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 AIย 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.

๐ŸŒย Professional Profile:

Google Scholar

๐Ÿ† Suitability for Awardย 

Dr. Xin Wangโ€™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. Wangโ€™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.

๐ŸŽ“ Educationย 

  • Ph.D. in Control Science and Engineering (2015-2020) โ€“ Zhejiang University, supervised by Prof. Peng Cheng & Prof. Jiming Chen, specializing in AI Security and Distributed Intelligence.
  • Visiting Scholar in Information Security (2018-2019) โ€“ 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.

๐Ÿ’ผ Experienceย 

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

๐Ÿ… Awards and Honorsย 

  • Taishan Scholars Award (2024) ๐Ÿ… โ€“ Recognized for research excellence in AI security and distributed systems.
  • Leader of Youth Innovation Team (2022) ๐Ÿš€ โ€“ Acknowledged for driving innovation in Shandong Higher Education Institutions.
  • Second Prize, Shandong Provincial Science and Technology Progress Award (2022) ๐Ÿ† โ€“ Contributions to federated learning and privacy-preserving AI.
  • Best Paper Award, CCSICCโ€™21 ๐Ÿ“„ โ€“ Vulnerability Analysis for IoT Devices in Multi-Agent Systems.
  • Best Paper Award, ICAUSโ€™24 โœˆ๏ธ โ€“ Optimized Data Collection for UAVs in Industrial IoT Environments.

๐Ÿ”ฌ Research Focusย 

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.

๐Ÿ“Š 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

 

Mr. Ashok Yadav | Computational Intelligence | Best Researcher Award

Mr. Ashok Yadav | Computational Intelligence | Best Researcher Award

Mr. Ashok Yadav, Indian Institute of Information Technology Allahabad, India

Mr. Ashok Yadav is a distinguished researcher in the field of cybersecurity, natural language processing (NLP), social network analysis, and offensive content detection. He holds a Ph.D. from the Indian Institute of Information Technology Allahabad, where his thesis focused on detecting and countering offensive content. Mr. Yadav also completed his M.Tech. in Cyber Security from AKTU Lucknow, specializing in intrusion detection and prevention in wireless sensor networks. He holds a B.Tech. in Computer Science from the School of Management Sciences, Lucknow. With a deep interest in cybercrime, OSINT (Open Source Intelligence), and hate speech, Mr. Yadav has contributed significantly to the academic and practical understanding of these areas. His work spans across multiple domains, including deep learning, computational intelligence, and social media networks. Mr. Yadav is actively involved in academic conferences and serves as a reviewer for several prestigious journals. ๐Ÿ–ฅ๏ธ๐Ÿ”๐Ÿ“š

Professional Profile

Google Scholar

Suitability for Awardย 

Mr. Ashok Yadav is highly suitable for the Research for Best Researcher Award due to his outstanding contributions to cybersecurity, NLP, and social network analysis. His research on offensive content detection, tracking, and counter-generation has had a significant impact on mitigating cyber threats and addressing harmful speech on digital platforms. Mr. Yadavโ€™s deep understanding of emerging technologies such as deep learning, OSINT, and computational intelligence positions him as a leader in his field. His active participation in global conferences like the ACL and his role as a reviewer for notable journals further highlight his academic influence. Mr. Yadavโ€™s commitment to advancing cybersecurity and his contributions to combating hate speech and cybercrime make him a deserving candidate for this prestigious award. His research not only addresses current challenges in cybersecurity but also provides innovative solutions for the future. ๐Ÿ†๐Ÿ’ป๐ŸŒ

