Prof. Dr. Hsien-Huang Wu | Automation Awards | Best Researcher Award

Prof. Dr. Hsien-Huang Wu | Automation Awards | Best Researcher Award

Prof. Dr. Hsien-Huang Wu, National Yunlin University of Science and Technology, Taiwan

Dr. Hsien-Huang Wu is a Distinguished Professor in the Department of Electrical Engineering at National Yunlin University of Science and Technology, Douliu, Taiwan. He received his B.S. and M.S. degrees in Telecommunication Engineering from National Chiao Tung University in 1982 and 1986, respectively, and earned his Ph.D. in Electrical and Computer Engineering from the University of Arizona in 1993. His research focuses on artificial intelligence and computer vision, particularly for automated optical inspection (AOI) applications. With extensive industrial collaboration, Dr. Wu has worked with over 50 companies to develop innovative systems for automated inspection and production, bridging academic research and practical implementation.

Professional Profile:

SCOPUS

Summary of Suitability for Best Researcher Award – Dr. Hsien-Huang Wu

Dr. Hsien-Huang Wu stands out as a leading figure in the application of artificial intelligence and computer vision to industrial inspection and measurement systems. With a career spanning over three decades and a Ph.D. from the University of Arizona, he currently serves as a Distinguished Professor at the National Yunlin University of Science and Technology, Taiwan—an acknowledgment of his academic stature and impact.

🎓 Education

  • 📍 B.S. in Telecommunication Engineering
    National Chiao Tung University, Hsinchu, Taiwan – 1982

  • 📍 M.S. in Telecommunication Engineering
    National Chiao Tung University, Hsinchu, Taiwan – 1986

  • 🌎 Ph.D. in Electrical and Computer Engineering
    University of Arizona, Tucson, USA – 1993

💼 Work Experience

  • 👨‍🏫 Distinguished Professor
    Department of Electrical Engineering, National Yunlin University of Science and Technology (NYUST), Douliu, Taiwan
    Current

🌟 Key Achievements

  • 🤖 Pioneering research in artificial intelligence and computer vision for automated optical inspection (AOI)

  • 🏭 Collaborated with 50+ companies to develop intelligent inspection and production automation systems

  • 🔬 Leader in applying cutting-edge AI techniques to real-world industrial measurement and inspection challenges

  • 📚 Significant contributor to academic and applied research in electrical and computer engineering

🏅 Awards & Honors

  • 🥇 Recognized as a Distinguished Professor at NYUST

  • 🏆 Multiple accolades and recognitions for industry collaboration and academic excellence

  • 🧠 Honored for impactful contributions to the field of automated inspection systems

Publication Top Notes:

Prototype design of an intelligent Internet of Things system combined green energy storage device

Distribution Analysis of Dental Plaque Based on Deep Learning

Automatic Optical Inspection for steel golf club

Prof. Dr. Nelson Gutierrez | Automation Awards | Best Researcher Award

Prof. Dr. Nelson Gutierrez | Automation Awards | Best Researcher Award 

Prof. Dr. Nelson Gutierrez, UTE University, Ecuador

Dr. Nelson Ramiro Gutiérrez Suquillo is an Ecuadorian researcher and academic known for his interdisciplinary work at the intersection of robotics, renewable energy, and intelligent industrial systems. He serves as a research lecturer at Universidad UTE since 2015 and is currently pursuing a Ph.D. in Robotics. He holds master’s degrees in Renewable Energies & Energy Sustainability and Materials Science & Technology, as well as a bachelor’s degree in Electronic Engineering and Information Networks. His research spans AI-driven diagnostics, mobile robotics for humanitarian applications, sustainable mechanical design, and advanced signal processing. With publications in journals such as Sensors, Salud, Ciencia y Tecnología, INCISCOS, and Enfoque UTE, his work demonstrates a strong commitment to practical, impactful innovation. Dr. Gutiérrez combines technical depth with applied focus, contributing significantly to Ecuador’s academic and technological landscape through research, teaching, and development projects.

Professional Profile:

ORCID

Summary of Suitability for Best Researcher Award – Nelson Ramiro Gutiérrez Suquillo

Nelson Ramiro Gutiérrez Suquillo stands out as a versatile and impactful researcher whose work bridges robotics, renewable energy, AI-driven diagnostics, and sustainable engineering. His strong academic background, ongoing PhD in robotics, and dual master’s degrees in renewable energy and materials science demonstrate a deep and interdisciplinary technical foundation.

