Maurizio D’Arienzo | Computer Network | Best Researcher Award

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Assoc. Prof. Dr. Maurizio D’Arienzo | Computer Network | Best Researcher Award

Assoc. Prof. Dr. Maurizio D’Arienzo, University of Campania “L. Vanvitelli”, Italy

Dr. Maurizio D’Arienzo is an accomplished academic and researcher currently serving as an Associate Professor at the Università della Campania “L. Vanvitelli” in Italy. His career spans over two decades, marked by significant contributions to the field of computer networks, particularly in Quality of Service (QoS), software-defined networks, and collaborative diagnosis frameworks. With a distinguished record of research, teaching, and international collaborations, Dr. D’Arienzo has emerged as a prominent figure in the intersection of information engineering and digital transformation. He holds a reputable position in both academia and applied research through his extensive involvement in European and national research projects and his influential presence in international scientific communities.

🌍 Professional Profile

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🏆 Suitability for Best Researcher Award

Dr. Maurizio D’Arienzo exemplifies academic excellence, interdisciplinary research innovation, and international collaboration. With a strong publication record, impactful teaching, and extensive involvement in pioneering research projects—particularly in the fields of computer networks, quality of service, and emerging technologies like AI and blockchain—Dr. D’Arienzo has significantly advanced the frontiers of information and communication technologies. His contributions have not only garnered academic recognition but have also demonstrated practical relevance in real-world systems. For these reasons, Dr. D’Arienzo is highly deserving of the Best Researcher Award, and his nomination stands as a testament to his sustained commitment to excellence in research, education, and service to the scientific community.

🎓 Education

Dr. D’Arienzo earned his Ph.D. in Information Technology Engineering from the University “Federico II” of Naples in February 2003. His doctoral thesis focused on the “Deployment of Flexible Services over Programmable Networks,” reflecting his early engagement with adaptive network infrastructure. Prior to this, he obtained his Laurea Degree in Electronic Engineering from the same university in June 1999, where he developed an API for Quality of Service control in video-streaming applications. These foundational academic pursuits laid the groundwork for a research career rooted in real-world applicability and future-oriented network architectures.

💼 Experience

Dr. D’Arienzo’s professional journey began with research collaborations under European framework projects and expanded into prominent fellowships in Italy and the UK. He served as a Research Fellow at Imperial College London from 2005 to 2006, engaging in EPSRC-funded research on self-aware networks. From 2006 to 2023, he held a permanent position as Assistant Professor at the Department of Political Science, Università della Campania. He has contributed to diverse projects like Smarthealth 2.0, PRIN, and PATTERN AI, where his work centered around network security, digital experience testing in 5G environments, and blockchain-integrated privacy models. His leadership in digital transformation projects with institutions like Banco Napoli Foundation underscores his ability to bridge academic innovation with institutional application.

🔬 Research Focus

Dr. D’Arienzo’s research is deeply embedded in computer networks, with a core focus on Quality of Service (QoS) mechanisms, scalable architectures, and adaptive protocol design. He has significantly contributed to the theoretical and experimental validation of communication models supporting multi-service integration. His more recent research explores game-theoretical approaches in sensor network coordination, algorithmic resilience in software-defined networking (SDN), and the security of digital infrastructures. His global academic collaborations further enriched his approach, enhancing innovation in network protocol research and experimentation.

🏅 Awards and Honors

Dr. D’Arienzo has been recognized multiple times for his scholarly contributions. He received the Best Paper Award at AFIN 2010 for the work titled “Smoothing selfishness by isolating non-cooperative nodes in wireless ad hoc networks”, and again at IEEE Symposium 2010 for the development of UANM, a unified architecture for network measurement. His continued excellence was acknowledged in 2017 at AFIN for a framework facilitating dynamic deployment in wireless sensor networks. Furthermore, his certification as a reviewer and active participation in over two dozen international conference committees highlight his esteemed role in the peer review ecosystem.

📚 Publication Top Notes

An Experimental Comparison of Basic Device Localization Systems in Wireless Sensor Networks
Journal: Network
Date: April 14, 2025
DOI: 10.3390/network5020011
Contributors: Maurizio D’Arienzo
Summary: This article explores the performance of several basic device localization systems in the context of wireless sensor networks (WSNs). It experimentally compares key techniques based on metrics such as energy efficiency, accuracy, and deployment complexity. The study provides insights into choosing suitable localization methods for various WSN deployment scenarios, emphasizing trade-offs between precision and resource usage.

