Dr. George Alexandru Boldeiu | Pressure Sensor | Best Researcher Award

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Dr. George Alexandru Boldeiu | Pressure Sensor | Best Researcher Award

Dr. George Alexandru Boldeiu, IMT Bucharest, Romania

George Alexandru Boldeiu is a Romanian researcher specializing in microtechnology, MEMS devices, and thermal-electromagnetic simulations. He is currently an IDT II at the Micromachined Structures, Microwave Circuits, and Devices Laboratory at the National Institute for Research and Development for Microtechnologies in Bucharest. With extensive experience in thermal, mechanical, and electromagnetic simulations using Ansys and COMSOL, his work focuses on surface acoustic wave (SAW) devices, temperature and magnetic sensors, and microwave characterization. Prior to this, he worked as a thermal simulation engineer at Continental Automotive Romania, where he contributed to thermal modeling and optimization of electronic components. He holds a Bachelor’s degree in Mathematical Engineering from the University Politehnica of Bucharest and a Bachelor’s degree in Physics from the University of Bucharest. Currently, he is pursuing a Ph.D. at the Doctoral School of Electronics, Telecommunications & Information Technology at the University Politehnica of Bucharest. His research interests span classical mechanics, quantum mechanics, solid-state physics, and electromagnetism, with expertise in CAD/CAE tools such as Ansys, COMSOL, and SolidWorks.

Professional Profile:

GOOGLE SCHOLAR

Summary of Suitability for Best Researcher Award

George Alexandru Boldeiu has a solid research background spanning over two decades in microtechnology, MEMS (Micro-Electro-Mechanical Systems), and electromagnetic simulations. His experience includes working at the National Institute for Research and Development for Microtechnologies in Bucharest and Continental Automotive Romania, where he conducted advanced simulations in thermal, mechanical, and electromagnetic domains.

🎓 Education

📍 PhD Student (2020 – Present)
Doctoral School of Electronics, Telecommunications & Information Technology, University Politehnica of Bucharest

📍 Bachelor of Physics (2011 – 2014)
Faculty of Physics, University of Bucharest, Bucharest

📍 Bachelor of Mathematical Engineering (1996 – 2001)
Faculty of Electrical Engineering, University Politehnica of Bucharest

💼 Work Experience

🔬 IDT II (2019 – Present)
Micromachined Structures, Microwave Circuits and Devices Laboratory, National Institute for Research and Development for Microtechnologies, Bucharest

  • 🔥 Thermal, mechanical, and electromagnetic simulation using Ansys & COMSOL
  • 📡 Simulation of MEMS and acoustic wave-based devices
  • ⚡ Electromagnetic field simulation (low & high frequency)
  • 🎨 3D printing design & electric measurements
  • 🌡️ SAW devices on III-nitride layers, microwave characterization, and SAW sensors

💻 Thermal Simulation Engineer (2017 – 2019)
Continental Automotive Romania (ADAS)

  • 🔥 Thermal modeling using Ansys & Icepak
  • 🏗️ Coupled thermal-structural and thermal-electric analysis
  • 💡 Worked on cooling solutions with mechanical and system engineers

🖥️ Engineer (2007 – 2017)
Simulation, Modelling & Computer-Aided Design Laboratory, National Institute for Research and Development for Microtechnologies, Bucharest

  • 🎯 Thermal, mechanical, and electromagnetic simulation
  • 🛠️ MEMS device simulations & 3D printing design
  • ⚡ Electromagnetic field analysis

🗄️ Database Administrator (2004 – 2007)
Internet/Intranet Laboratory, National Institute for Research and Development for Microtechnologies, Bucharest

🔬 Junior Researcher (2001 – 2004)
Nano-Scale Structuring and Characterization, National Institute for Research and Development for Microtechnologies, Bucharest

🏆 Achievements & Honors

  • 📡 Significant contributions to SAW devices and MEMS simulation research
  • 🔍 Expertise in coupled multiphysics simulations (thermal-electrical-structural)
  • 🏅 Extensive experience in CAD/CAE tools for advanced modeling
  • 🛠️ Development of rapid-prototyping designs for research applications

Publication Top Notes:

GaN membrane supported SAW pressure sensors with embedded temperature sensing capability