🎓 Education

  • 🧠 Ph.D. in Robotics (Ongoing) – Focused on mobile robotics, system identification, and intelligent systems

  • Master’s in Renewable Energies & Energy Sustainability – Expertise in sustainable technologies and systems

  • 🔬 Master’s in Materials Science & Technology – Specialized in material behavior and simulation

  • 📡 Bachelor’s in Electronic Engineering and Information Networks – Strong foundation in electronics and industrial communication

💼 Work Experience

  • 👨‍🏫 Docente Investigador (Research Lecturer)Universidad UTE (Since 2015)
    Leads research in robotics, AI for diagnostics, and energy sustainability

  • 🤖 Collaborator on applied robotics projects, including mobile platforms and humanitarian demining

  • ⚙️ Industrial systems innovator: developed prototypes for diagnostics and sustainable machinery

🏆 Achievements & Publications

  • 📚 Published in Sensors, Salud, Ciencia y Tecnología, INCISCOS, and Enfoque UTE

  • 🔍 Contributions include:

    • AI for predictive maintenance 🧠

    • System modeling of differential robots 🤖

    • Sustainable mechanical systems 🌱

    • Wavelet-based sEMG signal processing 🧾

    • ABS brake simulation using finite elements 🛞

🥇 Awards & Honors

  • 🏅 Recognized at national and institutional levels for contributions to sustainable innovation and applied robotics

  • 🧑‍🔬 Active leader in Ecuador’s academic and research ecosystem, mentoring students and spearheading interdisciplinary projects

Publication Top Notes:

Comparison of Two System Identification Approaches for a Four-Wheel Differential Robot Based on Velocity Command Execution

Optimization of Fault Prediction by A.I. in Industrial Equipment: analysis of the operating parameters of a Bench Grinder

Application of Model-Based Design for Filtering sEMG Signals Using Wavelet Transform

Diseño de Robot Móvil para tareas de Desminado Humanitario

Análisis por el método de elementos finitos del comportamiento de las pastillas de freno ABS con base de acero y zinc discretizando el elemento continuo utilizando software CAE

Analysis by the Finite Element Method of the Behavior of the Brake Pads Using CAE Software

Diseño y construcción de un prototipo para la extracción continua de aceite de la semilla Sacha Inchi con un proceso de prensado en frío

 

Dr. Tahera Kalsoom | Industrial IoT | Best Researcher Award

Dr. Tahera Kalsoom | Industrial IoT | Best Researcher Award 

Dr. Tahera Kalsoom, Manchester Metropolitan University, United Kingdom

Dr. Tahera Kalsoom is a dedicated lecturer and researcher with over five years of experience in teaching undergraduate and postgraduate courses. She has supervised more than 100 theses and published 14 articles in leading journals and conferences. Her research focuses on the Internet of Things (IoT), Industry 4.0/5.0, data analytics, digitalization, firm performance, and technology management. Dr. Kalsoom holds a Ph.D. in Computing, Engineering, and Physical Sciences from the University of the West of Scotland, where her thesis explored the impact of IoT and dynamic data processing on firm performance. She has also earned an MSc in Financial Management from Middlesex University and a BBA in International Hospitality Management from Stenden University. In addition to her teaching roles at Manchester Metropolitan University and other institutions, Dr. Kalsoom actively contributes to the academic community as a reviewer for various journals and conferences, including IEEE and Wiley & Sons. She is a member of several professional organizations, including IEEE, the British Academy of Management, and the American Finance Association.

Professional Profile:

GOOGLE SCHOLAR

Summary of Suitability for Best Researcher Award: Dr. Tahera Kalsoom

Dr. Tahera Kalsoom is highly suitable for the Best Researcher Award based on her outstanding interdisciplinary research profile, international academic exposure, and clear contributions to emerging domains such as the Internet of Things (IoT), Industry 4.0/5.0, and Data Analytics. With a Ph.D. from a reputable UK institution and over 14 research publications in well-regarded journals and conferences, she demonstrates a consistent research trajectory aligned with modern technological transformations impacting firm performance and digitalisation.

🎓 Education

  • PhD in Computing, Engineering and Physical Sciences
    University of the West of Scotland, Glasgow, UK (2017–2021)
    📘 Thesis: Impact of the Use of IoT, Visibility and Dynamic Data Information Processing Capabilities on Firm Performance

  • MSc in Financial Management
    Middlesex University, London, UK (2014–2015)
    📘 Thesis: Performance of banks after the financial recession, a study of market trends

  • BBA (Hons) in International Hospitality Management
    Stenden University, Qatar (2006–2010)
    📘 Dissertation: Performance analysis of Vodafone call centre in Doha

💼 Professional Experience

  • Lecturer
    Manchester Fashion Institute, MMU, UK (2022–Present)
    📊 Teaching Business Analytics, Strategic Fashion Management, supervising PG students, and PhD co-supervision.