Education

Mr. Ashok Yadav has a strong academic background, with a focus on cybersecurity, NLP, and social network analysis. He completed his Ph.D. in Computer Science from the Indian Institute of Information Technology Allahabad in 2021, specializing in offensive content detection and tracking. His doctoral thesis, titled Offensive Content Detection, Tracking, and Counter Generation, reflects his expertise in combating harmful speech in digital environments. Prior to his Ph.D., Mr. Yadav earned an M.Tech. in Cyber Security from AKTU Lucknow, where his research on intrusion detection and prevention in wireless sensor networks earned recognition. He also holds a B.Tech. in Computer Science from the School of Management Sciences, Lucknow. Mr. Yadavโ€™s academic journey is complemented by certifications from the SANS Institute, including training in Cyber Threat Intelligence, Digital Forensics, and Open-Source Intelligence. His educational background has equipped him with a deep understanding of both theoretical and practical aspects of cybersecurity. ๐ŸŽ“๐Ÿ’ก๐Ÿ”

Experienceย 

Mr. Ashok Yadav has extensive experience in both academia and industry, particularly in the fields of cybersecurity, NLP, and social network analysis. He is currently pursuing advanced research in offensive content detection, hate speech, and cybercrime. His professional journey includes serving as a reviewer for several prestigious journals, such as the Cloud Computing and Data Science Journal and the International Research Journal of Multidisciplinary Technovation. Mr. Yadav has also been actively involved in international conferences, including the 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024), where he contributed to the main track and demonstration track. He has attended various SANS Institute training summits, enhancing his expertise in Cyber Threat Intelligence, Digital Forensics, and Open-Source Intelligence. Mr. Yadavโ€™s practical experience in cybersecurity and his contributions to the academic community make him a valuable asset in his field. ๐Ÿ’ผ๐ŸŒ๐Ÿ”

Awards and Honors

Mr. Ashok Yadav has received several prestigious certifications and accolades for his contributions to cybersecurity and digital forensics. He was awarded the Gate Qualification in Computer Science and Information Technology in 2019, demonstrating his expertise in the field. In 2020, he qualified for the UGC-Net Assistant Professor in Computer Science and Application. Mr. Yadavโ€™s active participation in high-profile conferences such as the 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024), where he was an attendee, further highlights his academic recognition. He has also been recognized for his contributions as a reviewer for prominent journals, including the Cloud Computing and Data Science Journal and the International Research Journal of Multidisciplinary Technovation. Additionally, Mr. Yadav has earned multiple certifications from the SANS Institute in Cyber Threat Intelligence, Digital Forensics, and Open-Source Intelligence, further solidifying his standing in the cybersecurity community. ๐Ÿ…๐ŸŽ–๏ธ๐ŸŒŸ

Research Focusย 

Mr. Ashok Yadavโ€™s research focus lies at the intersection of cybersecurity, natural language processing (NLP), social network analysis, and offensive content detection. His work on detecting and countering hate speech and offensive content on digital platforms addresses a growing concern in todayโ€™s internet-driven society. His Ph.D. research on Offensive Content Detection, Tracking, and Counter Generation has contributed significantly to the development of automated systems that can identify and mitigate harmful speech online. Mr. Yadav is also deeply involved in exploring the use of deep learning, computational intelligence, and OSINT (Open-Source Intelligence) in the detection of cyber threats and cybercrime. His research aims to create innovative solutions for tackling the challenges posed by cyberattacks, misinformation, and online hate speech. Through his work, Mr. Yadav seeks to enhance the security and integrity of online spaces, making them safer for users. ๐Ÿ”๐Ÿ’ป๐Ÿง 

Publication Top Notes

  • Title: Open-source Intelligence: A Comprehensive Review of the Current State, Applications, and Future Perspectives in Cyber Security
    • Cited by: 32
    • Year: 2023
  • Title: Intrusion Detection and Prevention Using RNN in WSN
    • Cited by: 12
    • Year: 2022
  • Title: Detecting SQL Injection Attack Using Natural Language Processing
    • Cited by: 8
    • Year: 2022
  • Title: Detecting Malware in Android Applications by Using Androguard Tool and XGBoost Algorithm
    • Cited by: 2
    • Year: 2022
  • Title: HateFusion: Harnessing Attention-Based Techniques for Enhanced Filtering and Detection of Implicit Hate Speech
    • Year: 2024

 

