Yinhui Li | Materials Physics | Best Researcher Award

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Assist Prof Dr. Yinhui Li | Materials Physics | Best Researcher Award

Supervisor, Taiyuan University of Technology, China.

Yinhui Li is an Assistant Professor at Taiyuan University of Technology, specializing in Material Physics and Chemistry. With a solid academic foundation and numerous contributions to piezoelectric sensors and nanocomposite materials, Yinhui’s innovative work has earned recognition in the scientific community. His research focuses on cutting-edge advancements in wearable technology and flexible electronics.

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Education 🎓

Ph.D. in Material Physics and Chemistry (2015-2018): Yinhui Li earned his doctoral degree from the University of Chinese Academy of Sciences in Beijing, China, where he specialized in Material Physics and Chemistry, focusing on advanced materials research. M.Sc. in Chemical Engineering and Technology (2012-2015): Prior to his Ph.D., he completed a Master’s degree at Taiyuan University of Technology in Shanxi, China, honing his expertise in chemical engineering and technology. B.Sc. in Chemistry (2008-2012): Li began his academic journey with a Bachelor’s degree in Chemistry from Hebei Normal University of Science & Technology, laying the foundation for his future research in materials science.

Experience 💼

Dr. Yinhui Li has been an Assistant Professor at Taiyuan University of Technology since completing his Ph.D. His expertise lies in flexible piezoelectric devices and carbon nanocomposite materials. He has led various research projects on developing piezoelectric sensors for wearable technologies and has actively contributed to his university’s Double First Class Initiative.

Research Interest ⚙️

Piezoelectric Sensors and Nanogenerators: Yinhui Li’s research centers on enhancing the performance of piezoelectric devices, focusing on energy harvesting and sensing applications. Carbon Nanocomposite Materials: He explores the integration of carbon nanomaterials to improve the mechanical and electrical properties of devices, making them more efficient and versatile. Wearable Smart Technology: Li is also dedicated to advancing wearable technologies, developing flexible, energy-efficient systems for health monitoring and communication. Flexible Electronics: His work in flexible electronics seeks to create bendable, durable devices that can be seamlessly integrated into everyday objects, offering greater functionality and user convenience.

Awards 🏅

Shanxi Province Science Foundation for Youths.

Numerous invention patents related to piezoelectric sensors and flexible nanogenerators.

Publications Top Notes 📚

High-temperature flexible electric Piezo/pyroelectric bifunctional sensor with excellent output performance – Nano Energy, 2024, cited by 6 articles. Link

High-performance piezoelectric nanogenerators based on hierarchical ZnO@CF/PVDF composite film for self-powered meteorological sensor – Journal of Materials Chemistry A, 2023. Link

Flexible Piezoelectric and Pyroelectric Nanogenerators Based on PAN/TMAB Nanocomposite Fiber Mats for Self-Power Multifunctional Sensors – ACS Applied Materials & Interfaces, 2022. Link

Enhanced Piezoelectric Performance of Multi-layered Flexible PVDF-BaTiO3-rGO Films for Monitoring Human Body Motions – Journal of Materials Science: Materials in Electronics, 2022. Link

Multi-layered BTO/PVDF Nanogenerator with Highly Enhanced Performance Induced by Interlaminar Electric Field – Microelectronic Engineering, 2021. Cited by: 22 articles. Link

 

 

 

Haijun Bao | Urban Management | Best Scholar Award

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Prof. Haijun Bao | Urban Management | Best Scholar Award

Dean, Hangzhou City University, China.

Haijun Bao is the Dean of the Faculty of Spatial Planning and Design at Hangzhou City University. With over two decades of experience in land management and spatial planning, he is recognized for his contributions to urban-rural planning and public policy. His leadership in the academic and government sectors has led to innovations in low-carbon planning and sustainable development, making him a leading voice in the field.

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Education🎓

Prof. Haijun Bao holds a Ph.D. in Land Management from Zhejiang University, where he studied from 1996 to 2005. In 2004, he participated in a co-training Ph.D. program in Real Estate Management at Hong Kong Polytechnic University, enhancing his expertise in the field. Furthering his academic experience, Prof. Bao was a Visiting Scholar at the University of Cambridge from 2011 to 2012, where he expanded his research and engaged with leading global scholars in land and real estate management. His diverse academic background equips him with a broad and deep understanding of land and real estate management principles.

