Assoc. Prof. Dr. Yao-Chuan Tsai | Sensor | Best Researcher Award

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Assoc. Prof. Dr. Yao-Chuan Tsai | Sensor | Best Researcher Award

Assoc. Prof. Dr. Yao-Chuan Tsai | National Chung Hsing University | Taiwan

Assoc. Prof. Dr. Yao-Chuan Tsai is a distinguished scholar and innovative researcher whose work integrates mechanical engineering, microfabrication, and smart agricultural technologies. His academic journey and professional experiences have spanned Taiwan and Japan, and his expertise covers micro-electro-mechanical systems (MEMS), micromanufacturing, automation, and artificial intelligence applications in agriculture. Currently serving as the Department Chair of Bio-Industrial Mechatronic Engineering at National Chung Hsing University, he has been instrumental in advancing interdisciplinary approaches to smart farming and bio-industrial automation. Assoc. Prof. Dr. Yao-Chuan Tsai has also directed major research centers, guided industry collaborations, and received international recognition for his inventive contributions in agricultural engineering, demonstrating a career that bridges cutting-edge technology with real-world sustainability solutions.

Professional Profile

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Summary of Suitability 

Assoc. Prof. Dr. Yao-Chuan Tsai is a distinguished researcher and academic leader in bio-industrial mechatronic engineering, micro-electromechanical systems (MEMS), micromanufacturing, automation, artificial intelligence applications, and smart agriculture. With advanced degrees in Mechanical Engineering from National Taiwan University and a strong international research background in Japan, he has established himself as a pioneer at the intersection of engineering innovation and agricultural technology.

Education

Assoc. Prof. Dr. Yao-Chuan Tsai earned his Bachelor of Science degree in Mechanical Engineering from National Chiao-Tung University, where he built the foundational knowledge of mechanics, materials, and automation. He continued his graduate studies at National Taiwan University, completing both his Master of Science and Doctor of Philosophy degrees in Mechanical Engineering. His doctoral research involved MEMS and micromanufacturing, laying the groundwork for future exploration of automation and artificial intelligence applications in agriculture. His strong academic training across Taiwan’s leading universities prepared him with a balance of technical rigor, innovative thinking, and interdisciplinary vision that underpins his current contributions.

Experience

Assoc. Prof. Dr. Yao-Chuan Tsai professional career reflects a balance between academic leadership and international research collaborations. He began as a researcher at the Micro System Integration Center (μSIC) and later at the Advanced Institute for Materials Research (WPI-AIMR) at Tohoku University in Japan, where he contributed to micromanufacturing and MEMS integration projects. He also gained industry experience as a researcher with MEMS-CORE Corporation in Japan, applying micro-automation technologies in practical contexts. Returning to Taiwan, he joined the Department of Bio-Industrial Mechatronic Engineering at National Chung Hsing University as Assistant Professor and steadily advanced to Associate Professor and Department Chair. He also served as Director of the Agricultural Automation Center, where he established collaborative projects linking artificial intelligence, robotics, and farming technology. His leadership roles underscore his ability to bridge academia, research, and industry with measurable impact.

Research Interests

Assoc. Prof. Dr. Yao-Chuan Tsai research interests encompass micro-electro-mechanical systems, micromanufacturing, automation technologies, and their integration into agricultural applications. He is particularly dedicated to advancing smart agriculture, focusing on precision farming systems that incorporate MEMS sensors, machine learning algorithms, and AI-driven automation to optimize productivity while maintaining sustainability. His work also explores automation in livestock farming, including animal monitoring, weight detection, and behavior recognition, as well as AI-based bird detection and repelling systems. By combining MEMS design with AI modeling, his research provides innovative solutions to challenges in agriculture, demonstrating how cutting-edge technology can transform traditional industries.

Awards

Assoc. Prof. Dr. Yao-Chuan Tsai has received multiple awards and honors that highlight his excellence in both teaching and research. He has twice been honored with the National Chung Hsing University Industry-Academic Outstanding Teacher Award, recognizing his contributions to technology transfer and academic-industry collaboration. He was also the recipient of the School Outstanding Instructor Award, demonstrating his commitment to education and mentorship. His patents on agricultural automation systems, including an automatic animal weight measurement method and a bird detection and repelling system, won Silver Medals at the Taiwan Innovation and Technology Expo Invention Competitions. Furthermore, he earned an Outstanding Award in AI and Agriculture, Forestry, Fisheries, and Animal Husbandry at a major AI competition, underscoring the interdisciplinary impact of his work. These accolades reflect not only his technical contributions but also his role in shaping the future of agricultural innovation.

