FAN Bo | Data Security Management | Best Researcher Award

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Dr. FAN Bo | Data Security Management | Best Researcher Award

Senior Engineer at Southwest Jiaotong University, China

Dr. Fan Bo is a Senior Engineer and Chief Technical Specialist at the National Engineering Laboratory for Industrial Big Data Application Technology in China. With a Ph.D. and extensive experience in industrial innovation, he also serves as a project manager for the Ministry of Science and Technology’s Key Field Innovation Team and a technical expert for Chongqing Iron & Steel Electronic Co., Ltd. Dr. Fan has participated in over ten national R&D programs, published more than ten research papers, filed ten invention patents, and contributed to national and industrial standards. His groundbreaking work in data governance, business data modeling, and multi-value-chain distributed data spaces has benefited thousands of enterprises, earning him prestigious awards and international recognition.

 

Profile

ORCID

Education

Dr. Fan Bo has a strong academic foundation that underpins his expertise in industrial big data and digital transformation technologies. He earned his Ph.D. in a specialized field, equipping him with advanced knowledge and research skills crucial for tackling complex engineering and technological challenges. His academic journey reflects a commitment to excellence and a focus on integrating theoretical insights with practical applications, which has significantly contributed to his professional accomplishments in industrial innovation and data science.

 Experience

Dr. Fan Bo has a distinguished career marked by leadership and innovation in industrial big data and digital transformation. As Chief Technical Specialist at the National Engineering Laboratory for Industrial Big Data Application Technology, he oversees key technological advancements. He has participated in over ten national R&D programs, including leading a sub-project, and directed four key R&D initiatives in Sichuan Province. Additionally, Dr. Fan managed two horizontal digital transformation projects for China’s National Pipeline Group during the 13th and 14th Five-Year Plans. His concurrent roles as project manager for the Ministry of Science and Technology’s Key Field Innovation Team and technical expert for Chongqing Iron & Steel Electronic Co., Ltd. highlight his multifaceted expertise and ability to drive impactful projects in the field.

Research Interests

Dr. Fan Bo’s research interests focus on the application of industrial big data, data governance, and digital transformation technologies. He is particularly interested in the development and implementation of data governance platforms, business data models, and multi-value-chain distributed data spaces. His work aims to optimize industrial processes through innovative data solutions, particularly in the manufacturing and automotive sectors. Dr. Fan’s research also explores the integration of cloud service technologies and scenario-oriented business models to enhance efficiency and drive economic benefits for industrial enterprises. His contributions continue to shape the future of industrial data applications and digital innovation.

Skills

Dr. Fan Bo possesses a wide range of technical and leadership skills that have contributed to his success in industrial big data and digital transformation. He is highly skilled in data governance, designing and implementing complex data platforms, and developing business data models tailored to specific industrial scenarios. His expertise also extends to multi-value-chain distributed data spaces, enabling optimized data utilization across various industries, particularly in manufacturing and automotive sectors. Additionally, Dr. Fan has strong project management abilities, having led multiple high-impact initiatives under national R&D programs and major industrial projects. His proficiency in cloud service technologies, technical standard development, and innovation in digital transformation underscores his versatility and ability to drive technological advancements.

 

Publication

Title: Optimal Selection Technology of Business Data Resources for Multi-Value Chain Data Space—Optimizing Future Data Management Methods

  • Authors: Bo Fan, Linfu Sun, Dong Tan, Meng Pan
  • Journal: Electronics
  • Volume: 13
  • Issue: 23
  • Article Number: 4690
  • DOI: 10.3390/electronics13234690
  • Year: 2024

Conclusion

Dr. Fan Bo’s substantial research, innovation, and leadership in advancing industrial big data applications make him a deserving candidate for the Research for Best Researcher Award. His contributions not only address critical challenges in digital transformation but also generate tangible economic and industrial benefits, solidifying his position as a leading figure in his field.

Reza Fotohi | Privacy-Preserving | Best Researcher Award

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Dr. Reza Fotohi | Privacy-Preserving | Best Researcher Award

University Professor at Shahid Beheshti University, Iran

Summary:

Dr. Reza Fotohi is a Ph.D. candidate in Computer Software Engineering at Shahid Beheshti University (SBU) in Tehran, Iran. His research specializes in privacy-preserving data collection and analysis, privacy-preserving machine learning, and federated learning. Reza has made significant contributions to his field, with multiple publications in high-ranking journals and over 1196 citations, resulting in an h-index of 24 and an i10-index of 29. Reza’s academic journey includes an M.Sc. in Computer Software Engineering from the Islamic Azad University of Shabestar and a B.Sc. from the University of Applied Science and Technology in East Azerbaijan, Iran. His work has been recognized with numerous awards, including being named among the top 2% of researchers worldwide by Stanford University and receiving fellowships and outstanding student awards throughout his academic career. Currently, Reza is researching data privacy in intelligent enterprises, continuing to advance the frontiers of privacy-preserving technologies.