Experience👨‍🏫

Prof. Haijun Bao has an extensive academic and professional background, currently serving as the Dean of the Faculty of Spatial Planning and Design at Hangzhou City University, a position he has held since 2021. Prior to this, he was the Vice Director at the Zhejiang Provincial Natural Resources Department from 2020 to 2021, where he contributed to provincial resource management and policy development. From 2010 to 2015, he was the Assistant Dean at the Institute of Land and Urban-Rural Development at Zhejiang University of Finance and Economics, focusing on land management and urban planning. He also held the role of Section Chief of the Human Resources Office at the same university from 2016 to 2020, overseeing personnel management and organizational development.

Research Interests🔬

Prof. Haijun Bao’s research focuses on public policy and spatial governance, with a strong emphasis on smart urban-rural planning and low-carbon development. His work explores innovative approaches to balancing sustainability with urbanization, aiming to create resilient, eco-friendly urban environments. Through his research, Prof. Bao seeks to bridge the gap between sustainable development practices and the challenges posed by rapid urban growth, contributing to the development of greener, more adaptable cities and rural areas.

Awards 🏆

Haijun Bao has been recognized as one of the Leading Talents in the Ministry of Natural Resources’ High-Level Scientific and Technological Innovation Talent Project. He is also a key member of Zhejiang’s Ten Thousand People Plan for Scientific and Technological Innovation and has been awarded the 151 Talent Project of Zhejiang Province.

Publications Top Notes 📚

Correction Factor for Mitigating the ‘One-Size-Fits-All’ Phenomenon in Assessing Low-Carbon City Performance Land (2024). link

An Empirical Study on the Mismatch Phenomenon in Utilizing Urban Land Resources in China Land (2023). link

How Can Urban Regeneration Reduce Carbon Emissions? A Bibliometric Review Land (2023). link

Strategies for Sustainable Urban Development—Addressing the Challenges of the 21st Century Buildings (2023). link

“Strategies for Sustainable Urban Development—Addressing the Challenges of the 21st Century” published in Buildings in March (2023). link

 

 

 

 

 

Haowei Zhang | Engineering | Best Researcher Award

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Dr. Haowei Zhang | Engineering | Best Researcher Award

Ph.D student, The University of Hong Kong, Hong Kong.

👨‍🔬 Haowei Zhang is a dynamic researcher specializing in structural health monitoring, concrete structure damage detection, and computer vision-based bridge Weight-In-Motion (WIM) systems. With a Ph.D. in progress at The University of Hong Kong, he has made significant contributions through cutting-edge research and impactful publications in top-tier journals. Haowei’s work spans deep learning, machine learning, and advanced imaging techniques for infrastructure health assessment, making him a standout researcher in civil engineering.

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Education 🎓

Dr. Haowei Zhang is a current Ph.D. student in Civil Engineering at The University of Hong Kong, under the supervision of Prof. Ray Kai Leung Su. His doctoral research builds on his expertise in bridge safety performance and vehicle non-contact weigh-in-motion (WIM) technology. He holds a Master’s degree in Civil Engineering from Southeast University, where he focused on the safety performance of bridges, supervised by Prof. Gang Wu and Prof. Kang Gao. Prior to that, he earned his Bachelor’s degree from Northeastern University in China, with a thesis on experimental building design supervised by Prof. Zhechao Wang. During his undergraduate studies, he also attended a summer training program at the University of Oxford, where he explored micromechanics and its applications in liquid metal 3D printing.

Experience 💼

Dr. Haowei Zhang is currently pursuing a Ph.D. in Civil Engineering at The University of Hong Kong, supervised by Prof. Ray Kai Leung Su. He holds a Master’s degree in Civil Engineering from Southeast University, where his research focused on vehicle non-contact weigh-in-motion (WIM) technology and the safety performance of bridges. Additionally, he earned his Bachelor’s degree from Northeastern University, specializing in experimental building design.

Professionally, Dr. Zhang serves as a Junior Researcher at Dongqu Intelligent Transportation Infrastructure Technology (2023-present), where he contributes to the development of computer vision models and equipment for transportation infrastructure. He has also led research projects on bridge monitoring, concrete structure damage detection, and deep learning algorithms for weight identification. During his master’s studies, he worked as a part-time college psychological counselor at Southeast University, providing psychological support and managing data files for graduate students.

His work uniquely combines civil engineering, intelligent transportation systems, and mental health advocacy.

Research Interests 🔬

Haowei Zhang’s research interests lie in structural health monitoring, computer vision-based WIM systems, deep learning, machine learning applications in civil engineering, and non-contact vehicle weight identification. His work focuses on developing innovative solutions for monitoring the integrity of concrete structures and enhancing safety through advanced image processing and data analysis.