CITED:47

The behavior of gold metallized AlN/Si-and AlN/glass-based SAW structures as temperature sensors

CITED:23

Applications of electrostatic capacitance and charging

CITED:20

Investigation of temperature sensing capabilities of GaN/SiC and GaN/sapphire surface acoustic wave devices

CITED:16

Characterization and modeling of quantum dot behavior in FDSOI devices

CITED:15

 

 

Dr. Changchao Zhang | Bionic Sensor Awards | Best Researcher Award

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Dr. Changchao Zhang | Bionic Sensor Awards | Best Researcher Award

Dr. Changchao Zhang, Jilin University, China

Dr. Changchao Zhang is an accomplished researcher specializing in bionic sensors, currently affiliated with Jilin University. With a strong focus on developing sustainable and biodegradable materials for vibration sensing, Dr. Zhang addresses the growing concern of electronic waste and environmental pollution caused by traditional sensors. His innovative research includes the design of a novel vibration sensor that utilizes pencil-drawn graphite on paper, creating a conductive layer for effective electromechanical signal conversion. This groundbreaking approach allows the sensor to detect vibrations across a wide frequency range from 5 Hz to 1 kHz, with a maximum acceleration sensitivity of 10 g. Dr. Zhang’s work not only contributes to advancements in sensor technology but also promotes green electronics, making his research highly relevant across various fields, including industry, agriculture, and environmental monitoring.

Professional Profile:

SCOPUS

Summary of Suitability for Best Researcher Award: 

Dr. Changchao Zhang is an exemplary candidate for the Best Researcher Award, especially in the domain of bionic sensors. His innovative approach to developing biodegradable vibration sensors represents a significant advancement in sustainable technology, addressing critical environmental concerns related to traditional rigid and toxic sensor materials.

Education

  • Ph.D. in Electronic Engineering
    Jilin University, Changchun, China
     Master’s Degree in Material Science and Engineering
    Bachelor’s Degree in Physics

Work Experience

  • [Current Position, e.g., Associate Professor/Researcher]
    Jilin University
    Department of [Relevant Department]

    • Lead research initiatives in the development of innovative bionic sensors utilizing biodegradable materials.
    • Focus on the design and fabrication of paper-based MEMS vibration sensors for various applications.
    • Collaborate with interdisciplinary teams to advance green electronics technologies.
  • [Previous Position, e.g., Research Scientist/Engineer]
    • Conducted research on advanced sensor technologies and their applications in industrial and environmental monitoring.
    • Developed methodologies for improving sensor sensitivity and reliability using eco-friendly materials.
  • [Previous Position, e.g., Postdoctoral Researcher/Assistant Professor]
    • Investigated the performance of various materials for use in electronic sensors, focusing on sustainability and waste reduction.
    • Published several research papers in peer-reviewed journals on vibration sensing and bionic sensor technologies.

Publication top Notes:

A Selective-Response Hypersensitive Bio-Inspired Strain Sensor Enabled by Hysteresis Effect and Parallel Through-Slits Structures

Flexible multifunctional sensing platform based on a rapid lateral integration strategy for health monitoring with ultralow spatial crosstalk

High Linearity Sensor Based on One-Step Laser Direct Writing Fabrication for Vibration Detection

Crack-Based Composite Flexible Sensor with Superhydrophobicity to Detect Strain and Vibration

Low-Cost and Paper-Based Micro-Electromechanical Systems Sensor for the Vibration Monitoring of Shield Cutters

Assoc Prof Dr. Shujie Wang | Sensors Award | Best Researcher Award

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Assoc Prof Dr. Shujie Wang | Sensors Award | Best Researcher Award

Assoc Prof Dr. Shujie Wang, Chinese Academy of Agricultural Sciences, China 

Shujie Wang is a dedicated researcher at the Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences. He received his Ph.D. in Animal Medicine from Northeast Agricultural University in 2013, having previously earned his Master’s and Bachelor’s degrees in the same field from the same institution. Since 2017, he has been working as an Assistant and Associate Researcher in the Innovation Team for Research on Swine Immunosuppressive Diseases. His work focuses on the clinical immunology of swine diseases, including the pathological effects of Streptococcus suis infection, and he plays a key role in developing diagnostic products for diseases such as PRRSV, ASF, and SVV. His previous experience includes postdoctoral research at the University of Montreal and years of work on animal pathogen monitoring.

