Dr. Alice Cervellieri | AI Network | Best Researcher Award

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Dr. Alice Cervellieri | AI Network | Best Researcher Award

Dr. Alice Cervellieri, Polytecnic of Turin, Italy

Professional Profile:

Google Scholar
Scopus

Suitability for the Best Researcher Award

Dr. Alice Cervellieri is an exceptional researcher and academic whose work spans multiple disciplines, including artificial intelligence, energy analysis, and construction technology. With extensive experience in structural reinforcement, agricultural mechanics, and energy-efficient building systems, Dr. Alice Cervellieri’s innovative contributions have led to significant advancements in both academia and industry. Her involvement in international projects, such as the EU H2020 “ENCORE” initiative, demonstrates her global impact on sustainable building practices. As a member of key IEEE IES Technical Committees and a mentor in Harvard University’s mentorship program, she consistently fosters cutting-edge research and technological solutions. Dr. Alice Cervellieri’s work, recognized at top conferences and in SCOPUS-indexed publications, makes her a highly suitable candidate for the Best Researcher Award.

Training and Academic Path:

  • Degree in Civil Engineering – University of Engineering, Bologna (2005)
  • Master’s Degree in Civil Engineering – University of Engineering, Bologna (2011)
  • Degree in Science of Mediation Language – University of Scienze della Mediazione Linguistica (2019)

Academic Work Experience:

Dr. Alice Cervellieri is a multidisciplinary researcher and educator with extensive experience in architectural design, energy efficiency, agricultural mechanics, and dynamic simulations. She has contributed to various high-impact projects, including structural restoration and seismic engineering at the University of Engineering in Florence and the EU H2020 project “ENCORE” at the Polytechnic University of Marche, focusing on energy and comfort in residential buildings.

Dr. Cervellieri has served as a visiting professor at the Catholic University of Manizales in Colombia and mentored for the Harvard Mentorship Project since 2021. Her academic engagements include teaching the “Energy Certifier” course for Emilia Romagna Region and participating in prestigious summer schools at institutions such as the University of Warwick, IMT Lucca, and the University of Bologna. Dr. Cervellieri is also a certified translator for the Consulate of the Embassy of the Republic of Cuba and has completed professional training in digital transformation technologies through MIT.

International Involvement:

Dr. Alice Cervellieri is also involved in numerous international research projects, notably in Intelligent Transportation Systems (ITS) and building efficiency monitoring. She has presented her work at prestigious international conferences, including IEEE International Conferences and the AABC Europe Advanced Automotive Battery Conference.

Awards and Recognition:

Her multidisciplinary contributions highlight her dedication to innovation, sustainability, and academia. She continues to influence fields ranging from construction technology to AI-driven solutions in healthcare.

Assignments in International Committees:

Dr. Alice Cervellieri serves on key technical committees, such as IEEE IES Technical Committees on Factory Automation and Industrial Agents, where she contributes to the development of cutting-edge technologies in these sectors.

Professional Committees:

  • Member, IEEE IES Technical Committee on Factory Automation (2023–Present)
  • Member, IEEE IES Technical Committee on Industrial Agents (2023–Present)

Publications and Conferences:

Dr. Alice Cervellieri has presented at prestigious conferences such as IEEE ETFA, IEEE INDIN, and LASMCER and is a co-author of SCOPUS-indexed publications, including works on UAVs for infrastructure inspection, cyber-physical systems for building efficiency, and holonic management trees.

Publication Top Notes:

1. The Double Propeller Ducted-Fan, An UAV for Safe Infrastructure Inspection and Human-Interaction

  • Conference: IEEE International Conference on Emerging Technologies and Factory Automation (ETFA 2020)
  • Date: 08-11 September 2020
  • Authors: Bonci Andrea, Cervellieri Alice, Longhi Sauro, Nabissi Giacomo, Scala Giuseppe Antonio

2. Innovative Approach in Cyber Physical System for Building Efficiency Monitoring

  • Conference: IEEE International Conference on Emerging Technologies and Factory Automation (ETFA 2021)
  • Date: 07-10 September 2021
  • Authors: Bonci Andrea, Cervellieri Alice, Pirani Massimiliano

3. On the Synthesis of Holonic Management Trees

  • Conference: IEEE International Conference on Emerging Technologies and Factory Automation (ETFA 2021)
  • Date: 07-10 September 2021
  • Authors: Pirani Massimiliano, Bonci Andrea, Cervellieri Alice, Longhi Sauro

4. Brotweg—A Path of Bread in an Alpine Environment: New Mechanical Solutions for Grain Processing in Steep Mountain Slopes

  • Book Chapter: In Innovative Biosystems Engineering for Sustainable Agriculture, Forestry and Food Production: International Mid-Term Conference 2019 of the Italian Association of Agricultural Engineering (AIIA)
  • Publisher: Springer International Publishing
  • Authors: Sabrina Mayr, Riccardo Brozzi, Alice Cervellieri, Thomas Desaler, Raimondo Gallo, Josef Gamper, Bernhard Geier, Laurin Holzner, Pasqualina Sacco, Fabrizio Mazzetto