Awards 🏆

International Exhibition of Inventions of Geneva – Silver Prize (2024)
Honor of Individual Academic Innovation – Southeast University (2023)
First-Class Academic Scholarship – Southeast University (2021)
Outstanding Undergraduate Student of Liaoning Province (2021)
National Scholarship (2020)

Publications Top Notes 📄

Automatic crack detection on concrete and asphalt surfaces using semantic segmentation network with hierarchical Transformer, Engineering Structures, 2023 Cited by: 45. link

Non-contact vehicle weight identification method based on explainable machine learning models and computer vision, Journal of Civil Structural Health Monitoring, 2023 Cited by: 20. link

Fully decouple convolutional network for damage detection of rebars in RC beams, Engineering Structures, 2023 Cited by: 25. link

A machine learning and game theory-based approach for predicting creep behavior of recycled aggregate concrete, Case Studies in Construction Materials, 2022 Cited by: 35. link

 

 

 

 

 

 

Manisha Kasar | Artificial Intelligence | Best Researcher Award

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Dr. Manisha Kasar | Artificial Intelligence | Best Researcher Award

Assistant Professor, Bharati Vidyapeeth Deemed to be University College of engineering, Pune, India.

Dr. Manisha M. Kasar is an accomplished researcher and educator in the field of computer engineering, with over 11 years of experience. Her expertise spans facial recognition systems, artificial intelligence, and machine learning. She currently serves as an Assistant Professor at Bharti Vidyapeeth College of Engineering, Pune. Dr. Kasar has made significant contributions to the research community through her innovative work on emotion recognition, AI-based systems, and security applications. She is also the holder of several patents and has published numerous papers in prestigious journals.

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Education 🎓

Dr. Kasar holds a Ph.D. in Information Technology from Bharti Vidyapeeth University, Pune, completed under the VISVESVARAYA Ph.D. Scheme in 2021. She also earned her M.Tech in Computer Engineering from NMIMS in 2014, and a B.E. in Computer Engineering from NMU in 2009. Her strong academic foundation has been pivotal in her research achievements.

Experience 💼

With over 11 years of experience, Dr. Kasar is currently an Assistant Professor at Bharti Vidyapeeth College of Engineering, Pune. She has previously worked at Vishwakarma Institute of Information Technology and as a visiting faculty member at Bharti Vidyapeeth. Her teaching and administrative skills have been recognized through her roles in various academic institutions, and she has contributed to mentoring and guiding students in advanced technology research.

Research Interest 🔍

Dr. Kasar’s research interests include artificial intelligence, machine learning, computer vision, and security systems. Her work primarily focuses on the development of AI-based applications such as facial emotion recognition, gesture-controlled systems, and fraud detection. She is particularly interested in exploring how machine learning models can optimize real-world applications like security systems and video surveillance.

Awards & Patents 🏆

Dr. Kasar is the holder of two significant patents:

Smart Mirror System with Infrared Blaster.

A Method to Identify Suspicious Financial Transactions and Prevent Fraud.

Her innovative work in these areas showcases her commitment to practical problem-solving through technology.

Publications  📚

Kasar, M., “EmoSense: Pioneering Facial Emotion Recognition with Precision Through Model Optimization,” International Journal of Engineering, April 2024. Cited by 1 article. link

Kasar, M., “AI-based Real-time Hand Gesture-Controlled Virtual Mouse,” Australian Journal of Electrical and Electronics Engineering, 2024. Cited by 0 articles. link

Kasar, M., “Use of Convolutional Neural Network and SVM Classifiers for Traffic Signals Detection,” International Journal on Recent and Innovation Trends in Computing and Communication, 2023. Cited by 3 articles. link

 

 

 

 

 

 

Ming-Peng Zhuo | Smart Textile | Best Researcher Award

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Assoc Prof Dr. Ming-Peng Zhuo | Smart Textile | Best Researcher Award

Associate Professor, Soochow University, China

Ming-Peng Zhuo, born on February 15, 1990, in China, is currently an Associate Professor at Soochow University’s National Engineering Laboratory for Modern Silk and College of Textile and Clothing Engineering. With a solid background in materials science, he specializes in organic semiconductor materials and their optoelectronic applications. He has built a remarkable academic career, contributing significantly to the field through innovative research in nanomaterials and QLED technologies.

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Education 🎓

PhD in Materials Science & Engineering (2016-2019), Soochow University, Suzhou, China. Research focused on organic semiconductor materials and their optoelectronic application under Prof. Liang-Sheng Liao.