A Cost Effective Solution for the Deployment of Wireless Sensor Networks
Journal: International Journal of Mobile Network Design and Innovation, 2019
DOI: 10.1504/ijmndi.2019.10027010
ISSN: 1744-2869
Contributors: M. D’Arienzo, S.P. Romano
Summary: This study proposes a low-cost strategy for deploying wireless sensor networks with minimal overhead. It introduces a deployment framework that balances energy consumption, network coverage, and fault tolerance. The methodology integrates hardware constraints and energy-aware protocols to optimize node placement and connectivity, making it suitable for environmental and structural monitoring applications.

GOSPF: An Energy Efficient Implementation of the OSPF Routing Protocol
Journal: Journal of Network and Computer Applications, 2016
DOI: 10.1016/j.jnca.2016.07.011
EID: 2-s2.0-84985990205
Contributors: D’Arienzo, M.; Romano, S.P.
Summary: The paper presents GOSPF, a green-oriented enhancement of the OSPF (Open Shortest Path First) routing protocol, tailored for energy efficiency in IP-based sensor networks. Through simulations and practical analysis, it demonstrates substantial energy savings while maintaining high routing performance, offering a viable solution for green network design in dynamic environments.

Estimation of the Energy Consumption of Mobile Sensors in WSN Environmental Monitoring Applications
Conference: 27th International Conference on Advanced Information Networking and Applications Workshops (WAINA 2013)
DOI: 10.1109/WAINA.2013.33
EID: 2-s2.0-84881435314
Contributors: Darienzo, M.; Iacono, M.; Marrone, S.; Nardone, R.
Summary: This conference paper evaluates energy usage patterns in mobile sensor nodes within environmental WSNs. By proposing a simulation model and real-world testing scenarios, the authors quantify how mobility affects power consumption and propose strategies for optimizing operational lifespans in long-term monitoring setups.

Petri Net Based Evaluation of Energy Consumption in Wireless Sensor Nodes
Journal: Journal of High Speed Networks, 2013
DOI: 10.3233/JHS-130482
EID: 2-s2.0-84892702986
Contributors: D’Arienzo, M.; Iacono, M.; Marrone, S.; Nardone, R.
Summary: Utilizing Petri nets, this paper models the energy consumption behaviors of sensor nodes within WSNs. The approach allows for detailed representation of node states and transitions, providing designers with a tool for simulating and analyzing energy dynamics under different protocol and application conditions.

Mr. Murali M | Cloud Computing | Best Researcher Award

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Mr. Murali M | Cloud Computing | Best Researcher Award

Mr. Murali M, Sona College of Technology, India

Mr. Murali M is an accomplished academic with over 14 years of experience in Information Technology education and research. He earned his B.E. in Computer Science and Engineering (2007) and M.E. in Pervasive Computing Technologies (2010) from Anna University. Currently pursuing a Ph.D. at Anna University, Chennai, he serves as Assistant Professor at Sona College of Technology, Salem. Mr. Murali’s expertise spans Robotic Process Automation, Cloud Computing, HCI, and Software Engineering. His dedication to both research and education is reflected in numerous certifications, a published patent, and societal contributions such as mentoring the Tamil Nadu Police-recognized “Migrant Care” app. A recognized reviewer and ISO auditor, he continues to shape academic excellence through continuous innovation and mentorship. 🌐🎓🔬

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🏆 Suitability for Best Researcher Award

Mr. Murali M exemplifies the spirit of innovation and impactful research. His pioneering contribution to developing an AI-enabled intelligent logistics system, recognized with a published patent, reflects his commitment to applied research that solves real-world problems. As an educator and researcher, his interdisciplinary focus—ranging from RPA and cloud computing to wireless sensor networks and HCI—positions him as a thought leader. Beyond academia, his guidance of the award-winning “Migrant Care” app, acknowledged by Tamil Nadu Police, highlights his societal impact. As a reviewer for international journals and an ISO-certified auditor, Mr. Murali maintains high academic and operational standards. His dedication, innovation, and real-world application of research make him a standout candidate for the Best Researcher Award. 🏅📘💡