5. The Development of A Small Stripper Header for Cereal Harvesting in Steep Mountain Environments

  • Conference: In Biosystem Engineering for Sustainable Agriculture, Forestry and Food Production: International Mid-Term Conference 2019
  • Date: September 12-13 2019
  • Conference Proceedings: Unibas
  • Authors: Laurin Holzner, Riccardo Brozzi, Alice Cervellieri, Thomas Desaler, Raimondo Gallo, Josef Gamper, … & Fabrizio Mazzetto

6. A Lithium-Ion Battery Remaining Useful Life Prediction Method with the Invariant Capacity Analysis Based on a New Algorithm

  • Journal: Journal of Electrical System
  • Year: 2024
  • Authors: Cervellieri Alice

7. Advanced SOC Prediction for Lithium-Ion Batteries Using FNN Machine Learning Techniques: A Bayesian Regularization Training Approach

  • Journal: Journal of Electrical System
  • Year: 2024
  • Authors: Cervellieri Alice

8. Advanced State of Health Prediction for Lithium-Ion Batteries Using Capacity Estimation and Feedforward Neural Networks: A Machine Learning Approach

  • Journal: Journal of Electrical System
  • Year: 2024
  • Authors: Cervellieri Alice

9. A Feed-Forward Back-Propagation Neural Network Approach for Integration of Electric Vehicles into Vehicle-to-Grid (V2G) to Predict State of Charge for Lithium-Ion Batteries

  • Journal: Energies
  • Year: 2024
  • Authors: Cervellieri Alice

 

 

 

 

Dr. Haitham Adarbah | AI in Network Awards | Best Researcher Award

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Dr. Haitham Adarbah | AI in Network Awards | Best Researcher Award

Dr. Haitham Adarbah, Texas A&M University, United States

Dr. Haitham Adarbah is a Postdoctoral Researcher at Texas A&M University, Corpus Christi, specializing in communication protocols for autonomous vehicles with a focus on AI and 5G-6G technologies. He holds a Ph.D. in Wireless Networks from De Montfort University, UK, an M.Sc. in Computer Science from Amman Arab University, and a B.Sc. in Computer Science from AL-Zaytoonah University of Jordan. Dr. Adarbah’s research includes enhancing connectivity for autonomous vehicles and has previously explored vehicular networks, 5G, IoT, cloud computing, and AI as an IT Lecturer at Gulf College, Muscat. His significant publications address efficient broadcasting in mobile ad-hoc networks and security improvements in network protocols. With extensive teaching experience, he has mentored students and contributed to curriculum development in Computer Science.

🌍 Professional Profile:

Orcid
Google Scholar

Suitability for the Best Researcher Award

  1. Innovative Research: Dr. Adarbah’s research in advanced areas like 5G-6G connectivity, AI algorithms, and vehicular networks represents cutting-edge work in Computer Science. His focus on optimizing communication protocols and enhancing network performance is highly relevant and impactful.
  2. Publication Record: His publications in reputable journals and conferences reflect a strong research output and influence. The citations of his work indicate that his research is recognized and valued within the academic community.
  3. Cross-Disciplinary Contributions: Dr. Adarbah’s ability to integrate AI with wireless network technologies and his contributions to both theoretical and applied aspects of network research highlight his versatility and expertise in the field.
  4. Teaching and Mentorship: His long-standing teaching experience and dedication to mentoring students demonstrate his commitment to academic excellence and the development of future researchers.
  5. Professional Development: His role in preparing grant proposals and collaborating with industry partners underscores his active engagement in advancing research and securing funding.

🎓 Education:

Dr. Haitham Adarbah is a Postdoctoral Researcher at Texas A&M University, Corpus Christi, specializing in communication protocols for autonomous vehicles with a focus on AI and 5G-6G technologies. He earned his PhD in Wireless Networks from De Montfort University, UK, with research on bandwidth and energy-efficient route discovery. He also holds an M.Sc. in Computer Science from Amman Arab University and a B.Sc. in Computer Science from AL-Zaytoonah University of Jordan.

📚 Academic and Research Experience:

Currently, Dr. Adarbah engages in cutting-edge research on enhancing connectivity for autonomous vehicles at Texas A&M University. His previous role as an IT Lecturer at Gulf College, Muscat, involved teaching and researching in areas such as vehicular networks, 5G, IoT, cloud computing, and AI.

📝 Research Achievements:

Dr. Adarbah’s notable publications include works on efficient broadcasting in mobile ad-hoc networks, the impact of carrier sensing on route discovery, and security improvements in network protocols. His research interests span route discovery mechanisms, noise impact in broadcasting, vehicular networks, and AI applications in wireless technologies.