Master of Engineering in Materials Engineering (2014-2016), Nanchang University, China. Research centered on inorganic functional nanomaterials for energy and environmental applications under Prof. Wei-Fan Chen.

Bachelor of Science in Materials Physics (2010-2014), Nanchang University, China. Studied synthetic methodology for inorganic functional nanomaterials.

Experience 🏢

Ming-Peng Zhuo is currently an Associate Professor at Soochow University (since June 2022), where he works at the National Engineering Laboratory for Modern Silk and the College of Textile and Clothing Engineering. His role involves integrating cutting-edge research in nanomaterials and photonic applications into textile engineering, bridging traditional materials with modern technological advancements.

Before his current position, Zhuo served as a Postdoctoral Researcher at Soochow University from June 2019 to June 2022, working at the Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices. Under the supervision of renowned scholars Prof. Shuit-Tong Lee and Prof. Liang-Sheng Liao, he focused on the development of organic semiconductor materials. His postdoctoral work primarily centered on improving the performance and stability of organic devices, including OLEDs and QLEDs, contributing to advancements in carbon-based materials for optoelectronics and sustainable energy solutions.

Research Interests 🔬

Ming-Peng Zhuo’s research encompasses a broad range of topics within materials science and nanotechnology, with a particular focus on the precise self-assembly of organic micro-/nanostructures for advanced photonic applications. His work is notable for combining principles of chemistry, physics, and materials engineering to innovate in fields such as quantum dot light-emitting diodes (QLEDs), which hold promise for the next generation of display technologies due to their superior color purity and energy efficiency.

Zhuo is also deeply involved in the rational design of inorganic nanomaterials, where he develops materials with tailored properties for specific functions. His expertise extends into energy applications, where he explores how nanomaterials can be optimized for better energy storage, conversion, and harvesting systems. This includes photocatalysis, solar cells, and other technologies aimed at improving sustainability in energy consumption.

Furthermore, his research is applied to environmental challenges, leveraging nanotechnology to address pollution control and resource management. For example, he investigates the use of nanomaterials for water purification and air filtration, targeting the reduction of hazardous pollutants and enhancing environmental health.

Zhuo’s work often involves a highly interdisciplinary approach, merging concepts from nanophotonics, optoelectronics, and materials chemistry to push the boundaries of what’s possible in display technologies, sustainable energy solutions, and environmental remediation. His research is characterized by both experimental innovation and theoretical insights, contributing to the rapid advancement of nanoscience and its practical applications.

Awards 🏆

Recipient of various academic accolades for outstanding research in the field of materials science and engineering, especially in the development of quantum dot light-emitting diodes (QLEDs) and nanomaterials.

Publications Top Notes 📚

Zhuo, Ming-Peng, et al., Cascaded charge-transfer organic alloys for controlled hierarchical self-assembly, Matter, 2024, 7, 1. Cited by 15. link

Zhuo, Ming-Peng, et al., Vertical Phase-Engineering MoS2 Nanosheet Enhanced Textiles, ACS Nano, 2024, 18, 492-505. Cited by 10. link

Zhuo, Ming-Peng, et al., Hydrophilic 1T-WS2 Nanosheet Arrays for Hydroelectric Generation, Small, 2024, 2308527. Cited by 8.

 

 

 

 

 

Saike Yang | Energy | Best Researcher Award

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Dr. Saike Yang | Energy | Best Researcher Award

Postdoctoral researcher, State Grid Hebei Electric Power Research Institute, State Grid Hebei Electric Power Supply Co., Ltd., China

Dr. Saike Yang is a dedicated postdoctoral researcher at the State Grid Hebei Electric Power Research Institute, where his work focuses on enhancing the safety and reliability of power systems. With a strong academic foundation and innovative research in power cable insulation detection, Dr. Yang is making significant contributions to the field of electrical engineering.

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Education 🎓

Dr. Saike Yang was born in Hebei, China, in 1995. He earned his B.Sc. degree from North China Electric Power University in Baoding in 2017. He furthered his education by obtaining a Ph.D. from Xi’an Jiaotong University in 2022, where he specialized in power cable insulation testing and developed novel methodologies for non-destructive testing.

Experience 🛠️

Dr. Yang began his research career at the 54th Research Institute of China Electronic Technology Group Corporation from October 2022 to July 2023. He is currently a postdoctoral researcher at the State Grid Hebei Electric Power Co., Ltd., and Xi’an Jiaotong University. His experience in both academic and industrial research environments equips him with a unique perspective on the practical applications of his work.

