Mr. Mehrdad Shoeibi | Smart Network | Best Researcher Award

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Mr. Mehrdad Shoeibi | Smart Network | Best Researcher AwardĀ 

Mr. Mehrdad Shoeibi, Worcester Polytechnic Institute, United States

Mehrdad Shoeibi is an AI specialist and researcher with expertise in industrial engineering, machine learning, and generative AI, particularly in healthcare, data analytics, and optimization. He is currently pursuing a Ph.D. in Business Administration and Management (IT) at Worcester Polytechnic Institute (WPI) and serves as a Research Assistant for the SmartWAnDS Project, focusing on AI applications in chronic wound analysis. He holds an M.Sc. in Industrial Engineering from the Institute for Management and Planning Studies (IMPS) and a B.Sc. from Islamic Azad University (IAU). Mehrdad has extensive experience in project control management and optimization, having worked in the construction and engineering industries. His technical skills include Python, AI/ML frameworks, and various business intelligence and project management tools.

Professional Profile:

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Suitability of Mehrdad Shoeibi for the Best Researcher Award

Mehrdad Shoeibi demonstrates a strong research background in Generative AI, Machine Learning, Healthcare Applications, and Optimization, which aligns with cutting-edge advancements in AI. His ongoing Ph.D. at Worcester Polytechnic Institute (WPI) and previous degrees in Industrial Engineering establish a solid academic foundation.

šŸŽ“ Education

  • Doctor of Philosophy, Business Administration and Management (IT) (2023 ā€“ Present)
    šŸ“ Worcester Polytechnic Institute (WPI) | GPA: 3.80
  • Master of Science, Industrial Engineering (2018 ā€“ 2021)
    šŸ“ Institute for Management and Planning Studies (IMPS) | GPA: 3.41/4
  • Bachelor of Science, Industrial Engineering (2010 ā€“ 2014)
    šŸ“ Islamic Azad University (IAU) | GPA: 3.11/4

šŸ’¼ Work Experience

Academic & Research Experience

  • Research Assistant ā€“ SmartWAnDS Project, WPI (Aug 2023 ā€“ Present)
    šŸ”¹ Conducting systematic reviews on generative AI applications in healthcare.
    šŸ”¹ Developing tools for chronic wound image annotation and classification.
  • Teaching Assistant ā€“ Game Theory (Feb 2021 ā€“ Jun 2021)
    šŸ“ Institute for Management and Planning Studies (IMPS)
  • Teaching Assistant ā€“ Energy Pricing (Feb 2019 ā€“ Jun 2019)
    šŸ“ Institute for Management and Planning Studies (IMPS)

Industry Experience

  • Project Control Manager ā€“ Aalam Architectural & Structural Consultants (Dec 2019 ā€“ Apr 2023)
    šŸ”¹ Managed BIM implementation.
    šŸ”¹ Coordinated interdisciplinary efforts.
    šŸ”¹ Cost estimation and project scheduling.
    šŸ”¹ Process management and optimization.
  • Project Control Specialist ā€“ Payasazeh Pasargad (Jun 2018 ā€“ Dec 2019)
    šŸ”¹ Provided value engineering recommendations.
    šŸ”¹ Coordinated construction activities.
    šŸ”¹ Prepared project progress reports.
  • Project Control Engineer ā€“ Aalam Architectural & Structural Consultants (Jan 2013 ā€“ Jul 2015)

šŸ† Achievements, Awards & Honors

  • šŸ“œ Published research in Generative AI applications in healthcare.
  • šŸ… Key contributor to the SmartWAnDS Project at WPI.
  • šŸŽ– Expertise in machine learning, optimization, and AI-driven healthcare solutions.
  • šŸ† Experience in business intelligence and operations research.

PublicationĀ Top Notes:

Moving toward resiliency in health supply chain

CITED:8

A Novel Six-Dimensional Chimp Optimization Algorithmā€”Deep Reinforcement Learning-Based Optimization Scheme for Reconfigurable Intelligent Surface-Assisted Energy Harvesting inĀ ā€¦

CITED:1

Improved IChOA-Based Reinforcement Learning for Secrecy Rate Optimization in Smart Grid Communications.

CITED:1

Energy-Efficient and Secure Double RIS-Aided Wireless Sensor Networks: A QoS-Aware Fuzzy Deep Reinforcement Learning Approach

CITED:0

5DGWO-GAN: A Novel Five-Dimensional Gray Wolf Optimizer for Generative Adversarial Network-Enabled Intrusion Detection in IoT Systems.