🎓 Education

Mr. Murali M’s academic foundation is rooted in excellence and innovation. He obtained his B.E. in Computer Science and Engineering from Anna University, Chennai in 2007, followed by an M.E. in Pervasive Computing Technologies from Anna University, Trichy in 2010. Currently, he is pursuing his Ph.D. in Computer Science from Anna University, Chennai, focusing on intelligent systems and automation. His academic path reflects a progressive alignment with emerging technologies, particularly in areas such as AI, cloud computing, and software systems. His rigorous academic training has been instrumental in shaping his research trajectory and commitment to impactful innovation, both in academia and industry. 🧠📚🖥️

👨‍💼 Experience

With over 14 years in academia, Mr. Murali M has consistently contributed to Information Technology education and research. He began his career as a Web Designer at Admire Solutions, Erode (2007–2008), transitioning into academia as a Lecturer at Sona College of Technology, Salem (2010–2011), where he now serves as Assistant Professor since December 2011. His teaching, mentoring, and administrative roles reflect a commitment to academic excellence and institutional development. Notably, he is an ISO core team member, contributing to internal audits and quality systems. His blend of industry experience and academic rigor ensures a practice-based, research-driven learning environment for his students. 💼👨‍🏫📈

🏅 Awards and Honors

Mr. Murali M’s professional journey is marked by multiple accolades and contributions. His standout achievement includes being listed as the fourth inventor on the 2022 patent “AI Enabled Intelligent Logistics System” (Application No. 202241049421). He received formal recognition from the Tamil Nadu Police for mentoring the socially impactful “Migrant Care” app. Murali is also a certified ISO 9001:2015 Internal Auditor and plays a key role as an ISO core team member in his department. His selection as a reviewer for the International Association of Online Engineering journal further highlights his academic credibility. These honors underscore his dual impact—technological and societal—making him a deserving candidate for recognition. 🏅📜🚀

🔍 Research Focus

Mr. Murali M’s research interests encompass several high-impact areas in modern computing. His primary focus areas include Robotic Process Automation (RPA), Wireless Sensor Networks (WSNs), Human-Computer Interaction (HCI), Software Engineering, and Cloud Computing. He is particularly passionate about designing scalable and intelligent systems that improve efficiency and human experience. His interdisciplinary approach bridges technical innovation with social utility, as demonstrated through projects like “Migrant Care” and patented AI logistics systems. Murali’s ongoing Ph.D. research aims to explore advanced automation techniques and adaptive systems using AI and pervasive computing. His work supports future-ready computing solutions that address real-world challenges in enterprise systems, public services, and educational technology. 🤖☁️📶🖱️

📊 Publication Top Notes

  1. A Comprehensive Study on Security Threats in Autonomous Vehicles: Safeguarding the Future

  1. Tribology Interface Over Digital Technologies and Envisaging Tribology with Patent Landscape – A Queer Review

  1. Deep Learning-Based Continuous Glucose Monitoring with Diabetic Prediction Using Deep Spectral Recurrent Neural Network

  2. Detection of Lung Ultrasound Covid-19 Disease Patients Based on Convolution Multifacet Analytics Using Deep Learning

  3. Brain Tumor Detection Using Deep Learning Neural Network for Medical IoT Applications

  4. Analysis of Lung Cancer Detection Based on the Machine Learning Algorithm and IoT

 

 

Prof. Dr. Wen-Chung Tsai | Internet of Things | Best Researcher Award

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Prof. Dr. Wen-Chung Tsai | Internet of Things | Best Researcher Award

Prof. Dr. Wen-Chung Tsai, National Taichung University of Science and Technology, Taiwan

Prof. Dr. Wen-Chung Tsai is an esteemed academic and researcher specializing in Embedded Systems, Internet of Things (IoT), Artificial Intelligence (AI), and Information Security. He earned his Ph.D. in Electronics Engineering from National Taiwan University in 2011 and has since contributed significantly to academia and industry. Dr. Tsai has held key roles at National Taichung University of Science and Technology and Chaoyang University of Technology, where he has mentored students and advanced research in wireless networks, software-hardware integration, and communication protocols. His industry experience includes serving as Deputy Manager at VIA Technologies and as a researcher at the Industrial Technology Research Institute (ITRI), Taiwan. With an extensive publication record, he continues to shape the future of computing and communication technologies.

