Prof. Dr. Xin Wang | Distributed AI | Best Researcher Award

Prof. Dr. Xin Wang | Distributed AI | Best Researcher Award

Prof. Dr. Xin Wang, Qilu University of Technology, China

Prof. Dr. Xin Wang is a distinguished scholar in Distributed AI and Federated Learning, currently serving as a Professor at Shandong Computer Science Center, Qilu University of Technology. With a Ph.D. in Control Science and Engineering from Zhejiang University, he has contributed significantly to AI Security, Privacy, and LLM Security. Dr. Wang has led multiple national research projects and received prestigious honors, including the Taishan Scholars Award and the Shandong Provincial Science and Technology Progress Award. His work integrates AI with secure computing, enhancing privacy protection and optimization in collaborative learning systems.

🌍 Professional Profile:

Google Scholar

🏆 Suitability for Award 

Dr. Xin Wang’s outstanding contributions to Distributed AI, Federated Learning, and AI Security make him a strong candidate for the Best Researcher Award. As a leader in AI-driven security frameworks, he has spearheaded national-level projects focusing on privacy-preserving AI and secure learning models. His research bridges theory with practical applications, enhancing security in multi-agent and industrial IoT systems. Recognized for his high-impact publications and award-winning research, Dr. Wang’s innovations in cryptographic function identification and UAV data collection optimization demonstrate exceptional originality and real-world relevance, solidifying his place as a leader in computational intelligence and AI security.

🎓 Education 

  • Ph.D. in Control Science and Engineering (2015-2020) – Zhejiang University, supervised by Prof. Peng Cheng & Prof. Jiming Chen, specializing in AI Security and Distributed Intelligence.
  • Visiting Scholar in Information Security (2018-2019) – Tokyo Institute of Technology, mentored by Prof. Hideaki Ishii, focusing on cryptographic vulnerabilities and federated learning security.

His multidisciplinary training across AI, security, and automation has positioned him at the forefront of cutting-edge computational research.

💼 Experience 

  • Professor (2024–Present) – Shandong Computer Science Center, Qilu University of Technology.
  • Associate Professor (2020–2024) – Shandong Computer Science Center, leading research on privacy protection in collaborative AI.
  • Project PI in National Natural Science Foundation of China (2025-2027) – Developing privacy-preserving defense mechanisms for federated learning.
  • Project PI in National Key Research and Development Program (2021-2024) – Developing AI-driven meta-services for cloud-based industrial manufacturing.
  • Visiting Scholar (2018-2019) – Tokyo Institute of Technology, conducting security research on cryptographic vulnerabilities in multi-agent IoT systems.

🏅 Awards and Honors 

  • Taishan Scholars Award (2024) 🏅 – Recognized for research excellence in AI security and distributed systems.
  • Leader of Youth Innovation Team (2022) 🚀 – Acknowledged for driving innovation in Shandong Higher Education Institutions.
  • Second Prize, Shandong Provincial Science and Technology Progress Award (2022) 🏆 – Contributions to federated learning and privacy-preserving AI.
  • Best Paper Award, CCSICC’21 📄 – Vulnerability Analysis for IoT Devices in Multi-Agent Systems.
  • Best Paper Award, ICAUS’24 ✈️ – Optimized Data Collection for UAVs in Industrial IoT Environments.

🔬 Research Focus 

Dr. Wang specializes in Distributed AI, Federated Learning, and AI Security & Privacy. His research integrates cryptographic techniques, optimization algorithms, and adversarial defenses to improve the security of collaborative learning models. He has pioneered LLM security frameworks to safeguard against data leakage and adversarial attacks. His work extends into privacy-preserving AI for multi-agent IoT systems and UAV data collection efficiency. Through national projects, he has developed secure meta-services for cloud computing, advancing the field of intelligent automation and resilient AI architectures for real-world deployment in cyber-physical systems and industrial environments.

📊 Publication Top notes:

  • Title: Privacy-Preserving Distributed Machine Learning via Local Randomization and ADMM Perturbation
    • Year: 2020
    • Citations: 61
  • Title: Privacy-Preserving Collaborative Computing: Heterogeneous Privacy Guarantee and Efficient Incentive Mechanism
    • Year: 2018
    • Citations: 49
  • Title: Differentially Private Maximum Consensus: Design, Analysis and Impossibility Result
    • Year: 2018
    • Citations: 26
  • Title: Dynamic Privacy-Aware Collaborative Schemes for Average Computation: A Multi-Time Reporting Case
    • Year: 2021
    • Citations: 18
  • Title: Leveraging UAV-RIS Reflects to Improve the Security Performance of Wireless Network Systems
    • Year: 2023
    • Citations: 17

 

Dr. Alice Cervellieri | AI Network | Best Researcher Award

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