Publication Top Notes

  • On‐chip micro‐pseudocapacitors for ultrahigh energy and power delivery
    Year: 2015
    Citation: 80

  • Identifying images of dead chickens with a chicken removal system integrated with a deep learning algorithm
    Year: 2021
    Citation: 79

  • Non-contact magnetic cantilever-type piezoelectric energy harvester for rotational mechanism
    Year: 2018
    Citation: 61

  • Design and fabrication of a phononic-crystal-based Love wave resonator in GHz range
    Year: 2014
    Citation: 47

  • Laser-induced graphene stretchable strain sensor with vertical and parallel patterns
    Year: 2022
    Citation: 45

  • Low-concentration ammonia gas sensors manufactured using the CMOS–MEMS technique
    Year: 2020
    Citation: 43

  • Metallic glass as a mechanical material for microscanners
    Year: 2015
    Citation: 38

  • Evidence of a Love wave bandgap in a quartz substrate coated with a phononic thin layer
    Year: 2014
    Citation: 31

Conclusion

Assoc. Prof. Dr. Yao-Chuan Tsai has established himself as a leading researcher at the intersection of mechanical engineering, MEMS, and agricultural automation. His educational background, extensive research experiences across Taiwan and Japan, and leadership roles in academia underscore his multidisciplinary expertise. His research interests in micromanufacturing, automation, smart agriculture, and AI applications have led to impactful innovations, including patented technologies and award-winning inventions. With a proven record of publications, invited talks, and recognitions, Assoc. Prof. Dr. Yao-Chuan Tsai contributions extend beyond academic theory into practical solutions that enhance agricultural productivity and sustainability. His achievements make him a highly deserving candidate for recognition in award nominations, reflecting not only his academic excellence but also his broader impact on industry and society through technological innovation.

Ms. Navneet Gandhi | Gas Sensor Awards | Best Researcher Award

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Ms. Navneet Gandhi | Gas Sensor Awards | Best Researcher Award 

Ms. Navneet Gandhi, IIITDM jabalpur, India

Navneet Gandhi is an aspiring semiconductor researcher currently pursuing a Ph.D. at IIITDM Jabalpur, India, with a strong focus on advanced nanoelectronic devices and sensor technologies. Her doctoral research centers on the simulation, fabrication, and machine learning-aided optimization of junctionless FET-based sensors, emphasizing negative capacitance and strain silicon approaches. With a Master’s degree in Embedded Systems and VLSI Design from SVITS Indore and a Bachelor’s degree in Electronics and Telecommunication Engineering from LNCT Indore, Navneet has built a solid academic foundation. Her research interests span simulation and modeling of NC-FET-based biosensors and gas sensors, the use of AI techniques in semiconductor device analysis, and the exploration of next-generation device architectures such as nanosheets, forksheets, and FerroFETs. Additionally, she is engaged in the fabrication of nanomaterial-based sensors. Navneet combines strong theoretical expertise with hands-on experience, aiming to contribute significantly to the advancement of sensor technology and nanoelectronics.

Professional Profile:

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ORCID

Summary of Suitability: Navneet Gandhi – Best Researcher Award

Navneet Gandhi is a highly promising researcher in the field of semiconductor devices, nanosensors, and machine learning-assisted modeling. With a solid academic background and deep-rooted research expertise, she is making significant contributions to the advancement of next-generation sensor technologies.

📚 Education Background

  • 🎓 Ph.D. (Pursuing) | 2021 – 2024
    Institute: IIITDM Jabalpur, India
    Thesis: Simulation, Fabrication, and Machine Learning-Aided Optimization of Advanced Junctionless FET-Based Sensors With Negative Capacitance and Strain Silicon Approach

  • 🎓 Master of Engineering (M.E.) | 2011 – 2014
    Specialization: Embedded System and VLSI Design
    Institute: SVITS, Indore, India
    Percentage: 79.6%
    Thesis: Design of Voice Morphing System Using FFT

  • 🎓 Bachelor of Engineering (B.E.) | 2006 – 2010
    Specialization: Electronics and Telecommunication Engineering
    Institute: L.N.C.T, Indore, India
    Percentage: 79.78%