🌍 Professional Profile 

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🏆 Suitability for Best Researcher Award 

Dr. Wen-Chung Tsai is a highly qualified candidate for the Best Researcher Award due to his outstanding contributions in Embedded Systems, IoT, AI, and Wireless Communication Protocols. His extensive experience in academia and industry enables him to conduct cutting-edge research while ensuring practical applications in technological advancements. His work in software-hardware integration and information security has paved the way for more secure and efficient digital ecosystems. Having served as an Associate Professor and Researcher, he has led multiple projects that enhance computing, connectivity, and cybersecurity. His ability to bridge theory with real-world implementation demonstrates his excellence in research, making him a deserving recipient of this prestigious award.

🎓 Education 

Dr. Wen-Chung Tsai pursued his Ph.D. in Electronics Engineering from National Taiwan University (2006-2011), where he focused on advanced computing architectures and embedded system design. Before that, he completed his Master’s in Electrical Engineering from National Cheng Kung University (1996-1998), where he specialized in networking protocols and wireless communication technologies. His strong academic foundation in software-hardware integration, AI-driven embedded systems, and IoT security has guided his research endeavors. With interdisciplinary expertise spanning computer science, electronics, and telecommunications, he has consistently contributed to technological innovation and engineering advancements. His academic journey is a testament to his commitment to pushing the boundaries of technology through rigorous research and innovation.

💼 Experience 

Dr. Wen-Chung Tsai has a rich professional background that blends academic excellence with industrial innovation. He currently serves as an Associate Professor at National Taichung University of Science and Technology (2022–Present). Prior to this, he was an Associate Professor at Chaoyang University of Technology (2020–2022) and an Assistant Professor in the same institution (2013–2020). His industry experience includes roles as Deputy Manager at VIA Technologies (2000–2009), Engineer at the Industrial Technology Research Institute (2011–2013), and Visiting Scholar at the University of Wisconsin-Madison (2010). His diverse experience in academia, research institutions, and corporate sectors enables him to drive impactful innovations in IoT, AI, and cybersecurity.

🔬 Research Focus

Dr. Wen-Chung Tsai’s research revolves around cutting-edge technologies in Embedded Systems, IoT, AI, and Cybersecurity. His work in software-hardware integration aims to develop optimized and secure computing environments. His contributions to wireless networks and communication protocols enhance the efficiency of 5G, IoT, and edge computing applications. His AI-driven security models focus on protecting IoT ecosystems from cyber threats. With expertise in real-time embedded computing, he works on power-efficient architectures for smart devices and intelligent networks. His multidisciplinary approach combines electronics, AI, and cybersecurity to develop scalable and resilient technological solutions for future smart cities, industrial automation, and digital transformation.

📊 Publication Top Notes 

  • Field-Programmable Gate Array-Based Implementation of Zero-Trust Stream Data Encryption for Enabling 6G-Narrowband Internet of Things Massive Device Access

    • Year: 2024

  • Anticipative QoS Control: A Self-Reconfigurable On-Chip Communication

    • Year: 2022

  • Automatic Key Update Mechanism for Lightweight M2M Communication and Enhancement of IoT Security: A Case Study of CoAP Using Libcoap Library

    • Year: 2022

  • Network-Cognitive Traffic Control: A Fluidity-Aware On-Chip Communication

    • Year: 2020

 

Prof. Yuehai Zhou | Telecommunications | Best Researcher Award

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Prof. Yuehai Zhou | Telecommunications | Best Researcher Award

Prof. Yuehai Zhou, Xiamen University, China

Prof. Yuehai Zhou is an esteemed researcher in underwater acoustic communication and signal processing. He obtained his Ph.D. in Marine Sciences from Xiamen University and has held research positions in Israel and the U.S. Currently an Associate Professor at Xiamen University, he focuses on underwater acoustic networks and smart acoustic equipment design. His work advances telecommunications in marine environments, ensuring efficient underwater data transmission. With multiple publications in high-impact journals, Prof. Zhou is a leader in oceanic communication technologies. His research bridges electrical engineering and marine sciences, contributing to advancements in global underwater communication systems. 🌊🔊