Research Interests 🔍

Dr. Yang’s research interests lie in the field of power cable insulation detection. His work primarily focuses on developing advanced non-destructive testing methods to improve the safety and reliability of electrical power systems. His innovations include new voltage generators and fault detection technologies that minimize damage to power cables during testing.

Awards 🏆

Dr. Yang’s contributions to the field have been recognized through various awards and honors. His work on power cable insulation has garnered attention for its practical applications and significant impact on the reliability of electrical systems.

Publications Top Notes 📚

S. Yang, H. Li, P. Xu, et al. (2021). A Novel DAC Generator for PD Testing of MV Cable Insulation. IEEE Transactions on Power Delivery, 36(1), 499-501. Cited by: 50 articles. link

S. Yang, L. Wang, X. Guo, et al. (2021). Implementation of a Novel Very Low Frequency Cosine-Rectangular Voltage Generator for Insulation Testing of Power Cables. IEEE Transactions on Power Electronics, 36(7), 7679-7692. Cited by: 65 articles.

S. Yang, K. Zhao, L. Wang, et al. (2021). Development of the Accurate Localization of Partial Discharges in Medium-Voltage XLPE Cables Based on Pulse Reconstruction. IET Generation, Transmission & Distribution, 16(2), 193-203. Cited by: 30 articles.

S. Yang, X. Yue, J. Chen, et al. (2022). A Method to Improve the Efficiency of Onsite Damped AC Test of Medium-Voltage Cables. IEEE Transactions on Power Delivery, 37(4), 3424-3427. Cited by: 40 articles. link

 

 

 

 

 

Mohsen Choubani | Nanostructures | Best Researcher Award

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Assoc Prof Dr. Mohsen Choubani | Nanostructures | Best Researcher Award

Associate professor, Scientific Faculty of Monastir, Unversity of Monastir, Tunisia

Mohsen Choubani is an Associate Professor of Physics at the Scientific Faculty of Monastir (F.S.M), Tunisia, specializing in Micro-Opto-Electronic and Nanostructures. Born on September 17, 1971, in Mahdia, Tunisia, he has dedicated over 27 years to education and research. Choubani is married with four children and actively contributes to academic and scientific communities.

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Education 🎓  

Mohsen Choubani is an Associate Professor of Physics at F.S.M, Tunisia. He earned his Ph.D. in Physics in April 2011 with the distinction of “Very Honorable” from the Faculty of Sciences of Tunis. Prior to that, he completed a Thorough Studies Diploma (DEA) in Physics in December 1997 with a “Pretty Good” distinction at F.S.M, Tunisia. He also holds a Mastery in Physics, awarded in July 1995 with a “Pretty Good/Quite” distinction from the same institution. Mohsen began his academic journey with a Baccalaureate in Experimental Science, which he received in June 1991 from the High School of Ksour-essef, Mahdia.

Professional Experience 💼

Mohsen Choubani has a diverse and extensive teaching career. Since September 2022, he has been serving as an Associate Professor at the Faculty of Sciences of Monastir (F.S.M), Tunisia. Prior to this role, he was an Assistant Professor at F.S.M from September 2012 to July 2022, following his time as a Higher Education Assistant in September 2010. His career in education began as a Secondary School Teacher, a position he held from September 1997 to 2010. In addition to his full-time roles, Mohsen has experience as a Part-Time Teacher at both the Higher Institute of Computer Science of Mahdia (2006-2007) and F.S.M (1996-1997).

Research Interests 🔬

Modeling and Optimization of Non-linear Optical Properties in Quantum Dots, Quantum Rings, and Nano-Holes

The exploration of non-linear optical properties in quantum systems like quantum dots, quantum rings, and nano-holes (droplets) is pivotal for advancing photonics and optoelectronics. These quantum structures exhibit unique behaviors under varying electromagnetic fields, enabling the manipulation of light at the nanoscale. Modeling these properties involves complex computational techniques to optimize their performance in various applications, such as quantum computing, high-resolution imaging, and ultrafast communication technologies. By understanding and optimizing the interactions within these nanostructures, researchers can develop innovative solutions for next-generation optical devices.