  • 🏫 Intermediate (12th) | 2005 – 2006
    Board: Govt. G. H. S. School, Khirkiya (M.P)
    Percentage: 88%
    Subjects: Physics, Chemistry, Mathematics, English, Hindi

  • 🏫 High School (10th) | 2003 – 2004
    Board: Govt. G. H. S. School, Khirkiya (M.P), India

🏆 Achievements, Awards & Honors

✨ Academic Excellence:

  • Consistently performed with distinction in both undergraduate and postgraduate studies (Above 79% in B.E. and M.E.) 🎖️

  • 88% in Intermediate with strong fundamentals in science and mathematics 📐🔬

🌟 Research Contributions (Ph.D. Focus):

  • Advanced research in simulation and fabrication of Negative Capacitance FET-based sensors

  • Integration of Machine Learning and Deep Learning in semiconductor device analysis 🤖📊

  • Exploration of emerging technologies including NC-FETs, Nanosheets, Forksheet, and FerroFETs

🔬 Interdisciplinary Skills:

  • Simulation ⚙️

  • Nanomaterials fabrication 🧪

  • Sensor modeling 📉

  • AI-based device optimization 🧠

Publication Top Notes:

Self-heating and interface traps assisted noise behavior analysis of JL-FinFET H2 gas sensor

Proof of concept: comparative study of machine learning models for optimization and performance evaluation of DM RSD JLNC-FinFET biosensor

Revealing the Reliability Performance of a Dielectric-Modulated Negative Capacitance Junctionless FinFET Biosensor

Junctionless negative capacitance FinFET-based dielectric modulated biosensor with strain silicon integration at different FE thickness

A proof of concept for reliability aware analysis of junctionless negative capacitance FinFET-based hydrogen sensor

Unveiling the Self-Heating and Process Variation Reliability of a Junctionless FinFET-Based Hydrogen Gas Sensor

Demonstration of a Junctionless Negative Capacitance FinFET-based Hydrogen Gas Sensor: A Reliability Perspective

Self-Heating and Interface Traps Assisted Early Aging Revelation and Reliability Analysis of Negative Capacitance FinFET

Prof. Dr. Lorena Barona López | Sensors | Best Researcher Award

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Prof. Dr. Lorena Barona López | Sensors | Best Researcher Award 

Prof. Dr. Lorena Barona López, EPN, Ecuador 

Lorena Isabel Barona López is a researcher and professor specializing in computer science and telecommunications, currently affiliated with the Escuela Politécnica Nacional in Quito, Ecuador. She holds a Ph.D. in Computer Science from the Universidad Complutense de Madrid, Spain, where she developed a situational awareness model for 5G mobile networks within the SELFNET architecture. Her academic background also includes a Master’s in Telematic Services and Networking Engineering from Universidad Politécnica de Madrid and a Bachelor’s degree in Electronic and Information Network Engineering from Escuela Politécnica Nacional. Dr. Barona’s research interests encompass 5G networks, software-defined networking (SDN), virtualization, and data analysis. She is an accredited Level 1 researcher by the Ecuadorian Secretariat for Higher Education, Science, and Technology and a member of various international research networks, including Ciencia Digital and Indra Digital Lab. With extensive teaching experience at both national and international universities, she has lectured in areas such as cybersecurity, network security, embedded systems, and system architecture. Dr. Barona also serves as the Executive Editor of the Ciencia Digital journal and has professional experience in systems administration and IT support. She is proficient in both Spanish and English and actively pursues professional development in artificial intelligence, machine learning, programming, and digital pedagogy.

Professional Profile:

GOOGLE SCHOLAR

ORCID

Summary of Suitability for Best Researcher Award

Dr. Lorena Isabel Barona López is a distinguished academic and researcher in the fields of Computer Science, 5G networks, Data Analysis, Software-Defined Networks (SDN), and Virtualization. Her extensive research background, innovative contributions to next-generation networking technologies, and commitment to both education and scientific advancement make her an exceptionally qualified candidate for the Best Researcher Award.