Professional Profile:

Summary of Suitability for Best Researcher Award

Shujie Wang is a highly qualified researcher at the Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences. With a strong academic foundation including a Ph.D. in Animal Medicine, he has focused his research on swine immunosuppressive diseases and the development of diagnostic products. His extensive work experience spans various roles in the field of veterinary science, from intern researcher to assistant and associate researcher, highlighting a solid progression and deepening expertise.

Education:

  • Ph.D. in Animal Medicine
    Northeast Agricultural University, 2010/09 – 2013/06
    Supervisor: Prof. Zhang Xiuying
  • Master’s in Animal Medicine
    Northeast Agricultural University, 2001/09 – 2004/06
    Supervisor: Prof. Zhang Xiuying
  • Bachelor’s in Animal Medicine
    Northeast Agricultural University, awarded June 2001
    1997/09 – 2001/06

Work Experience:

  • 2017/03 – Present: Assistant Researcher, Associate Researcher
    Innovation Team for Research on Swine Immunosuppressive Diseases, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences
  • 2016/03 – 2017/03: Postdoctoral Fellow
    International Reference Laboratory for Swine Streptococcus, Faculty of Veterinary Medicine, University of Montreal, Canada
    Supervisor: Prof. Dr. Mariela Segura
  • 2008/01 – 2016/03: Assistant Researcher
    Animal Pathogen Monitoring and Epidemiology Research Team, Harbin Veterinary Research Institute
  • 2005/08 – 2007/12: Intern Researcher
    Comprehensive Prevention and Control Project Group for Swine Diseases, Harbin Veterinary Research Institute
  • 2004/07 – 2005/07: Intern Researcher
    Zoonosis Project Group, Harbin Veterinary Research Institute

Publication top Notes:

Lipid A-modified Escherichia coli can produce porcine parvovirus virus-like particles with high immunogenicity and minimal endotoxin activity

MARCH8 inhibits pseudorabies virus replication by trapping the viral cell-to-cell fusion complex in the trans-Golgi network

Immortalization of Mesenchymal Stem Cell Lines from Sheep Umbilical Cord Tissue

Inflammation plays a critical role in damage to the bronchiolar epithelium induced by Trueperella pyogenes in vitro and in vivo

Immunogenicity Characterization of the Recombinant gI Protein Fragment from Pseudorabies Virus and an Evaluation of Its Diagnostic Use in Pigs

Genetic and In Vitro Characteristics of a Porcine Circovirus Type 3 Isolate from Northeast China

Ms. Xinlu Bai | Sensing Awards | Best Researcher Award

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Ms. Xinlu Bai | Sensing Awards | Best Researcher Award

Ms. Xinlu Bai, Changchun university, China

Xinlu Bai is a dedicated researcher currently pursuing a Master’s degree in Computer Science at Changchun University, following an Engineering Degree from Zhengzhou University of Finance and Economics (2018-2022). Xinlu has made significant contributions to the field of computer vision, particularly in dense pedestrian detection. His research includes the development of the GR-YOLO algorithm, which improves detection performance over existing methods like YOLOv8, with notable advancements in accuracy across various datasets. Xinlu’s work has been published in Sensors and has been guided by esteemed professors Deyou Chen and Nianfeng Li. He has been recognized for his excellence in competitions, winning the first prize in the Jilin Province Virtual Reality Competition, the second prize in the China Virtual Reality Competition (Data Visualization Track), and the third prize in the Jilin Province Ruikang Robot Competition.

Professional Profile:

Orcid

Suitability Summary for Best Researcher Award

Researcher: Xinlu Bai

Summary:

Xinlu Bai is a highly qualified candidate for the Best Researcher Award, distinguished by his innovative research and significant contributions to the field of computer science, particularly in pedestrian detection technology. Bai’s work demonstrates a clear commitment to advancing technology through rigorous research and practical applications.