Ms. Nathalia Hidalgo Leite | Artificial Neural Networks | Best Researcher Award

Ms. Nathalia Hidalgo Leite | Artificial Neural Networks | Best Researcher Award

Ms. Nathalia Hidalgo Leite, State University of Campinas, Brazil

๐ŸŽ“ Nathalia Hidalgo Leite is a Ph.D. candidate in Energy Systems Planning at the State University of Campinas (Unicamp) ๐Ÿ‡ง๐Ÿ‡ท, focusing on electric mobility. She also holds an MBA in Value Investing from UniBTA and an M.S. in Energy Systems Planning from Unicamp, and a B.S. in Agronomic Engineering from UFSCar ๐ŸŒฑ. As a researcher at CPTEn and CPFL Energy, and an instructor at Unicamp, she has contributed significantly to energy systems planning and education. Her international academic experience includes programs in Portugal ๐Ÿ‡ต๐Ÿ‡น, Denmark ๐Ÿ‡ฉ๐Ÿ‡ฐ, Spain ๐Ÿ‡ช๐Ÿ‡ธ, Italy ๐Ÿ‡ฎ๐Ÿ‡น, and the USA ๐Ÿ‡บ๐Ÿ‡ธ. Nathalia’s research interests span the economic and financial viability of energy systems, artificial neural networks, and renewable energy integration ๐ŸŒž. Proficient in Portuguese, English, and Spanish, she holds numerous certifications in finance and technical skills ๐Ÿ“Š. Her achievements are recognized by multiple academic and extracurricular awards, underscoring her dedication and multifaceted talents ๐ŸŒŸ.

๐ŸŒ Professional Profile:

Google Scholar

๐ŸŽ“ Educational Background

Nathalia Hidalgo Leite is currently pursuing a Ph.D. in Energy Systems Planning at the State University of Campinas (Unicamp) ๐Ÿ‡ง๐Ÿ‡ท, focusing on the economic and financial viability for electric mobility. She also holds an MBA in Value Investing from UniBTA and an M.S. in Energy Systems Planning from Unicamp, where she studied the economic viability of photovoltaic solar energy. Nathalia completed her B.S. in Agronomic Engineering at the Federal University of Sao Carlos (UFSCar), researching artificial neural networks applied to Asian soybean rust ๐ŸŒฑ.

๐Ÿข Professional Experience

Nathalia is an accomplished researcher and instructor. At Unicamp, she has taught courses in computer algorithms, programming, numerical calculation, and discrete mathematics. As a researcher at the Sao Paulo Center for Energy Transition Studies (CPTEn) and previously at CPFL Energy, she has made significant contributions to energy systems planning. Nathalia also worked as a Financial Planning and Analysis Specialist at Grupo JLJ and interned at Ecomark Indรบstria e Comรฉrcio de Fertilizantes Especiais Ltda ๐ŸŒŸ.

๐ŸŒ International Experience

Nathalia has enriched her academic journey with several exchange programs. She spent six months at the University of Lisbon ๐Ÿ‡ต๐Ÿ‡น and the University of Southern Denmark ๐Ÿ‡ฉ๐Ÿ‡ฐ, three months at Universitat Politรจcnica de Valรจncia ๐Ÿ‡ช๐Ÿ‡ธ, one month at Universitร  degli Studi di Roma La Sapienza ๐Ÿ‡ฎ๐Ÿ‡น, and also attended Beverly Hills High School ๐Ÿ‡บ๐Ÿ‡ธ and Moore Elementary School in Colorado ๐Ÿ‡บ๐Ÿ‡ธ during her earlier education ๐Ÿ“š.

๐Ÿ“ Research Interests

Nathalia’s research interests include the economic and financial viability of energy systems, artificial neural networks, and the integration of renewable energy sources. She is particularly focused on interdisciplinary approaches to solving complex problems in energy planning and sustainability ๐ŸŒž.

๐ŸŒ Certifications and Skills

Nathalia holds numerous certifications in finance, photovoltaic systems, scientific writing, and programming. She is proficient in Portuguese (native), English (fluent), and Spanish (advanced). Her technical skills and continuous learning make her a versatile and knowledgeable professional in her field ๐Ÿ“Š.