👩‍🎓 Education

  • 🎓 Ph.D. in Computer Science
    Universidad Complutense de Madrid, Spain
    (Nov 2013 – Sep 2017)
    📘 Thesis: Modelo de Conciencia Situacional para el Análisis de Datos en Redes Móviles 5G
    🔍 Research Areas: 5G, Data Analysis, SDN, Virtualization

  • 🎓 Master’s in Telematic Services & Networking Engineering
    Universidad Politécnica de Madrid, Spain
    (Sep 2012 – Jul 2013)
    📘 Thesis: Propuesta de Escenarios Virtuales con la Herramienta VNX para Pruebas del Protocolo OpenFlow
    🔍 Focus: OpenFlow, Networks, SDN, Virtualization

  • 🎓 Bachelor’s in Electronic and Information Network Engineering
    Escuela Politécnica Nacional, Ecuador
    (Oct 2004 – Oct 2010)
    📘 Project: IP-based Surveillance System for Condominiums in Ambato
    🔍 Focus: IP, Networks

💼 Work & Teaching Experience

  • 🧠 Researcher, GASS Group
    Universidad Complutense de Madrid
    (Nov 2013 – Jul 2017)
    🧪 Focus on cybersecurity, 5G, and data analysis.

  • 📝 Executive Editor, Ciencia Digital Journal
    (Sep 2017 – Present)

  • 👩‍🏫 Teaching Roles (2011–2025):
    Courses in:

    • Communication Systems, Embedded Systems, Cybersecurity 🔐

    • Network Security, Software Engineering 💻

    • Extended Databases, Operating Systems 🖥️

    • MOOCs and online teaching platforms 🎓

    📍 Institutions:

    • Escuela Politécnica Nacional

    • Universidad Internacional de la Rioja (Spain)

    • Universidad Técnica de Ambato

    • Universidad Metropolitana

    • Universidad de las Américas

  • 🖥️ System Administrator, COMDECSA
    (May 2011 – Sep 2012)

  • 🧪 Lab Assistant, Escuela Politécnica Nacional
    (Sep 2009 – Aug 2010)

🏅 Achievements, Accreditations, and Honors

  • 🥇 Aggregated Researcher Level 1, Ecuador’s Secretaría de Educación Superior, Ciencia y Tecnología (2018)

  • 🌐 Member of:

    • Ciencia Digital Network (2019)

    • International Network Indra Digital Lab, Spain

  • 📜 Extensive professional certifications in:

    • AI & Machine Learning 🤖

    • ICT in Education 💡

    • Cloud Dashboards ☁️

    • Programming (Python 🐍, Java ☕, R 📊)

    • Educational tools and Moodle platforms 🎓

  • 🎖️ Expert in Pedagogical Innovation: flipped classrooms, digital teaching tools, and virtual course design.

Publication Top Notes:

A Systematic Literature Review of Machine Unlearning Techniques in Neural Networks

Heterogeneity Challenges of Federated Learning for Future Wireless Communication Networks

A comparison of EMG-based hand gesture recognition systems based on supervised and reinforcement learning

Recognition of Hand Gestures Based on EMG Signals with Deep and Double-Deep Q-Networks

Hand Gesture and Arm Movement Recognition for Multimodal Control of a 3-DOF Helicopter

Hand Gesture Recognition Using EMG-IMU Signals and Deep Q-Networks

A Hand Gesture Recognition System Using EMG and Reinforcement Learning: A Q-Learning Approach

Assoc Prof Dr Zhongxiang Liu | Applications of Sensors | Best Researcher Award

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Assoc Prof Dr Zhongxiang Liu | Applications of Sensors | Best Researcher Award 

 Assoc Prof Dr Zhongxiang Liu,Associate Researcher, Southeast University,China

Zhongxiang Liu is an Associate Professor at the School of Transportation, Southeast University, Nanjing, China. He has a strong background in structural engineering, with substantial experience in academia and research. His international exposure includes postdoctoral research at Columbia University and a visiting scholarship at Virginia Tech in the USA. With multiple editorial roles and contributions to international journals, Liu has established himself as a distinguished researcher in structural health monitoring and smart city infrastructure. He has received prestigious awards for his contributions to civil and structural engineering and is dedicated to advancing resilient and sustainable engineering solutions.

Professional Profile:

Summary of Suitability for the Best Researcher Award:

Zhongxiang Liu is an Associate Professor at the School of Transportation, Southeast University, with a Ph.D. in Structural Engineering from Southeast University, China. He has a robust academic background, having completed postdoctoral research at Columbia University and held a visiting scholar position at Virginia Tech. His research expertise lies in structural health monitoring, resilient structures for smart cities, and dynamic analysis of offshore structures. Liu is recognized for his prolific contributions as a guest editor for multiple high-impact journals and has received several prestigious awards, including the Science and Technology Progress Award of China and the Gold Medal at the International Exhibition of Inventions of Geneva.