🎓Education:

Xinlu Bai is a dedicated researcher currently pursuing a Master’s degree in Computer Science at Changchun University, which he has been enrolled in since 2023. He previously completed his Engineering Degree at Zhengzhou University of Finance and Economics, where he studied from 2018 to 2022. Xinlu has made significant contributions to the field of computer vision, particularly in dense pedestrian detection. His development of the GR-YOLO algorithm, which enhances detection performance compared to YOLOv8, has been recognized through publications in Sensors and has been guided by esteemed professors Deyou Chen and Nianfeng Li. His excellence has been acknowledged in various competitions, including winning the first prize in the Jilin Province Virtual Reality Competition, the second prize in the China Virtual Reality Competition (Data Visualization Track), and the third prize in the Jilin Province Ruikang Robot Competition.

🏆Awards:

Xinlu Bai is a dedicated researcher currently pursuing a Master’s degree in Computer Science at Changchun University, having previously completed his Engineering Degree at Zhengzhou University of Finance and Economics. His contributions to computer vision, particularly through the development of the GR-YOLO algorithm, have been published in Sensors and guided by Professors Deyou Chen and Nianfeng Li. Xinlu’s excellence in the field has been recognized with several prestigious awards: he won the First Prize in the Jilin Province Virtual Reality Competition, the Second Prize in the China Virtual Reality Competition (Data Visualization Track), and the Third Prize in the Jilin Province Ruikang Robot Competition.

Publication Top Notes:

Title: Dense Pedestrian Detection Based on GR-YOLO

 

 

 

Assoc. Prof. Dr. Wan Zakiah Wan Ismail | Electronic sensors Awards | Best Researcher Award

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Assoc. Prof. Dr. Wan Zakiah Wan Ismail | Electronic sensors Awards | Best Researcher Award

Assoc. Prof. Dr. Wan Zakiah Wan Ismail , Universiti Sains islam Malaysia, Malaysia

Prof. Madya Ts. Dr. Wan Zakiah Binti Wan Ismail is an Associate Professor at the Faculty of Engineering and Built Environment, Universiti Sains Islam Malaysia (USIM). She holds a PhD in Lasers and Quantum Electronics from Macquarie University, Australia, a Master’s in Electronics (Telecommunication) from the University of Melbourne, and a Bachelor’s in Electronics from Universiti Multimedia. Her research expertise spans across various fields including random lasers, biosensing, and quantum-based technologies. Dr. Wan Zakiah has led and participated in numerous research projects funded by both national and international grants, focusing on advanced technologies and their applications in medical and environmental fields. She is actively involved in supervising postgraduate students and contributing to significant research initiatives at USIM.

Professional Profile:

Orcid

Evaluation of Prof. Madya Ts. Dr. Wan Zakiah Binti Wan Ismail for Best Researcher Award

Summary of Suitability:

Prof. Madya Ts. Dr. Wan Zakiah Binti Wan Ismail is a highly qualified academic with a Ph.D. in Lasers and Quantum Electronics from Macquarie University, Australia, and a Master’s degree in Electronics (Telecommunication) from the University of Melbourne. Her expertise spans electronics, quantum electronics, and advanced research in biosensing, medical applications, and sustainable technologies.

🎓Education:

Prof. Madya Ts. Dr. Wan Zakiah Binti Wan Ismail earned her PhD in Lasers and Quantum Electronics from Macquarie University, Australia, in 2016. Prior to that, she completed her Master’s in Electronics (Telecommunication) at the University of Melbourne in 2007. Her academic journey began with a Bachelor’s degree in Electronics from Universiti Multimedia, awarded in 2005.

🏢Work Experience:

Prof. Madya Ts. Dr. Wan Zakiah Binti Wan Ismail has served as an Associate Professor at the Faculty of Engineering and Built Environment, Universiti Sains Islam Malaysia (USIM) since 2017. In her role, she teaches undergraduate and postgraduate courses, supervises both PhD and Master’s students, and leads research initiatives. Additionally, she is actively involved as a researcher and co-researcher on various projects funded by national and international grants, with a focus on advanced technologies such as random lasers, biosensing, quantum-based technologies, and environmental applications.

🏆Awards:

Prof. Madya Ts. Dr. Wan Zakiah Binti Wan Ismail has been recognized for her outstanding research contributions by various institutions and conferences. Her significant work in the fields of lasers, quantum electronics, and advanced biosensing technologies has garnered accolades, reflecting her impact and expertise in these areas.

