovations.
Dr. Hong Wang’s academic journey began with a Bachelor’s degree in Physics from Beihua University in 2016, which laid the foundation for her interdisciplinary approach to electronic materials. She then earned her Master’s degree in Integrated Circuits from Hebei University in 2018, further refining her expertise in semiconductor and electronic system design. Driven by a passion for optical and neuromorphic technologies, she pursued a PhD in Optical Engineering at Hebei University, completing it in 2021. Her doctoral research focused on the application of low-dimensional ferroelectric materials, contributing valuable insight into the behavior of memristive systems and their implications for artificial neural networks. This strong educational background has enabled her to explore innovative technologies in cognitive sensing and computing, bridging physics, materials science, and neural engineering. Her academic training not only exemplifies depth and rigor but also reflects a unique ability to translate theoretical research into applied cognitive systems.
🧪 Experience
Since 2021, Dr. Hong Wang has served as an Associate Professor at the School of Electronic Information and Engineering, Hebei University. In this role, she has taken on responsibilities spanning research leadership, mentoring graduate students, and leading interdisciplinary projects at the frontier of neuromorphic computing. She has directed five major research projects and collaborated internationally with scholars from Singapore, the Chinese Academy of Sciences, and Jilin University. Her work has provided novel insights into ferroelectricity in materials like SnSe and ReSe₂, and its application in memristive devices. In addition to her academic duties, Dr. Wang has contributed to two industry consultancy projects, aligning academic innovation with technological advancement. Her ability to bridge material innovation with neural system architecture distinguishes her as a versatile and future-oriented cognitive scientist. Her professional experience is marked by innovation, collaboration, and a commitment to enhancing cognitive systems through novel material applications.
🏅 Awards and Honors
While specific awards are not explicitly listed, Dr. Hong Wang’s impressive research metrics and collaborations signify her recognition within the global scientific community. With 15 SCI-indexed publications as first author and over 1365 citations, her work has garnered significant academic attention. Her successful collaborations with leading institutions like the National University of Singapore and the Chinese Academy of Sciences validate her contributions through groundbreaking experimental confirmations in ferroelectric behavior. Additionally, she holds 8 patents, reflecting the originality and applied potential of her research in neuromorphic computing. Her memberships in the Chinese Optical Society, the Chinese Institute of Electronics, and the Chinese Society for Optical Engineering indicate peer recognition and professional trust. These accomplishments, coupled with her high-impact research output, suggest that Dr. Wang is a strong contender for prestigious awards in cognitive science and materials research, and she is an exemplary nominee for the Best Researcher Award in Cognitive Science.
🔬 Research Focus
Dr. Hong Wang’s research centers on the design and application of neuromorphic memristors using low-dimensional ferroelectric materials. She explores how novel quantum dots and two-dimensional semiconductors, such as SnSe and ReSe₂, can mimic synaptic behavior for brain-like computing. A notable achievement includes her demonstration of robust dual-mode optical sensing using ferroelectric quantum dots, enabling both short-range and remote synapse-like responses, leading to high-accuracy image recognition systems. Her experimental work debunks traditional notions in electronics, such as the inertness of Pd electrodes, and provides novel insights into conductive filament formation. Her research has practical implications in artificial vision systems, optoelectronic sensing, and cognitive learning circuits. She is pioneering the application of ferroelectric polarization for neuromorphic behavior, with implications for smart sensing and adaptive cognitive devices. Through multidisciplinary collaborations and material innovations, Dr. Wang is shaping the future of neuromorphic computing, advancing cognitive technologies toward higher efficiency and closer brain mimicry.
✅ Conclusion
Dr. Hong Wang is an emerging leader in neuromorphic computing, merging ferroelectric material innovation with cognitive system design, making her a strong candidate for the Best Researcher Award.
Publications
Real-time monitoring and early warning neuromorphic system based on high-endurance three-mode sensing memristors