Education

Zhongxiang Liu earned his Ph.D. in Structural Engineering from Southeast University, Nanjing, China, in 2019. Prior to that, he completed his M.S. in Structural Engineering at the same institution in Chongqing, China, in 2015. He holds a B.S. in Civil Engineering from Chongqing University, Chongqing, China, awarded in 2012. His strong academic foundation has provided him with the necessary expertise to excel in structural health monitoring, offshore structure dynamics, and novel sensing technologies for smart cities.

Work Experience

Liu has been serving as an Associate Professor at Southeast University, Nanjing, China, since February 2021. Before this, he was a Postdoctoral Research Fellow at Columbia University, USA, from November 2019 to November 2020. He also gained valuable international experience as a Visiting Scholar at Virginia Tech, USA, from November 2016 to November 2017. His work in these roles has focused on structural health monitoring, dynamic analysis of offshore structures, and the application of resilient engineering technologies in urban infrastructure.

Skills

Zhongxiang Liu specializes in structural health monitoring, offshore structure analysis, and resilient urban infrastructure. His skills extend to advanced hydro- and aero-dynamic analysis, condition assessment of bridges, and novel sensing technologies for smart city applications. He has editorial and review expertise for high-impact journals, as well as experience in conducting performance evaluations of structural systems. His proficiency in combining these skills to address practical engineering challenges makes him a versatile researcher and educator in the field of civil engineering.

Awards and Honors

Liu has received numerous prestigious awards, including the First Prize in the Science and Technology Progress Award of Jiangsu, China (2022) and the Grand Prize from the China Highway and Transportation Society (2022). His research was recognized internationally, earning the Gold Award with congratulations from the Jury at the 48th International Exhibition of Inventions of Geneva in 2023. Liu was also honored with the Liu Huixian Earthquake Engineering Scholarship Award (2019), as well as several National Scholarships from the Ministry of Education of China during his doctoral and master’s studies.

Membership

Zhongxiang Liu is actively involved in the academic community, serving as a guest editor for multiple journals including Materials (MDPI), Applied Sciences (MDPI), and Modelling (MDPI). He is a Youth Editorial member for the International Journal of Structural Integrity and Journal of Disaster Prevention and Mitigation Engineering. In addition, he reviews for more than 20 international journals in the fields of structural engineering and performance evaluation, further establishing his expertise and influence in the field.

Teaching Experience

As an Associate Professor at Southeast University, Liu is involved in teaching and mentoring students in advanced structural engineering concepts. His international experience at prestigious institutions such as Columbia University and Virginia Tech enriches his teaching, allowing him to incorporate a global perspective into his lectures. He guides students in the fields of structural health monitoring, offshore structures, and smart city technologies, preparing the next generation of engineers to tackle modern infrastructure challenges with innovative solutions.

Research Focus

Liu’s research primarily focuses on structural health monitoring and the condition assessment of bridges, along with hydro- and aero-dynamic analysis of offshore structures. His work emphasizes resilient infrastructure solutions, particularly in the context of smart cities. By developing novel sensing technologies and resilient structural designs, Liu aims to enhance urban infrastructure’s longevity and safety. His research also explores the control and evaluation of dynamic responses in offshore structures, contributing to advancements in both civil engineering and sustainable urban development.

Publication top Notes:

 

Sensors for high energy physics applications

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Introduction of Sensors for high energy physics applications

Sensors for high energy physics applications are at the forefront of scientific discovery, enabling the detection and measurement of subatomic particles and phenomena in particle accelerators and detectors.

Particle Detectors:

Investigating the development of particle Detectors including silicon strip detectors calorimeters and time-of-flight detectors used to identify and track particles produced in high-energy collisions.

Radiation-Hard Sensors:

Focusing on sensors and materials that can withstand the intense radiation Environments found in particle Physics experiments ensuring long-term reliability and accuracy.

Fast Timing Detectors:

Addressing the need for sensors with high temporal Resolution for time-of-flight Measurements particle identification, and the study of short-lived particles.

Gas and Liquid Detectors:

Analyzing gas and liquid detectors. such as drift chambers and time projection Chambers, used for precise particle tracking and momentum measurement.

Trigger and Data Acquisition Systems:

Investigating sensor technologies integrated into Trigger and data Acquisition systems to efficiently select and record relevant collision events in real-time from the vast data generated in high-energy physics experiments.