🌍 Professional Profile:

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🏆 Suitability for the Best Researcher Award 

Prof. Yuehai Zhou is an exceptional candidate for the Best Researcher Award due to his groundbreaking contributions to underwater acoustic communication. His research enhances maritime security, environmental monitoring, and subsea data transmission. With expertise in underwater acoustic signal processing and network design, he pioneers advancements in oceanic telecommunications. His international research exposure in China, the U.S., and Israel has positioned him as a global expert in marine sciences and engineering. His publications, academic leadership, and innovation in smart underwater acoustic equipment establish him as a top researcher driving the future of underwater communication technology. 🌎🔬

🎓 Education 

Prof. Yuehai Zhou pursued his entire higher education at Xiamen University, China, specializing in Marine Sciences. He earned his Bachelor’s (2010), Master’s (2013), and Ph.D. (2018) degrees from the College of Ocean and Earth Sciences. His doctoral research focused on underwater acoustic communication systems. To expand his expertise, he undertook a visiting research program (2016–2018) at the University of Alabama, USA, where he collaborated with experts in electrical and computer engineering. His educational background blends oceanic sciences with telecommunications, providing a robust foundation for his research in underwater acoustics and signal processing. 📡🌊

💼 Experience

Prof. Yuehai Zhou has extensive experience in underwater communication research. He was a Visiting Student at the University of Alabama (2016–2018), where he explored advanced electrical and computer engineering applications in marine environments. From 2018 to 2020, he served as a Postdoctoral Researcher at the Acoustic and Navigation Laboratory, University of Haifa, Israel, where he worked on underwater acoustic networks. Since 2020, he has been an Associate Professor at Xiamen University, focusing on smart underwater acoustic equipment and maritime data transmission. His research integrates signal processing, oceanic science, and telecommunications to improve underwater communication systems. 🌊📡

🏅 Awards & Honors

Prof. Yuehai Zhou’s outstanding contributions to underwater acoustic communication and signal processing have earned him numerous accolades. He received prestigious research grants for marine telecommunications innovation. His Ph.D. research was recognized as one of the best dissertations in marine sciences at Xiamen University. As a postdoctoral researcher in Israel, he contributed to award-winning projects in subsea navigation and acoustic signal processing. He has also received multiple best paper awards in international conferences on underwater acoustics and telecommunications. His excellence in teaching and mentorship has further solidified his reputation as a leader in marine communication technology. 🏆🌊

🔬 Research Focus

Prof. Yuehai Zhou’s research centers on underwater acoustic communication, signal processing, and network design. His work enhances data transmission in underwater environments, supporting applications in marine exploration, defense, environmental monitoring, and autonomous underwater vehicles (AUVs). His studies in smart underwater acoustic equipment aim to optimize signal clarity, reduce interference, and enhance network stability in harsh oceanic conditions. His interdisciplinary approach integrates marine sciences, electrical engineering, and computer networks, making his research crucial for advancing global subsea telecommunications. His innovations drive the development of next-generation underwater wireless communication systems. 🌊🔊📶

📖 Publication Top Notes 

  1. A Three-Dimensional Marine Plastic Litter Real-Time Detection Embedded System Based on Deep Learning
    • Publication Year: April 2025
  2. R&D of a Micro-Sized AUV for Quasi-Real-Time In-Situ Monitoring of Coral Reefs
    • Publication Year: 2024
  1. Spatial–Temporal Multipath Clusters Joint Equalization for Deep-Sea Acoustic Communication in Large Delay Spread Channels
    • Publication Year: 2025
  2. A Fast Kalman Equalizer for Single-Carrier Underwater Acoustic Communication
    • Publication Year: 2024
  3. Minimum-BER Sparsity Exploitation Estimation of Time-Varying Underwater Acoustic OFDM Communication Channel
    • Publication Year: 2024
  4. Research on an M-Ary Frequency Shift Keying With Index Modulation System for Underwater Acoustic Communication
    • Publication Year: December 2024

 