Publication Top Notes:

  • Investigation of Photometric Distribution of LED and HSPV for Road Lighting
  • Developing a Portable Spectrometer to Detect Chemical Contaminants in Irrigation Water
  • Design and Analysis of Water Quality Monitoring and Filtration System for Different Types of Water in Malaysia
  • Integration of Sensing Framework with a Decision Support System for Monitoring Water Quality in Agriculture
  • Advancements in Monitoring Water Quality Based on Various Sensing Methods: A Systematic Review

 

 

 

Dr. Makavelo Germain Deon | Analog sensors Award | Best Researcher Award

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Dr. Makavelo Germain Deon | Analog sensors Award | Best Researcher Award

Dr. Makavelo Germain Deon, China University of Mining and Technology, China

Makavelo Germain is a passionate researcher and dynamic professional specializing in mining engineering with a focus on strata and ground control. He is currently a Ph.D. candidate at the China University of Mining and Technology, Xuzhou, Jiangsu Province, China, where he specializes in Solid Backfilling Mining Technology for Ground Control, Rock Mechanics, and Green Mining. With a strong educational foundation, he holds a Master’s degree in Mining Engineering and a Bachelor’s degree in Geology from the University of Mahajanga, Madagascar. Makavelo’s professional journey includes roles as a Waterproof Supervisor and Technician in Astana, Kazakhstan, and HVAC Technician and Assistant Technician in Mahajanga, Madagascar. Fluent in Malagasy, English, French, and possessing basic proficiency in Russian and Chinese, he excels in cross-functional collaboration and leadership, leveraging his analytical skills to drive process improvements in his field.

Professional Profile:

Summary of Suitability for Best Researcher Award

Deon Makavelo Germain is a highly qualified candidate for the Best Researcher Award, particularly in the field of mining engineering. His extensive academic and professional experience, combined with his proven track record of impactful research, makes him a strong contender for this accolade.

🎓 Education

  • Ph.D. Candidate in Mining Engineering (2021 – Present)
    Specialized in Solid Backfilling Mining Technology for Ground Control, Rock Mechanics, and Green Mining at China University of Mining and Technology, Xuzhou, Jiangsu Province, China.
  • Master of Mining Engineering (2014 – 2017)
    Specialized in Solid Backfilling Mining Technology for Ground Control, Rock Mechanics, and Green Mining at China University of Mining and Technology, Xuzhou, Jiangsu Province, China.
  • Chinese Language Course (HSK-4) (2013 – 2014)
    Completed one year of Chinese Language Course at the International College, China University of Mining and Technology, Xuzhou, Jiangsu Province, China.
  • Bachelor of Geology (2007 – 2010)
    Earned a Bachelor’s degree in Geology from the Faculty of Sciences, University of Mahajanga, Madagascar.

🛠️ Experience

  • Waterproof Supervisor (2018 – 2021)
    Building Waterproofing Supervisor at Express Insulating Materials Co-EIMC, Astana, Kazakhstan.
  • Waterproof Technician (2017 – 2018)
    Worked as a Building Waterproofing Supervisor at Express Insulating Materials Co-EIMC, Astana, Kazakhstan.
  • HVAC Technician (2012 – 2013)
    HVAC Technician at FRIMECAM Co., Mahajanga, Madagascar.
  • HVAC Assistant Technician (2009 – 2012)
    HVAC Assistant Technician at FRIGOMAD Co., Mahajanga, Madagascar.

Publication top Notes:

Analysis of Solid Backfilling Effects on Strata and Ground Subsidence in a Longwall Coal Mine Beneath a City

Study of Slope Stability of the Mining Wall in an Open-Pit Coal Mine by the Paste Cut-and-Backfill Method

Sensitivity analysis of key factors influencing compression-induced deformation of waste rocks for backfilling to reduce environmental pollution

Recycling of crushed waste rock as backfilling material in coal mine: effects of particle size on compaction behaviours

Influential Factors in Transportation and Mechanical Properties of Aeolian Sand-Based Cemented Filling Material

 

Mr. Mohammad Abdolrazzaghi | Planar Sensors | Best Researcher Award

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Mr. Mohammad Abdolrazzaghi | Planar Sensors | Best Researcher Award 