Electromagnetic Modeling of Non-homogeneous Planar Structures, Photonic Crystals, and Electronic Transport through Semiconductor Barriers

In the realm of electromagnetic modeling, non-homogeneous planar structures, photonic crystals, and semiconductor barriers are critical components that shape the behavior of light and electronic transport at the microscopic level. Non-homogeneous planar structures, with their varying material properties, influence wave propagation in ways that can be harnessed for novel optical devices. Photonic crystals, with their periodic structures, allow for the control of light in unprecedented ways, leading to the development of highly efficient waveguides, sensors, and filters. Furthermore, understanding electronic transport through semiconductor barriers is essential for designing advanced electronic and optoelectronic components, including transistors, diodes, and quantum devices. Through meticulous modeling and analysis, these elements contribute to the cutting-edge development of technologies that rely on precise electromagnetic interactions.

Awards 🏆

Numerous acknowledgments for contributions to physics education and research

Publications Top Notes 📚

Benzerroug, N., & Choubani, M. (2024). Effects of hills, morphology, electromagnetic fields, temperature, pressure, and aluminum concentration on the second harmonic generation of GaAs/AlxGa1-xAs elliptical quantum rings. Results in Physics, 63, 107883. (Cited by: 1) link

Choubani, M., & Benzerroug, N. (2024). Design of a frequency multiplier based on laterally coupled quantum dots for optoelectronic device applications in the Tera-Hertz domain: Impact of inhomogeneous indium distribution, strains, pressure, temperature, and electric field. Journal of Electronic Materials, 53(25). (Cited by: 1) link

Benzerroug, N., Makhlouf, D., & Choubani, M. (2023). Pressure, temperature, and electric field effects on linear and nonlinear optical properties in InxGa1-xAs/GaAs strained quantum dots: under indium segregation and In/Ga intermixing phenomena. Physica B, 658, 414819. (Cited by: 3) link

Makhlouf, D., Benzerroug, N., & Choubani, M. (2023). Tailoring of the Nonlinear Optical Rectification in vertically and laterally coupled InxGa1-xAs/GaAs quantum dots for Tera-hertz applications: under In/Ga inter-diffusion, indium segregation, and strains effects. Results in Physics, 48, 106457. (Cited by: 2) link

Choubani, M., Maaref, H., & Saidi, F. (2022). Linear, third-order nonlinear and total absorption coefficients of a coupled InAs/GaAs lens-shaped core/shell quantum dots in terahertz region. European Physical Journal Plus, 137, 265. (Cited by: 5) link

 

 

 

 

 

Xiaochun Li | Biomedical | Best Researcher Award

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Prof Dr. Xiaochun Li | Biomedical | Best Researcher Award

Associate Dean, Taiyuan University of Technology, China

Dr. Xiaochun Li is a Professor at the Department of Biomedical Engineering, TaiYuan University of Technology, Shanxi, China. With an extensive background in biomedical sensors and analytical chemistry, Dr. Li has made significant contributions to the field through innovative research and teaching. He has received multiple awards for his work, including the Second Prize of the Shanxi Provincial Natural Science Award and recognition as the “2021 Annual Science and Technology Innovation Person.” His research focuses on developing cutting-edge technologies for disease diagnosis and public health.

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Education 🎓

Dr. Xiaochun Li earned his Ph.D. in Biomedical Engineering, specializing in analytical chemistry and sensor technology. His educational journey laid a strong foundation for his future research and academic career, leading to his current position as a professor at TaiYuan University of Technology.

Experience 🧑‍🏫

Professor, TaiYuan University of Technology, Shanxi, China (2014-present): Leading research in biomedical sensors and analytical chemistry.

Associate Professor, TaiYuan University of Technology, Shanxi, China (2009-2014): Conducted advanced research and taught various courses.

Assistant Professor, TaiYuan University of Technology, Shanxi, China (2007-2009): Initiated his academic career, focusing on innovative research in biomedical engineering.

Research Interests 🔬

Dr. Xiaochun Li’s research interests encompass the development of biomedical sensors, optical fluorescence detection technologies, and AI-enhanced biochemical sensing. His work is particularly focused on creating innovative diagnostic tools for early disease detection and public health applications.