Mr. JeongHun Woo | Network Services | Excellence in Research

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Mr. JeongHun Woo | Network Services | Excellence in Research

Mr. JeongHun Woo, Changwon National University, South Korea

Mr. JeongHun Woo is a dedicated researcher specializing in Network Services, Wireless Networks, and Streaming Optimization. He completed his education at Changwon National University, South Korea, and has been actively involved in cutting-edge research projects, particularly in AI-based optimization and predictive analytics. His work on Yard Image AI Recognition for logistics optimization resulted in a technology patent, showcasing his innovative contributions to industrial applications. Additionally, his 2023 first-author publication on adaptive bitrate algorithms and bandwidth prediction has significantly enhanced video streaming quality. His ongoing research on CNC tool replacement cycle prediction highlights his expertise in applying machine learning to industrial automation. With a strong foundation in AI-driven network optimizations and industrial predictive modeling, Mr. Woo continues to push technological boundaries, contributing valuable insights to academia and industry. His research excellence makes him a key player in advancing intelligent network systems. 📡📶🔬

🌏 Professional Profile

Google Scholar

🏆 Suitability for Award 

Mr. JeongHun Woo’s outstanding contributions to network optimization, AI-driven prediction models, and wireless communication technologies make him a strong candidate for the Excellence in Research Award. His groundbreaking work in adaptive video streaming algorithms has significantly improved the Quality of Experience (QoE) in streaming services, addressing critical issues in network bandwidth prediction. His Smart Yard AI project, which optimizes industrial logistics through image recognition, showcases his ability to bridge academic research with real-world applications. The issuance of a technology patent from his research further validates the impact of his work. His ongoing research on predictive maintenance for CNC machine tools highlights his versatility in applying AI-driven methodologies to industrial automation and smart manufacturing. His ability to produce innovative, high-impact research across wireless networks, AI, and predictive analytics sets him apart as a leading researcher in his field. 🏆📡📊

🎓 Education 

Mr. JeongHun Woo pursued his education at Changwon National University, South Korea, where he developed a strong foundation in Network Services, Wireless Communication, and AI-Driven Optimization. His academic journey equipped him with expertise in machine learning applications, network bandwidth prediction, and industrial AI integration. Throughout his education, he focused on research-driven problem-solving, contributing to the development of streaming optimization algorithms and predictive analytics for industrial automation. His exposure to AI-powered logistics and wireless technologies has positioned him as an emerging expert in intelligent network solutions. His academic background not only fueled his passion for research but also enabled him to lead innovative projects such as AI-based yard logistics optimization and CNC machine tool lifecycle prediction. With a strong interdisciplinary approach, his education has played a crucial role in shaping his research excellence and industry-driven solutions. 🎓📚🔍

👨‍🔬 Experience

Mr. JeongHun Woo has been deeply engaged in research projects that integrate AI, wireless communication, and industrial automation. He played a key role in the Smart Yard Industry-Academic Cooperation Project (2022), where he developed an AI-based image recognition system to optimize logistics and process flow in industrial yards. This work led to the successful issuance of a technology patent, reinforcing his contributions to real-world AI applications.

In 2023, he authored a research paper focusing on adaptive bitrate algorithms and bandwidth prediction for enhanced video streaming experiences. His work in network bandwidth prediction using gated recurrent unit models demonstrated his expertise in machine learning-driven optimizations. Currently, he is working on predicting CNC machine tool replacement cycles, leveraging AI for predictive maintenance in smart manufacturing. His diverse experience across network systems, industrial AI applications, and streaming optimizations showcases his strong research acumen and technological impact. 🏭📡🤖

🏆 Awards and Honors 

Mr. JeongHun Woo has been recognized for his pioneering research in wireless networks, AI-driven optimization, and industrial analytics. His Smart Yard AI Recognition project led to the issuance of a technology patent, highlighting the innovative real-world impact of his research. His 2023 first-author publication on adaptive bitrate streaming and bandwidth prediction has been widely acknowledged in the field of wireless networks and multimedia communication.