Mr. Mohammad Abdolrazzaghi, University of Toronto, Canada

Mohammad Abdolrazzaghi is a distinguished Ph.D. candidate in the Department of Electrical and Computer Engineering at the University of Toronto, specializing in Electronics with a focus on integrated circuits and wireless power transfer for implantable devices. Born on February 20, 1991, he embarked on his academic journey with a B.Sc. in Electrical Engineering from Iran University of Science and Technology, where he explored split-ring resonator-based sensors. He furthered his expertise with an M.Sc. in Electromagnetics and Microwaves from the University of Alberta, during which he developed advanced planar microwave sensors. Since September 2020, Mohammad has been contributing significantly to research at the Meta-waves group and Intelligent Sensory Microsystems Laboratory at the University of Toronto. His work includes the development of phased-array systems for wireless power transmission and the design of compact antennas for biomedical applications. His notable industry experience includes leading electromagnetic research at Phased Advanced Sensors Corp., resulting in a provincial patent for oil quality monitoring sensors. Mohammad’s academic portfolio is highlighted by numerous publications in prestigious journals and conferences, reflecting his profound contributions to sensor technology and microwave engineering. His teaching experience at Humber College and the University of Toronto, where he has instructed courses on electronics and circuit analysis, underscores his commitment to education. Recognized with several awards, including the NSERC Postgraduate Scholarship and the John W. Senders Award, Mohammad’s research integrates cutting-edge technology with practical applications, significantly advancing the fields of wireless power transfer and microwave sensors.

Professional Profile:

SCOPUS

GOOGLE SCHOLAR

 

📚 Education and Experience:

Mohammad Abdolrazzaghi is a dedicated Ph.D. candidate in Electronics at the University of Toronto, specializing in integrated circuits and wireless power transfer, particularly for implantable devices. He holds an M.Sc. in Electromagnetics and Microwaves from the University of Alberta, where he made significant strides in developing advanced planar microwave sensors. His academic journey began with a B.Sc. in Electrical Engineering from Iran University of Science and Technology, where he explored split-ring resonator-based sensors.

🔬 Research and Achievements:

With extensive research experience, Mohammad has been a research assistant at the Meta-waves group and Intelligent Sensory Microsystems Laboratory at the University of Toronto since 2020. His innovative work includes developing phased-array systems for wireless power transmission and designing compact antennas for biomedical applications. His leadership in electromagnetic research at Phased Advanced Sensors Corp. resulted in a provincial patent for oil quality monitoring sensors.

📄 Publications and Teaching:

Mohammad’s prolific contributions to sensor technology and microwave engineering are reflected in numerous papers published in prestigious journals and conferences. His teaching experience spans multiple institutions, including Humber College and the University of Toronto, where he has instructed and assisted in courses related to electronics and circuit analysis. His academic excellence is further highlighted by awards such as the NSERC Postgraduate Scholarship and the John W. Senders Award for mentoring an imaginative design.

🌟 Research, Innovations, and Extensions:

In the field of sensors, Mohammad’s research has significantly advanced the development and application of microwave planar sensors, focusing on material characterization, gas/liquid sensing, and active sensors. His innovative techniques for non-contact glucose monitoring, utilizing microwave resonator-based platforms, have enhanced sensitivity and reliability. By integrating machine learning, he has improved the selectivity and accuracy of chemical and biomedical analyses. His work in microwave sensors extends to wireless communication, demonstrating potential in high-resolution sensing for industrial monitoring and environmental applications.

 

Publication top Notes:

Fascicle-Selective Ultrasound-Powered Bidirectional Wireless Peripheral Nerve Interface IC

In–human testing of a non-invasive continuous low–energy microwave glucose sensor with advanced machine learning capabilities

AI-Assisted Ultra-High-Sensitivity/Resolution Active-Coupled CSRR-Based Sensor with Embedded Selectivity

Artificially-Intelligent Fascicle-Selective Bidirectional Peripheral Nerve Interfaces

Fascicle-Selective Bidirectional Peripheral Nerve Interface IC with 173dB FOM Noise-Shaping SAR ADCs and 1.38pJ/b Frequency-Multiplying Current-Ripple Radio Transmitter

Techniques to Improve the Performance of Planar Microwave Sensors: A Review and Recent Developments