Profile:

Education:

Reza Fotohi is pursuing his Ph.D. in Computer Software Engineering at Shahid Beheshti University (SBU) in Tehran Province, Iran, from September 2019 to September 2023. He has achieved a GPA of 19.0/20, with coursework including Advanced Software Engineering, Self-adapting and Self-organize Systems, Advanced Network Security, and Ultra Large Scale Systems. His thesis, supervised by Dr. Fereidoon Shams Aliee and advised by Dr. Bahar Farahani, focuses on “A Lightweight Model for Privacy-Preserving of Data in Intelligent Enterprises.” Reza obtained his M.Sc. in Computer Software Engineering from the Islamic Azad University of Shabestar (IAU) in East Azerbaijan Province, Iran, between September 2012 and February 2014. He graduated with a GPA of 18.49/20, completing coursework such as Advanced Topics in Software Engineering, Advanced Operating System, Advanced Computer Networks, and Distributed Systems. His thesis, titled “DAWA: Defending against Wormhole Attack in MANETs by Using Fuzzy Logic and Artificial Immune System,” was supervised by Dr. Shahram Jamalie and advised by Dr. Morteza Analouei. He earned his B.Sc. in Computer Software Engineering from the University of Applied Science and Technology (UAST) in East Azerbaijan Province, Iran, from September 2007 to February 2010. Reza’s GPA was 17.37/20, and his coursework included Algorithm Design, Internet Engineering, Computer Simulation, and Network Installation and Configuration. His research project on Service Oriented Architecture (SOA) was supervised by Dr. Hadi Mikaeili and advised by Dr. Kambiz Fakhr.

Professional Experience:

Dr. Reza Fotohi is a dedicated researcher and academic in the field of Computer Software Engineering. During his Ph.D. at Shahid Beheshti University (SBU), he has served as a Teaching Assistant for the Ultra Large Scale Systems course in the winters of 2021 and 2022. Additionally, he worked as a Research Assistant in the winter of 2022, where he focused on privacy-preserving data collection and analysis, and privacy-preserving machine learning. His thesis, titled “A Lightweight Model for Privacy-Preserving of Data in Intelligent Enterprises,” is supervised by Dr. Fereidoon Shams Aliee and advised by Dr. Bahar Farahani. Throughout his academic career, Reza has published numerous papers in high-ranking journals, earning over 1196 citations with an h-index of 24 and an i10-index of 29. His research contributions have earned him recognition among the top 2% of researchers worldwide by Stanford University. He has also received several awards and fellowships, highlighting his excellence in research and academia.

Research Interests:

Dr. Reza Fotohi’s research interests lie at the intersection of privacy and data science, with a focus on privacy-preserving data collection and analysis, privacy-preserving machine learning, and federated learning. He is particularly interested in developing and implementing techniques that protect sensitive information in intelligent enterprises, ensuring data privacy while maintaining the utility and effectiveness of data-driven applications. His current research explores lightweight models for privacy-preserving data management, aiming to advance the field by creating more secure and efficient systems for handling private data in various applications.

Honors & Awards:

Dr. Reza Fotohi has been recognized among the top 2% of researchers worldwide by Stanford University for the academic year 2020-2021. He was awarded a Ph.D. fellowship by the Faculty of Computer Science and Engineering at Shahid Beheshti University for the year 2018-2019. Additionally, he ranked 17th in the Nationwide Ph.D. University Entrance Exam out of over 2367 participants in 2018-2019. He has been selected to use the student facilities of the National Elite Foundation in 2020-2021. Throughout his academic career, Reza has consistently been ranked as an outstanding student during his Ph.D. (2019-2023), M.Sc. (2012-2014), and B.Sc. (2007-2010) studies. He has also received outstanding researcher and thesis awards during his M.Sc. years from 2012 to 2014.

Publication:

 

Multi-level trust-based intelligence schema for securing of internet of things (IoT) against security threats using cryptographic authentication

  • Authors: K Mabodi, M Yusefi, S Zandiyan, L Irankhah, R Fotohi
  • Journal: The Journal of Supercomputing
  • Publisher: Springer
  • Volume: 76(9)
  • Pages: 1-26
  • Year: 2020
  • Citations: 106

SoS-RPL: Securing Internet of Things Against Sinkhole Attack Using RPL Protocol-Based Node Rating and Ranking Mechanism

  • Authors: R Fotohi, M Zaminkar
  • Journal: Wireless Personal Communications
  • Publisher: Springer
  • Volume: 114(2)
  • Pages: 1287-1312
  • Year: 2020
  • Citations: 90*

Securing wireless sensor networks against denial-of-sleep attacks using RSA cryptography algorithm and interlock protocol

  • Authors: R Fotohi, S Firoozi Bari, M Yusefi
  • Journal: International Journal of Communication Systems
  • Publisher: Wiley
  • Volume: 33(4)
  • Article: e4234
  • Year: 2020
  • Citations: 90

DAWA: Defending against wormhole attack in MANETs by using fuzzy logic and artificial immune system

  • Authors: S Jamali, R Fotohi
  • Journal: The Journal of Supercomputing
  • Publisher: Springer
  • Volume: 73(12)
  • Pages: 5173-5196
  • Year: 2017
  • Citations: 89

An agent-based self-protective method to secure communication between UAVs in unmanned aerial vehicle networks

  • Authors: R Fotohi, E Nazemi, FS Aliee
  • Journal: Vehicular Communications
  • Publisher: Elsevier
  • Volume: 26
  • Article: 100267
  • Year: 2020
  • Citations: 88