Assist Prof Dr. Apostolos Xenakis | Wireless Sensor Network | Excellence in Research

Assist Prof Dr. Apostolos Xenakis | Wireless Sensor Network | Excellence in Research

Assist Prof Dr. Apostolos Xenakis, University of Thessaly, Greece

Dr. Xenakis, an Assistant Professor at the University of Thessaly’s Department of Digital Systems, holds dual Master’s degrees in Computer Science from the University of Thessaly and Essex University, and a Ph.D. from the University of Thessaly, specializing in energy optimization in Wireless Sensor Networks. His extensive teaching portfolio includes courses in Physics, Digital Image Processing, and Digital Systems Security. Dr. Xenakis also boasts a diverse professional background with roles at the Ministry of National Defense, the Olympic Games Venue (2004), and VODAFONE S.A. His research interests encompass Wireless Sensor Networks, IoT, Fog Networks, and network optimization, with practical applications in precision agriculture and smart pharmaceutical manufacturing.

Professional Profile:

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Suitability for the Excellence in Research:

Dr. Apostolos Xenakis is a highly qualified candidate for the Excellence in Research Award, given his extensive academic background, research experience, and professional contributions to the fields of Wireless Sensor Networks (WSNs), Internet of Things (IoT), and Fog Networks. His work has demonstrated a consistent focus on innovation, particularly in the optimization of energy consumption in WSNs, which is critical for advancing modern communication systems.

Academic Background:

Dr. Xenakis holds two Masterā€™s degrees in Computer Science, specializing in Telecommunications and Networks, from the University of Thessaly, Greece, and Essex University, U.K. He also earned a Ph.D. from the University of Thessaly, where his thesis focused on optimizing energy consumption in Wireless Sensor Networks (WSNs) through network topology control methods. This solid educational foundation in computer science and engineering has equipped him with the knowledge and skills required for high-impact research.

Teaching Experience:

Dr. Xenakis has extensive teaching experience, currently serving as an Assistant Professor at the Department of Digital Systems, University of Thessaly. He teaches a variety of courses, including Physics, Digital Image Processing, and Digital Systemā€™s Security. His teaching career also includes numerous adjunct lecturer roles at the University of Thessaly and other institutions, covering subjects such as Telecommunications, Computer Science, and Digital Systems.

Professional Experience:

Dr. Xenakis has a robust professional background in networks and communications, including roles at the Ministry of National Defense, the Olympic Games Venue (2004), and VODAFONE S.A. His work has ranged from technical support and troubleshooting to telecom traffic analysis, providing him with practical industry experience that complements his academic pursuits.

Research Interests and Contributions:

Dr. Xenakisā€™ research focuses on Wireless Sensor Networks (WSNs), Internet of Things (IoT), Fog Networks, and optimization techniques for computer and telecommunication network design. His research is notable for its practical applications, such as precision agriculture and smart pharmaceutical manufacturing.

Publication Top Notes:

  • Title: Topology Optimization in Wireless Sensor Networks for Precision Agriculture Applications
    • Citations: 77
    • Year: 2007
  • Title: Smart Pharmaceutical Manufacturing: Ensuring End-to-End Traceability and Data Integrity in Medicine Production
    • Citations: 60
    • Year: 2021
  • Title: Towards Distributed IoT/Cloud Based Fault Detection and Maintenance in Industrial Automation
    • Citations: 47
    • Year: 2019
  • Title: The Use of LEGO Mindstorms in Elementary Schools
    • Citations: 35
    • Year: 2017
  • Title: Cross-layer Energy-aware Topology Control through Simulated Annealing for WSNs
    • Citations: 26
    • Year: 2016

 

 

 

Assoc Prof Dr. Shuzhi Liu | Sensor Networks Awards | Best Researcher Award

Assoc Prof Dr. Shuzhi Liu | Sensor Networks Awards | Best Researcher Award

Assoc Prof Dr. Shuzhi Liu, Qilu Normal University, China

Dr. Shuzhi Liu is an Associate Professor at Qilu Normal University, Jinan, China, specializing in IoT, Indoor Positioning, and Next-Generation Communication. He earned his Ph.D. from Dongguk University, and holds two Bachelor of Engineering degrees from Hanyang University and Qingdao University of Science and Technology. Since September 2023, Dr. Liu has been recognized for his exceptional interpersonal communication skills, which enhance his teaching and academic collaborations. His role includes facilitating complex discussions, collaborating with the dean to improve academic programs, and contributing to teaching excellence through detailed course evaluations and active engagement in research.

šŸŒ Professional Profile:

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Education:

Dr. Liu earned his Ph.D. from Dongguk University (2018-2023), focusing on IoT, Indoor Positioning, and Next-Generation Communication šŸŽ“. He also holds a Bachelor of Engineering from Hanyang University (2016-2018) and another Bachelor of Engineering from Qingdao University of Science and Technology (2014-2018) šŸ†.

Job Experience:

Since September 2023, Dr. Liu has served as an Associate Professor at Qilu Normal University. His role involves demonstrating strong communication skills, facilitating clear discussions on complex topics, and collaborating with the dean to assess and improve academic programs and courses šŸ“Š.

Current Position:

Dr. Shuzhi Liu is an accomplished Associate Professor at Qilu Normal University, Jinan, China šŸ“š. He is recognized for his expertise in research and exceptional interpersonal communication skills, which enhance his interactions with students and faculty.

Specializations:

He specializes in lesson planning, faculty collaboration, and significantly contributes to teaching excellence through comprehensive course evaluation and active engagement in academic publication āœļø.

Publication Top Notes:

  • Enabling Technologies for AI Empowered 6G Massive Radio Access Networks
    • Publication Year: 2023
    • Citations: 27
  • Hybrid of Angular and Distance Protection for Coexistence of 5G Base Stations and Satellite Earth Stations
    • Publication Year: 2022
    • Citations: 5
  • Interference Analysis Method for 5G System to Radio Altimeter
    • Publication Year: 2022
    • Citations: 6
  • Clustering-Based Noise Elimination Scheme for Data Pre-Processing for Deep Learning Classifier in Fingerprint Indoor Positioning System
    • Publication Year: 2021
    • Citations: 10
  • Distance Protection for Coexistence of 5G Base Station and Satellite Earth Station
    • Publication Year: 2021
    • Citations: 11