👨‍🏫 Teaching and Mentorship:

With extensive teaching experience, Dr. Adarbah has mentored students in research and contributed to curriculum design and development across a range of Computer Science subjects.

Publication Top Notes:

  • Title: Efficient Broadcasting for Route Discovery in Mobile Ad-Hoc Networks
    • Year: 2015
    • Citations: 14
  • Title: Impact of Physical and Virtual Carrier Sensing on the Route Discovery Mechanism in Noisy MANETs
    • Year: 2013
    • Citations: 12
  • Title: Impact of Noise and Interference on Probabilistic Broadcast Schemes in Mobile Ad-Hoc Networks
    • Year: 2015
    • Citations: 10
  • Title: Security Challenges of Selective Forwarding Attack and Design a Secure ECDH-Based Authentication Protocol to Improve RPL Security
    • Year: 2022
    • Citations: 6
  • Title: Impact of the Noise Level on the Route Discovery Mechanism in Noisy MANETs
    • Year: 2012
    • Citations: 5

 

 

 

 

 

Assoc Prof Dr. Lun Zhao | AI in Network Award | Best Researcher Award

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Assoc Prof Dr. Lun Zhao | AI in Network Award | Best Researcher Award

Assoc Prof Dr. Lun Zhao, Shenzhen Polytechnic University, China

Dr. Lun Zhao, a distinguished academic and researcher at Shenzhen Polytechnic University, China 🇨🇳, holds dual Ph.D. degrees in Mechanical Engineering from Blekinge Institute of Technology, Sweden, and in Mechanical and Electrical Engineering from Kunming University of Science and Technology, China 🎓. As a Distinguished Associate Researcher at the Institute of Intelligent Manufacturing Technology since 2022, Dr. Zhao has made significant strides in intelligent manufacturing, publishing over 70 academic papers, including 8 in JCR Area 1 journals 📚. He has also been granted 4 authorized invention patents. Dr. Zhao leads the Intelligent Connection New Technology R&D Team and directs several key research centers. His outstanding contributions have earned him recognitions such as the Shenzhen Overseas High-Level Talent Introduction “Peacock Plan Category C” 🏆. He has also hosted and participated in numerous research projects worth over 10 million RMB, demonstrating his expertise and leadership in the field 🌟.

🌐 Professional Profile:

Scopus

🎓 Educational Background

  • Ph.D. in Mechanical Engineering: Blekinge Institute of Technology, Sweden (2015.12-2017.1)
  • Ph.D. in Mechanical and Electrical Engineering: Kunming University of Science and Technology, China (2012.09-2018.06)

💼 Professional Experience

  • Distinguished Associate Researcher: Institute of Intelligent Manufacturing Technology, Shenzhen Polytechnic University (2022.7–present)
  • Secondment: Shenzhen Municipal Science and Technology Innovation Commission Major Special Project Division (2022.12-2023.8)
  • Postdoctoral Fellow: Institute of Integration, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences (2020.9–2022.6)
  • Distinguished Associate Professor: School of Mechanical Engineering, Guizhou University (2018.9-2020.7)

📚 Academic Contributions

Dr. Zhao Lun has made significant contributions to the field of intelligent manufacturing. He has published over 70 academic papers, with 8 in JCR Area 1 journals. He has been granted 4 authorized invention patents and has supervised numerous postgraduate students, including 3 postdoctoral, 3 doctoral, and over 30 master’s students.

🏆 Achievements and Roles

  • Leader: Intelligent Connection New Technology R&D Team
  • Director: Shenzhen Vocational College-Guangzhou Xindongli Ultrasonic Welding R&D Center
  • Director: Shenzhen Vocational College-Guangdong Haimingsheng Intelligent Connection Joint Laboratory
  • Postdoctoral Supervisor
  • External Tutor: Tsinghua University Shenzhen International Graduate School

🌟 Recognitions and Awards

  • Shenzhen Overseas High-Level Talent Introduction “Peacock Plan Category C”
  • Hosted and participated in research projects: Worth over 10 million RMB, including the 2022 National Key R&D Plan of the Ministry of Science and Technology, National Natural Science Foundation Youth Fund Project, China Postdoctoral Fund General Project, and Shenzhen High-end Talent Scientific Research Startup Project.

Publication Top Notes:

  • Numerical and experimental investigation of an Archimedes screw turbine for open channel water flow application
  • A Deep Convolutional Neural Network-Based Method for Self-Piercing Rivet Joint Defect Detection
  • Mechanical properties of ultrasonic welded and self-piercing riveted joints in a 5A06 aluminum alloy and a TA1 titanium alloy
  • Influence of Patterns on Mechanical Properties of Ultrasonically Welded Joints in Copper Substrate and Wire
  • Numerical study on the injection strategy on combustion and emission characteristics of a non-road diesel engine under different altitude conditions