Awards 🏆

Second Prize of Shanxi Provincial Natural Science Award (2022)

Outstanding Science and Technology Worker of China Society of Electronics (2019)

Silver Prize of National Science and Technology Workers’ Innovation and Entrepreneurship Competition (2016)

Young Outstanding Talents of Shanxi Province “Three Jin Talents” (2018)

2021 Annual Science and Technology Innovation Person (2022)

Publications Top Notes 📚

Zhang, L. L., Xu, P. T., Li, X. C., Yang, Z. H., Yu, H.-Z.. (2024). Blu-ray disc technology-enabled portable imaging system for immunoassay quantitation. Sens. Actuat. B-Chem., 419, 136376. Cited by 15 articles. link

Wang, C. X., Deng, R., Li, H. Q., Liu, Z. G., Niu, X. F., Li, X. C.. (2024). An integrated magnetic separation enzyme-linked colorimetric sensing platform for field detection of Escherichia coli O157: H7 in food. Microchimica Acta, 191, 454. Cited by 10 articles. link

Li, H. Q., Xu, H., Li, Y. L., Li, X. C.*. (2024). Application of artificial intelligence (AI)-enhanced biochemical sensing in molecular diagnosis and imaging analysis: Advancing and challenges. Trac-Trend. Anal. Chem., 174, 117700. Cited by 12 articles. link

 

 

 

 

 

Selma Ben Ftima | Hydraulics | Best Researcher Award

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Dr. Selma Ben Ftima | Hydraulics | Best Researcher Award

Doctor, UCLM, Spain

Dr. Selma Ben Ftima is a distinguished Industrial Electronics Engineer specializing in robotics and control systems. With a robust background in neural-network modeling and fractional-order control, she has made significant contributions to the field of robotics, particularly in the adaptive control of flexible link robots. Her innovative research has been published in several high-impact journals, earning her recognition within the scientific community.

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Education 🎓

Dr. Selma Ben Ftima is a dedicated researcher with a strong academic background in robotics and intelligent systems. She recently completed her Ph.D. in Robotics at the University of Castilla-La Mancha, Spain (Dec 2019 – Feb 2024), where her thesis focused on “Algebraic Identification and Adaptive Fractional-Order Control Applied to Very Lightweight Flexible Link Robots.” This work highlights her expertise in advanced control systems and robotics, particularly in the context of lightweight and flexible robotic structures.

Prior to her doctoral studies, Selma earned a Master of Science in Intelligent and Communicating Systems from the National Engineering School of Sousse, Tunisia (Oct 2017 – Jun 2018), specializing in Embedded Systems. Her academic journey began with a Diploma in Electronic Engineering with Honors from the same institution (Sep 2014 – Oct 2017), also specializing in Embedded Systems. Her educational background reflects a strong foundation in electronics and embedded systems, combined with specialized knowledge in robotics and control systems.

Experience 🛠️

Selma Ben Ftima has also gained valuable professional and teaching experience during her academic journey. She served as a University Teaching Assistant at the University of Sousse, Tunisia (Jan 2020 – Jun 2020), where she conducted laboratory sessions in signal processing and embedded systems. In this role, she focused on setting up experimental platforms and grading, providing hands-on learning experiences for students.

Before her teaching role, Selma worked as an Electrical Engineer at Rovex, Tunisia (Mar 2019 – Dec 2019). In this position, she coordinated electrical upgrades and managed supplier relations, ensuring the smooth operation of showroom equipment. Her ability to oversee technical upgrades and maintain essential equipment demonstrates her practical engineering skills.

During her time at the National Engineering School of Sousse, Tunisia (Sep 2014 – Jan 2017), Selma led various academic projects and internships. These included the development of a line-following robot and biometric facial recognition systems, showcasing her ability to apply theoretical knowledge to real-world challenges.

Research Interests 🔬

Dr. Ftima’s research interests lie in the fields of robotics, control systems, and signal processing. She focuses on the development of robust, optimal, and adaptive control systems for flexible link robots, fractional-order calculus, and neural-network-based modeling. Her work also extends to the practical implementation of these systems using advanced tools like MATLAB, LabVIEW, and NI hardware.

Awards 🏆

Dr. Ftima has consistently demonstrated academic excellence throughout her education and career. While she is still in the early stages of her professional journey, her work has been recognized through publications in peer-reviewed journals, showcasing her potential for future accolades in robotics and industrial electronics.

Publications Top Notes 📝

2023. Fractional Modeling and Control of Lightweight 1-DOF Flexible Robots Robust to Sensor Disturbances and Payload Changes, Fractal and Fractional Cited by: 15 articles. link

2022. A Fast Online Estimator of the Main Vibration Mode of Mechanisms from a Biased Slightly Damped Signal, IEEE Industrial Electronics Society Cited by: 12 articles. link

2021. Fractional Control of a Lightweight Single Link Flexible Robot Robust to Strain Gauge Sensor Disturbances and Payload Changes, Actuators Cited by: 20 articles. link

 

 

 

 

 

 

 

Shishir Priyadarshi | Space Physics | Best Researcher Award

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Dr. Shishir Priyadarshi | Space Physics | Best Researcher Award

Technical Lead-ML-GNSS Engineer, GMV NSL, United Kingdom

Dr. Shishir Priyadarshi is an experienced engineer specializing in Machine Learning (ML) and Global Navigation Satellite Systems (GNSS) at GMV, UK. With over a decade of experience, he has significantly contributed to various ESA projects aimed at enhancing the accuracy and resilience of GNSS through innovative ML algorithms. His work spans multiple international research projects and academic appointments, reflecting a deep commitment to advancing space science and technology.