CITED:0

 

 

Mr. CEYHUN YILMAZ | Smart Devices | Best Researcher Award

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Mr. CEYHUN YILMAZ | Smart Devices | Best Researcher AwardĀ 

Mr. CEYHUN YILMAZ, Sakarya University, Turkey

Assoc. Prof. Dr. Ceyhun Yılmaz is a distinguished mechanical engineer specializing in thermodynamic modeling, renewable energy systems, and hydrogen fuel cells. He earned his Ph.D., M.Sc., and B.Sc. in Mechanical Engineering (English) from the University of Gaziantep. With over a decade of academic and research experience, he has served as a Research Assistant, Assistant Professor, and now an Associate Professor at Afyon Kocatepe University. His expertise includes thermoeconomic analysis, optimization of energy systems, and hydrogen production technologies. Dr. Yılmaz has supervised multiple graduate theses and led numerous TƜBÄ°TAK-funded projects on sustainable energy solutions. He is an active member of ASME and the Turkish Thermal Science and Technique Association, contributing to high-impact scientific publications in top-tier journals. His dedication to advancing energy technologies continues to make a significant impact in the field.

Professional Profile:

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Suitability for Best Researcher Award

Assoc. Prof. Dr. Ceyhun Yılmaz has extensive experience in mechanical engineering, energy systems, and thermoeconomic optimization. His contributions to hydrogen fuel cells, renewable energy, and sustainability demonstrate significant impact in his field. Given his strong academic background, leadership in research, and international training, he is a strong candidate for the Best Researcher Award.

Education šŸŽ“

  • Bachelor of Science in Mechanical Engineering (English)
    University of Gaziantep, 2009
  • Master of Science in Mechanical Engineering (English)
    University of Gaziantep, 2011
  • Ph.D. in Mechanical Engineering (English)
    University of Gaziantep, 2016
    (Includes training at American Mechanical Engineering Society-Hydrogen and Fuel Cell, San Diego, USA, 2014 – 5 months)

Work Experience šŸ’¼

  • Research Assistant
    Department of Mechanical Engineering, University of Gaziantep, 2010-2016
  • Assistant Professor
    Department of Mechanical Engineering, Afyon Kocatepe University, 2017-2020
  • Associate Professor
    Department of Mechanical Engineering, Afyon Kocatepe University, 2020ā€“present

Achievements šŸ†

  • Supervised several Ph.D. and M.Sc. theses, including:
    • Ɩmer Faruk GĆ¼ler: Numerical Modeling of Hydrogen PEM Fuel Cell and Thermoeconomic Optimization (Ph.D., 2022)
    • Muhammed Arslan: Thermodynamic Modeling of a Biogas Power Plant (Ph.D., 2022)
    • Ozan Şen: Thermoeconomic Analysis of Geothermal and Solar Energy (M.Sc., 2021)
    • Ali Hasan Abbas: Thermodynamic Analysis of Natural Gas Liquefaction (M.Sc., 2021)
  • Involved in multiple TƜBÄ°TAK projects (Turkey’s scientific and technological research body), including:
    • Hydrogen Production Simulation using renewable energy and water electrolysis (2022-2023)
    • Concentrated Solar Collector for Afyon Province solar data (2022-2023)
    • Vanadium Redox Flow Battery Performance Evaluation (2023-2025)

Awards & Honors šŸ…

  • Received TƜBÄ°TAK project scholarships and executed high-impact research projects related to geothermal energy, hydrogen production, and renewable energy optimization.

PublicationĀ Top Notes:

Drought-induced oxidative damage and antioxidant responses in peanut (ArachisĀ hypogaeaĀ L.) seedlings

CITED:162

Thermodynamic evaluation of geothermal energy powered hydrogen production by PEM water electrolysisEconomics of hydrogen production and liquefaction by geothermal energy

CITED:152

Economics of hydrogen production and liquefaction by geothermal energy

CITED:126

CITED:124
CITED:111

Body Area Network

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Introduction of Body Area Network

Body Area Networks (BANs) are a frontier in wireless sensor technology, enabling the monitoring of physiological data, vital signs, and physical activity within or around the human body. These networks have profound implications for healthcare, sports, and wearable technology.

Medical BANs for Health Monitoring:

Investigating the development of BANs for continuous monitoring of vital signs, such as heart rate, blood pressure, and glucose levels, in clinical and home settings.

Wearable BAN Devices:

Focusing on wearable BAN devices, including smartwatches and fitness trackers, that integrate seamlessly with the human body to track activity, sleep, and health metrics.

Sensor Integration and Miniaturization:

Addressing challenges in sensor miniaturization and integration within BAN devices, enabling unobtrusive and comfortable long-term wear.

BAN Security and Privacy:

Analyzing security measures and privacy safeguards in BANs to protect sensitive medical and personal data from unauthorized access and breaches.

Wireless Communication Technologies for BANs:

Exploring wireless communication protocols, such as Bluetooth Low Energy (BLE) and Zigbee, optimized for BANs to ensure reliable and energy-efficient data transmission.