  • Associate Lecturer
    Arden University, Manchester, UK (2022)
    🖥️ Delivered courses on Data Analytics, Operations Management, and Digital Supply Chain 4.0.

  • Research Assistant
    University of the West of Scotland, UK (2021–2022)
    🧠 Contributed to IoT frameworks for EU projects ATHIKA and Safe-RH.

  • Associate Lecturer
    UWS, School of Business and Creative Industries (2020–2021)
    🧾 Delivered tutorials and designed assessments in Operations Management.

  • Lecturer
    ICON College, London, UK (2019–2020)
    🌐 Led IoT module, attended exam boards, and taught Project Management & Strategic Management.

  • Lecturer
    St. Patrick’s College, London, UK (2018–2019)
    🏫 Delivered lectures in HR, Leadership, and Operations Management.

  • Assistant Manager
    M.H. AL-Muftah Est., Doha, Qatar (2016–2017)
    📈 Handled payroll, financial audits, and reporting.

  • Payroll Administrator
    Hamad Int. Airport Project, Civil Aviation Authority, Qatar (2010–2014)
    💼 Managed payroll processing, appraisals, and timesheets.

🌟 Key Achievements

  • 📚 Supervised 100+ UG and PG theses

  • 📝 Published 14 research articles in reputable journals and conferences

  • 🔍 Regular reviewer for journals such as IEEE Access, IEEE Sensors Journal, Sensors (MDPI), Sustainability, and Wiley Books

  • 🎤 TPC Member for IEEE CAMAD, BAM, LRN, and UK-China Emerging Tech Conference

  • 🧑‍🏫 Module Leader and Exam Board Member at ICON and St. Patrick’s Colleges

  • 📦 Developed modules on IoT and Digital Supply Chain 4.0

🏅 Awards & Honours

  • 🥇 Merit AwardTop 20 MSc students, Middlesex University

  • 🏆 Distinction AwardTop 10 in BBA, Stenden University

  • 🎓 First Class ScholarshipStenden University

  • 📜 Roll of HonourTop 20 in HSSC, PEC Doha

Publication Top Notes:

Advances in sensor technologies in the era of smart factory and industry 4.0

CITED:325

Impact of IoT on manufacturing industry 4.0: A new triangular systematic review

CITED:112

Towards supply chain visibility using internet of things: A dyadic analysis review

CITED:107

IoT for 5G/B5G applications in smart homes, smart cities, wearables and connected cars

CITED:46

Market orientation and SME performance: Moderating role of IoT and mediating role of creativity

CITED:43

Millimeter-wave smart antenna solutions for URLLC in industry 4.0 and beyond

CITED:42

 

 

 

Dr. Marzena Miesikowska | Automation Robotics Award | Best Researcher Award

Dr. Marzena Miesikowska | Automation Robotics Award | Best Researcher Award

Dr. Marzena Miesikowska, Kielce University of Technology, Poland 

Marzena Mięsikowska is an Assistant Professor at Kielce University of Technology in Poland. She holds a PhD in Automation and Robotics and a Master’s degree in Computer Science, both from Kielce University of Technology. Her research interests encompass automation, robotics, information systems, and the analysis of acoustic and speech signals, particularly for drone applications and patient rehabilitation. She has completed a National Science Centre project and participated in the “Future Technologies for Defense” project by the National Centre for Research and Development. Mięsikowska has published multiple books and book chapters and holds a patent for a voice quality assessment method. She is also involved in editorial work and various academic collaborations.

Professional Profile:

SCOPUS

Summary of Suitability for Best Researcher Award: Marzena Mięsikowska

Dr. Marzena Mięsikowska is an Assistant Professor at Kielce University of Technology with a robust background in automation and robotics, information systems, and acoustic signal analysis. Her diverse expertise spans drone acoustic signal analysis, speech signal processing, and metrology.

Education:

  • Ph.D. in Automation and Robotics
    Kielce University of Technology, Kielce, Poland
  • Master of Computer Science
    Kielce University of Technology, Kielce, Poland

Work Experience:

  • Assistant Professor
    Kielce University of Technology, Kielce, Poland
    Current Position
  • Metrologist
    Central Office of Measures, Warsaw, Poland
    Past Position

Publication top Notes:

Analysis of Polish Vowels of Tracheoesophageal Speakers

Discriminant analysis of voice commands in a car cabin | Analiza dyskryminacyjna komend głosowych w kabinie pojazdu

Analysis of Sound Levels and Speech Intelligibility in the Presence of X4 Unmanned Aerial Vehicle in External Environmental Conditions

Discriminant analysis of voice commands in the presence of an unmanned aerial vehicle

Speech intelligibility in the presence of X4 unmanned aerial vehicle