๐Ÿ† Awards and Recognitions

Nathalia has received several awards for academic and extracurricular excellence, including the Excellence in Academic Performance award from Anglo Middle School ๐Ÿ‡ง๐Ÿ‡ท and multiple accolades from Lincoln Junior High School ๐Ÿ‡บ๐Ÿ‡ธ for academic achievement, athletic performance, and leadership. These recognitions highlight her dedication and multifaceted talents ๐ŸŒŸ.

Publication Top Notes:

1. ย Artificial Neural Networks Applied to Plant Disease
2. ย Study of Asian Soybean Rust

 

 

Assoc Prof Dr. Yuchuan Fu | AI in Network | Best Researcher Award

Assoc Prof Dr. Yuchuan Fu | AI in Network | Best Researcher Award

Assoc Prof Dr. Yuchuan Fu, Xidian University, China

๐Ÿ‘ฉโ€๐ŸŽ“ Dr. Yuchuan Fu, a Ph.D. graduate in Telecommunications Engineering from Xidian University (2020), is currently an Associate Professor at Xidian University’s School of Telecommunications Engineering. She pursued joint Ph.D. studies at Carleton University, Canada, and has garnered acclaim for her 47 publications in esteemed journals and conferences, earning accolades such as the Outstanding Doctoral Thesis Award and the Best Paper Award at DIVANet’23. Her expertise lies in Artificial Intelligence for Internet of Vehicles and Intelligent Transportation Systems, with notable contributions recognized by prestigious entities like the China Electronics Education Society. Dr. Fu’s impactful research, including 2 ESI highly cited papers and 1 hot paper, underscores her commitment to advancing telecommunications. ๐Ÿ†๐Ÿ”๐Ÿ“š

๐ŸŒย Professional Profiles :

Scopus

Google Scholar

๐ŸŽ“ Education:

Dr. Yuchuan Fu received her Ph.D. degree from Xidian University, China, in Telecommunications Engineering in 2020.

๐Ÿ‘ฉโ€๐Ÿ’ผ Experience:

She is currently serving as an Associate Professor at the School of Telecommunications Engineering, Xidian University, Shaanxi, China. Dr. Fu was a joint Ph.D. student with Carleton University, Canada, from 2018 to 2019.

๐Ÿ† Achievements:

Dr. Fu’s research interests include AI for Internet of Vehicles, Internet of Things, and Intelligent Transportation Systems. She has published 47 papers in prestigious journals and conferences, with several being highly cited. Her research has earned her recognition through numerous awards, including the Outstanding Doctoral Thesis Award and Best Paper Awards at international conferences.

๐Ÿ”ฌ Research Focus:

Her current academic focus lies in the areas of Internet of Vehicles and Intelligent Transportation Systems.

๐Ÿ“š Notable Honors:

  • Outstanding Doctoral Thesis Award (China Electronics Education Society, 2020)
  • Outstanding Achievement Award (Special Prize, Shaanxi Higher Education Institutions Science and Technology Research, 2022)
  • Best Paper Award (DIVANetโ€™23 International Conference)
  • Best Demo Award Winner (12th NEEE/CIC International Conference on Communications in China)
  • Best Student Paper Award (ADHOCNETS 2018 International Conference)

๐Ÿ“šย Publication Impact and Citations :

Scopus Metrics:

  • ๐Ÿ“ย Publications: 45 documents indexed in Scopus.
  • ๐Ÿ“Šย Citations: A total of 648 citations for his publications, reflecting the widespread impact and recognition of Dr. Yuchuan Fuโ€™s research within the academic community.