He has been actively involved in industry-academic collaborative projects, leading groundbreaking research that merges AI with industrial automation. His contributions to predictive analytics for CNC machine tool maintenance have positioned him at the forefront of smart manufacturing and AI-driven optimization. Through his patented technology, high-impact publications, and ongoing research in predictive maintenance, Mr. Woo has demonstrated exceptional excellence in research, making him a deserving candidate for the Research for Excellence in Research Award. 🏆📜🚀

🔬 Research Focus 

Mr. JeongHun Woo’s research revolves around Network Services, Wireless Networks, Streaming Optimization, and AI-driven Industrial Automation. His work is at the intersection of machine learning, predictive analytics, and real-world network applications.

His key research areas include:

✅ Streaming Optimization: Developing buffer-based adaptive bitrate algorithms to improve the Quality of Experience (QoE) for video streaming.
✅ AI for Industrial Automation: Leading AI-driven logistics optimization through yard image recognition and predictive maintenance in smart manufacturing.
✅ Wireless Networks & Bandwidth Prediction: Utilizing deep learning (Gated Recurrent Unit models) for accurate network bandwidth forecasting.
✅ Predictive Maintenance: Researching CNC machine tool lifecycle prediction to enhance manufacturing efficiency and reduce downtime.

His interdisciplinary approach combining network optimizations, AI, and industrial analytics makes him a key contributor to next-generation intelligent systems. 🌍📶📊

📚 Publication Top Notes:

Title: Improving the Quality of Experience of Video Streaming Through a Buffer-Based Adaptive Bitrate Algorithm and Gated Recurrent Unit-Based Network Bandwidth Prediction
Published Year: 2024

 

 

Dr. Meng-Wei Chang | Edge Computing | Best Researcher Award

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Dr. Meng-Wei Chang | Edge Computing | Best Researcher Award

Dr. Meng-Wei Chang, National Taiwan University of Science and Technology, Taiwan

Dr. Meng-Wei Chang is a highly skilled Chief Engineer with a strong background in electrical engineering and computer science. He holds a PhD from the National Taiwan University of Science and Technology and has extensive experience in developing innovative solutions for companies like ADATA Technology, Admiral Overseas Corporation, and Tatung. His expertise lies in RFQ/RFI assessments, hardware and software design, and autonomous mobile robots. Meng-Wei is a published author and holds multiple patents in the field of low power consumption and adaptive dynamic neural network inference. His passion for technology and dedication to delivering cutting-edge products make him a valuable asset to any team.

🌐 Professional Profiles :

Scopus

🎓 Education:

PhD in Electrical Engineering, National Taiwan University of Science and Technology. Undergraduate Coursework: Operating Systems; Databases; Algorithms; Programming Languages; Embedded Systems.

👨‍💻 Experience:

  • Leader Engineer at ADATA Technology: Developed autonomous mobile robot, participated in product prototype showcase, worked with National Taiwan University Hospital, Chunghwa Post, and Taoyuan Aerotropolis.
  • Leader Engineer at Admiral Overseas Corporation: Responsible for brand design, collaborated with units in Taipei, Hsinchu, Xiamen, Fujian, and Shenzhen, involved in US-China trade war assessments and cost reduction developments.
  • Engineer at Tatung: Developed first Android TV set-top box, designed Android streaming multimedia operational framework, provided RFQ/RFI solutions for various companies.

📝 Research & Patents:

Low power consumption and adaptive dynamic neural network inference and data processing flow patent in the Republic of China and USA, with Shun-Feng Su.

🏆 Research Interest :

Dr. Meng-Wei Chang’s research interests include Fog Computing, Edge Computing, Control Systems, and AI Acceleration. He is passionate about exploring innovative solutions in these areas and leveraging them to enhance the performance and efficiency of computing systems. With his expertise in electrical engineering and computer science, Meng-Wei is dedicated to developing novel approaches that harness the power of these technologies to solve real-world problems. 🌐

Publications Top Notes :

  1. Adaptive neural acceleration unit based on heterogeneous multicore hardware architecture FPGA and software-defined hardware
    • Published Year: 2024 (Article in Press)
    • Journal: Journal of the Chinese Institute of Engineers, Transactions of the Chinese Institute of Engineers, Series A
  2. Real-time multi-fusion perceptron architecture for autonomous drones
    • Published Year: 2022
    • Journal: Journal of the Chinese Institute of Engineers, Transactions of the Chinese Institute of Engineers, Series A