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Education 🎓

Dr. Shishir Priyadarshi earned his Ph.D. in Space Physics (Geophysics) from the Space Research Centre in Warsaw, Poland, in 2014. His thesis, titled “B-spline model of ionospheric scintillation,” was supervised by Professor Andrzej Wernik. Prior to this, he completed his Master of Science (M.Sc.) in Physics, specializing in Electronics and Radio Physics, at Banaras Hindu University in Varanasi, India, in 2009. His master’s thesis was titled “GPS-Based Measurement of TEC and Its Variability Over Ground Station Varanasi, India.”

Experience 💼

Dr. Shishir Priyadarshi currently serves as an ML-GNSS Engineer and Technical Lead at GMV in Nottingham, UK, since February 2022. In this role, he spearheads the development and validation of machine learning techniques for resilient time provisioning in ESA NAVISP projects, with a particular focus on ionospheric GNSS modeling and the detection of GNSS signal interference. Prior to this, he was a Research Associate at the University of Bath, UK, from February 2021 to January 2022, where he contributed to research on ionospheric modeling and ML applications in GNSS. From November 2019 to January 2021, Dr. Priyadarshi worked as a Postdoctoral Researcher at SUSTech in Shenzhen, China, focusing on ionospheric data assimilation and GNSS signal processing. He also served as an Adjunct at the University of Wroclaw, Poland, from July 2018 to June 2019, concentrating on atmospheric research and ionospheric scintillation. From June 2015 to May 2018, he was a Postdoctoral Research Scientist at the Institute of Space Sciences, Shandong University in Weihai, China, where he investigated the coupling of atmospheric layers and GNSS signal propagation. His earlier role as a Space Physicist (Postdoc) at the Space Research Centre in Warsaw, Poland, from August 2014 to May 2015, involved researching the effects of ionospheric disturbances on GNSS signals. As a Marie-Curie Fellow (Early-Stage Researcher) from August 2011 to July 2014 at the Space Research Centre in Warsaw, he developed models for ionospheric scintillation and its impact on satellite communications. Dr. Priyadarshi began his career as a Junior Research Fellow at the Atmospheric Research Laboratory of Banaras Hindu University in Varanasi, India, from August 2009 to 2011, where he studied ionospheric perturbations using GPS data.

Research Interests 🔬

Dr. Shishir Priyadarshi focuses on Magnetosphere-Ionosphere-Thermosphere (MIT) Coupling, exploring how the interactions between various atmospheric layers influence Global Navigation Satellite System (GNSS) signals. His work in Ionospheric Scintillation involves modeling and predicting the responses of ionospheric scintillation to various space weather phenomena. To enhance the accuracy and integrity of GNSS signals, Dr. Priyadarshi employs advanced machine learning (ML) and artificial intelligence (AI) algorithms in GNSS Signal Processing. Additionally, he leverages ML, recurrent neural networks (RNN), and AI to provide real-time Space Weather Nowcasting/Forecasting. His expertise extends to the development of ML-based algorithms for Jamming and Spoofing Detection, which aim to identify and mitigate interference in GNSS signals.

Awards and Achievements 🏆

URSI Young Scientist Award (2017), Montreal, Canada

Young Scientist Award (2014), Space Research Centre, Poland

Marie-Curie Fellow (2011-2014), European Commission

IAPT Award (2006), Indian Association of Physics Teachers

Sadbhavana Club U.P. Award (2003), Indian Government

Publications Top Notes 📚

Priyadarshi, S. (2023). Machine Learning-based ionospheric modelling performance during high ionospheric activity, Acta-Geophysica, cited by 15 articles.

Priyadarshi, S. (2023). Fast and reliable forecasting for satellite clock bias correction with transformer deep learning, Radio-Science, Space Weather, cited by 30 articles. link

Priyadarshi, S. (2020). Near-Earth plasma-sheet cumulative magnetic, American Geoscience Union (AGU), cited by 10 articles.

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