Google Scholar Metrics:

  • All Time:
    • Citations: 911 ๐Ÿ“–
    • h-index: 15ย  ๐Ÿ“Š
    • i10-index: 18 ๐Ÿ”
  • Since 2018:
    • Citations: 899 ๐Ÿ“–
    • h-index: 15 ๐Ÿ“Š
    • i10-index: 18 ๐Ÿ”

๐Ÿ‘จโ€๐Ÿซ A prolific researcher with significant impact and contributions in the field, as evidenced by citation metrics. ๐ŸŒ๐Ÿ”ฌ

Publications Top Notes :

  1. Vehicle position correction: A vehicular blockchain networks-based GPS error sharing framework
    • Published in IEEE Transactions on Intelligent Transportation Systems in 2020.
    • 113 citations.
  2. A decision-making strategy for vehicle autonomous braking in emergency via deep reinforcement learning
    • Published in IEEE Transactions on Vehicular Technology in 2020.
    • 100 citations.
  3. Vehicular blockchain-based collective learning for connected and autonomous vehicles
    • Published in IEEE Wireless Communications in 2020.
    • 95 citations.
  4. A mobility-aware vehicular caching scheme in content centric networks: Model and optimization
    • Published in IEEE Transactions on Vehicular Technology in 2019.
    • 90 citations.
  5. A survey of blockchain and intelligent networking for the metaverse
    • Published in IEEE Internet of Things Journal in 2022.
    • 78 citations.

 

 

 

 

 

 

 

 

Prof. Subir Das | Neural Networks | Best Researcher Award

Prof. Subir Das | Neural Networks | Best Researcher Award

Prof.Subir Das, Indian Institute of Technology (BHU) Varanasi, India

Prof. Subir Das is a distinguished Professor in the Department of Mathematical Sciences at the Indian Institute of Technology (BHU), Varanasi, India. Additionally, he holds the position of Visiting Professor at UCSI University in Kuala Lumpur, Malaysia. With a solid educational background, Subir earned his M.Sc. in Applied Mathematics and subsequently completed his Ph.D. in Science, being honored with the Griffith Memorial Award in Science from the University of Calcutta in 2001. Renowned for his expertise, Subir’s research interests span diverse areas such as Fracture Mechanics, Fractional Calculus, Mathematical Modeling, and Nonlinear Dynamics. His significant contributions to these fields have earned him recognition, including being listed among the world’s top 2% scientists in a global database curated by Stanford University, California, USA. With a passion for advancing mathematical sciences, Subir Das continues to leave an indelible mark in his academic journey.

๐ŸŒย Professional Profile:

Scopus

Orcid

Google Scholar

๐ŸŽ“ Education:

  • M. Sc. (Applied Mathematics)
  • Ph. D. (Science)
  • Recipient of the Griffith Memorial Award in Science from the University of Calcutta in 2001.

๐Ÿ” Research Interests:

  • Fracture Mechanics
  • Fractional Calculus
  • Mathematical Modelling
  • Nonlinear Dynamics

๐ŸŒ Recognition:

  • Listed among the WORLD’S TOP 2% SCIENTISTS in a world database created by Stanford University, California, USA.

๐Ÿ† Awards:

He was honored with the Griffith Memorial Award in Science by the University of Calcutta in 2001, recognizing his outstanding contributions to the field.

๐Ÿ”ฌ Research Focus:

Prof. Das has made significant contributions to various areas, including Fracture Mechanics, Fractional Calculus, Mathematical Modelling, and Nonlinear Dynamics. His research reflects a deep understanding of these subjects and contributes to advancements in the mathematical sciences

๐Ÿ“šย Publication Impact and Citations :

Scopus Metrics:

  • ๐Ÿ“ย Publications: 186 documents indexed in Scopus.
  • ๐Ÿ“Šย Citations: A total of 3,164 citations for his publications, reflecting the widespread impact and recognition of Prof. Subir Dasโ€™s research within the academic community.

Google Scholar Metrics:

  • All Time:
    • Citations: 4167 ๐Ÿ“–
    • h-index: 33 ๐Ÿ“Š
    • i10-index: 104 ๐Ÿ”
  • Since 2018:
    • Citations: 2327 ๐Ÿ“–
    • h-index: 24 ๐Ÿ“Š
    • i10-index: 74 ๐Ÿ”

๐Ÿ‘จโ€๐Ÿซ A prolific researcher with significant impact and contributions in the field, as evidenced by citation metrics. ๐ŸŒ๐Ÿ”ฌ

Publicationย  ย Topย  Notes: