Simeon Ogunbunmi | Privacy and Security | Best Researcher Award

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Mr. Simeon Ogunbunmi, Privacy and Security, Best Researcher Award

Simeon Ogunbunmi at Binghamton University, United States

Mr. Simeon Ogunbunmi is a highly motivated computer engineering doctoral candidate at Binghamton University, State University of New York. He holds a Master of Science degree in Electrical and Computer Engineering from Binghamton University, which he earned in August 2024. Prior to his master’s degree, he completed his Bachelor of Technology in Computer Science and Engineering at Ladoke Akintola University of Technology, Nigeria. Mr. Ogunbunmi has professional experience in leveraging network architecture, machine learning, cybersecurity, and cryptography to enhance trust and reputation system mechanisms. He has developed reputation systems for IoT using blockchain technology, with a focus on security and efficiency. Proficient in Python, MATLAB, and Java, Mr. Ogunbunmi is seeking research-intensive internships to further advance reputation, trust, privacy, and security systems.

Profile:

Education:

Mr. Simeon Ogunbunmi is currently pursuing a Doctor of Philosophy in Electrical and Computer Engineering at Binghamton University, State University of New York, Thomas J. Watson College of Engineering and Applied Science, with an expected graduation date of May 2027. He earned his Master of Science in Electrical and Computer Engineering from the same institution in August 2024, achieving a perfect cumulative GPA of 4.00/4.00. During his master’s program, he was awarded the 2023 and 2024 Provost’s Doctoral Summer Fellowship. His coursework included Computer Network Architecture, Computer Design, Machine Learning, Digital Communication, Network Security, Cryptography and Info Security, Mathematical Modeling, Advanced Engineering Analytics, Statistical Methods for Data Science, and Quantum Computing. Previously, Mr. Ogunbunmi completed his Bachelor of Technology in Computer Science and Engineering at Ladoke Akintola University of Technology in Ogbomoso, Nigeria, in April 2022, with a cumulative GPA of 3.75/4.00. He ranked 3rd in his class and was recognized for his outstanding contribution to students’ life. His coursework covered a wide range of topics, including Decision Support Systems, Integrated Circuits, Data Communication and Networks, Expert Systems, Digital Signal Processing, Modeling and Simulation, Artificial Intelligence, Control Engineering, Computer Networks, Applied Probability and Statistics, Engineering Management, and Engineering Project Management.

Professional Experience:

Mr. Simeon Ogunbunmi has a diverse range of professional experiences that showcase his expertise in computer engineering. As a Graduate Research Assistant at Binghamton University, he contributed significantly to the development of a reputation system for Unmanned Aerial Vehicle (UAV) systems using blockchain technology. His responsibilities included designing and implementing temperature settings using Python and Raspberry Pi hardware, analyzing and synthesizing data using R and MS-Excel, and conducting rigorous testing to prevent attacks and data tampering. In his role as a Remote Temperature Control System Intern at Hub Controls, Mr. Ogunbunmi researched existing solutions to build heat pump machines using Python and Linux, contributing to projects that measured atmospheric conditions and connected devices using Wi-Fi and Bluetooth technologies. These experiences demonstrate his ability to apply his skills in real-world settings, ensuring effective and efficient solutions in the fields of network architecture, machine learning, and cybersecurity.

Research Interest:

Mr. Simeon Ogunbunmi’s research interests encompass several cutting-edge areas within computer engineering. He is particularly interested in reputation systems for Internet of Things (IoT) devices, leveraging blockchain technology for enhanced security and efficiency. His work in this area focuses on developing robust mechanisms to ensure data integrity and trustworthiness in IoT ecosystems. Additionally, he is passionate about machine learning applications in cybersecurity, exploring ways to enhance threat detection and response using advanced algorithms and data analytics. Overall, Mr. Ogunbunmi’s research interests align with the forefront of technological advancements, aiming to contribute innovative solutions to pressing challenges in network security, trust, and privacy.

Technical Skills:

Mr. Simeon Ogunbunmi boasts a robust technical skill set, reflecting his diverse expertise and extensive experience in computer engineering. He is proficient in various programming languages, including Python, Java, JavaScript, C, CSS, and HTML, enabling him to tackle a wide range of development and engineering challenges. His software and operating system proficiencies encompass MATLAB, SPSS, Microsoft Word, Microsoft Excel, LaTeX, Microsoft Project, Fusion 360, and Linux, showcasing his versatility and adaptability across different platforms and tools. Additionally, Mr. Ogunbunmi is fluent in English and Yoruba, further enhancing his communication skills and cultural adaptability. He has also earned several certifications, including DevOps Fundamentals, Software Architecture, CompTIA Cloud+ Basic, Artificial Intelligence in Web Design, SQL Bootcamp with MySQL, and PHP & Python, demonstrating his commitment to continuous learning and professional development.

Publications:

A digital twins enabled reputation system for microchain-based UAV networks

  • Authors: Q. Qu, S. Ogunbunmi, M. Hatami, R. Xu, Y. Chen, G. Chen, E. Blasch
  • Conference: 2023 IEEE 12th International Conference on Cloud Networking (CloudNet)
  • Year: 2023
  • Pages: 428-432
  • Citations: 2

A Lightweight Reputation System for UAV Networks

  • Authors: S. Ogunbunmi, M. Hatami, R. Xu, Y. Chen, E. Blasch, E. Ardiles-Cruz, A. Aved, …
  • Conference: International Conference on Security and Privacy in Cyber-Physical Systems
  • Year: 2023
  • Citations: 2

A Survey on Reputation Systems for UAV Networks

  • Authors: S. Ogunbunmi, Y. Chen, E. Blasch, G. Chen
  • Journal: Drones
  • Year: 2024
  • Volume: 8
  • Issue: 6
  • Article Number: 253

 

Guowen Xu | Commputer Security | Best Researcher Award

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Prof. Guowen Xu, Commputer Security,  Best Researcher Award


Professor at University of Electronic Science and Technology of China, China

Prof. Guowen Xu is a renowned expert in cyberspace security, currently serving as a Professor at the School of Computer Science and Engineering at the University of Electronic Science and Technology of China (UESTC). He holds a Ph.D. in Cyberspace Security from UESTC, where he was supervised by IEEE Fellow Prof. Hongwei Li. He also completed a visiting Ph.D. program at Singapore Management University under the guidance of IEEE Fellow Prof. Robert H. Deng. Prof. Xu has held research fellow positions at Nanyang Technological University and postdoctoral positions at City University of Hong Kong, where he worked with IEEE Fellow Prof. Yuguang Fang. His research interests include applied cryptography, computer security, and AI security and privacy. He has received numerous accolades for his work, including being named one of the Stanford World’s Top 2% Scientists in 2023 and winning several best paper awards at prestigious conferences. Prof. Xu’s contributions to the field have been recognized internationally, and he continues to influence the development of advanced security technologies.

Profile:

Education:

Ph.D. in Cyberspace Security (2015/09 – 2020/12)

  • School of Computer Science and Engineering, UESTC
  • Supervisor: Prof. Hongwei Li (IEEE Fellow)

Visiting Ph.D. in Cyberspace Security (2019/08 – 2020/08)

  • School of Information Systems, Singapore Management University
  • Supervisor: Prof. Robert H. Deng (IEEE Fellow)

Bachelor of Information and Computing Science (2010/09 – 2014/06)

  • School of Mathematical and Physical Science, Anhui Jianzhu University (AHJZU)

Professional Experience:

Prof. Guowen Xu has a distinguished professional background in the field of cyberspace security. He is currently a Professor at the School of Computer Science and Engineering at the University of Electronic Science and Technology of China (UESTC), a position he has held since October 2024. Prior to this, he served as a Postdoctoral Fellow at the Department of Computer Science at City University of Hong Kong from May 2023 to October 2024, where he worked under the supervision of IEEE Fellow Prof. Yuguang Fang. Before his postdoctoral fellowship, Prof. Xu was a Research Fellow at the School of Computer Science and Engineering at Nanyang Technological University in Singapore from March 2021 to May 2023. His early academic career includes a visiting Ph.D. program at Singapore Management University from August 2019 to August 2020, supervised by IEEE Fellow Prof. Robert H. Deng. Prof. Xu’s extensive research experience and collaborations with leading scholars have significantly contributed to his expertise in applied cryptography, computer security, and AI security and privacy.

Research Interest:

Prof. Guowen Xu’s research interests are centered around the fields of applied cryptography, computer security, and AI security and privacy. His work focuses on developing innovative cryptographic techniques to enhance data security and privacy, particularly in the context of complex and evolving cyber threats. In the realm of computer security, he explores robust mechanisms to safeguard systems and networks from vulnerabilities and attacks. Additionally, Prof. Xu is deeply invested in the security and privacy aspects of artificial intelligence, investigating methods to protect AI systems from adversarial threats and ensure the ethical use of AI technologies. His interdisciplinary approach aims to address the pressing security challenges of the digital age, contributing to the advancement of safer and more resilient technological environments.

Awards and Honors:

  • 2023 Stanford World’s Top 2% Scientists
  • 2023 IEEE BigDataSecurity Best Paper Award
  • 2022-2024 Distinguished Reviewer of ACM Transactions on the Web
  • 2022 ECCV Online Registration Waiver Award
  • 2021 Wu Wenjun First Prize of Artificial Intelligence Science and Technology Progress
  • 2021 Outstanding Graduate Student of UESTC
  • 2021 Outstanding Graduate Student in Sichuan Province
  • 2021 IEEE INFOCOM Student Conference Award
  • 2020 IEEE ICPADS Best Paper Award
  • 2020 National Scholarship of Graduate Student (MOE of PRC, Top 1%)
  • 2020 First-class Scholarship of Graduate Student (UESTC, Top 1%)
  • 2019 SCF Best Student Paper Award (Sichuan Province Computer Federation)
  • 2019 National Scholarship of Graduate Student (MOE of PRC, Top 1%)
  • 2019 First-class Scholarship of Graduate Student (UESTC, Top 1%)
  • 2018 Network Security Scholarship of China Internet Development Foundation
  • 2018 National Scholarship of Graduate Student (MOE of PRC, Top 1%)
  • 2018 First-class Scholarship of Graduate Student (UESTC, Top 1%)
  • 2018 First-class Scholarship of Shenzhen Huiding Technology Co., Ltd (Top 1%)
  • 2018-2020 Excellent Student Award (UESTC)
  • 2018-2020 Excellent Graduate Student (UESTC)
  • 2016 Excellence Award of National Cipher Technology Competition

Publication Top Noted:

VerifyNet: Secure and Verifiable Federated Learning

  • Authors: G. Xu, H. Li, S. Liu, K. Yang, X. Lin
  • Journal: IEEE Transactions on Information Forensics and Security
  • Volume: 15
  • Pages: 911-926
  • Citations: 570
  • Year: 2020

Efficient and Privacy-Enhanced Federated Learning for Industrial Artificial Intelligence

  • Authors: M. Hao, H. Li, X. Luo, G. Xu, H. Yang, S. Liu
  • Journal: IEEE Transactions on Industrial Informatics
  • Volume: 16
  • Issue: 10
  • Pages: 6532-6542
  • Citations: 472
  • Year: 2019

Enabling Efficient and Geometric Range Query with Access Control over Encrypted Spatial Data

  • Authors: G. Xu, H. Li, Y. Dai, K. Yang, X. Lin
  • Journal: IEEE Transactions on Information Forensics and Security
  • Volume: 14
  • Issue: 4
  • Pages: 870-885
  • Citations: 192
  • Year: 2018

Towards Efficient and Privacy-Preserving Federated Deep Learning

  • Authors: M. Hao, H. Li, G. Xu, S. Liu, H. Yang
  • Conference: ICC 2019 – IEEE International Conference on Communications
  • Pages: 1-6
  • Citations: 178
  • Year: 2019

Privacy-Enhanced Federated Learning against Poisoning Adversaries

  • Authors: X. Liu, H. Li, G. Xu, Z. Chen, X. Huang, R. Lu
  • Journal: IEEE Transactions on Information Forensics and Security
  • Citations: 158
  • Year: 2021

Muhammad Sajjad | Cryptography | Best Researcher Award

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Dr. Muhammad Sajjad, Cryptography, Best Researcher Award

Doctorate at Quaid-I-Azam University Islamabad, Pakistan, Pakistan

Dr. Muhammad Sajjad is a mathematician specializing in data transmission, data security, coding theory, and cryptography. He earned his Ph.D. and M.Phil in Mathematics from Quaid-I-Azam University in Islamabad, Pakistan, focusing on coding and cryptographic schemes over vector algebra residue classes and higher-length cyclic codes over quaternion integers, respectively. He also holds an M.Sc in Mathematics and a B.Sc in Mathematics and Physics from Islamia University Bahawalpur. Dr. Sajjad has a wealth of experience in research and teaching, making significant contributions to the field of mathematics.

Profile:

Education:

  • Ph.D. in Mathematics (2020-2024) from Quaid-I-Azam University, Islamabad, Pakistan, with a focus on data transmission and data security using coding and cryptographic schemes over the residue classes of vector algebra.
  • M.Phil in Mathematics (2018-2020) from Quaid-I-Azam University, Islamabad, Pakistan, specializing in encoding and decoding of higher-length cyclic codes over quaternion integers.
  • M.Sc in Mathematics (2016-2018) from Islamia University Bahawalpur, Punjab, Pakistan.
  • B.Sc in Mathematics and Physics (2014-2016) from Islamia University Bahawalpur, Punjab, Pakistan.

Professional Experience:

Dr. Muhammad Sajjad has an extensive professional background in mathematics and academia. He has spent five years conducting research at Quaid-I-Azam University in Islamabad, Pakistan, focusing on various aspects of coding theory, cryptography, and data security. Currently, Dr. Sajjad serves as a Mathematics faculty member at Quaid-i-Azam University, where he imparts knowledge and expertise in areas such as Cryptography, Coding Theory, Linear Algebra, Rings and Fields, and Number Theory. In addition to his role at Quaid-i-Azam University, Dr. Sajjad has enriched his teaching experience as a visiting faculty member at prestigious institutions such as the National University of Modern Languages (NUML) and Bahria University, both located in Islamabad, Pakistan. He has also contributed his mathematical expertise as a faculty member at FG Sir Syed College in Rawalpindi, Pakistan. Throughout his professional journey, Dr. Sajjad has not only conducted impactful research but has also dedicated himself to educating and mentoring students, shaping the future of mathematics and related fields in Pakistan.

Research Interest:

Dr. Muhammad Sajjad’s research interests encompass a broad spectrum of mathematical and engineering disciplines. His expertise lies in the realms of data transmission, data security, coding theory, and cryptography. Within mathematics, Dr. Sajjad delves into areas such as vector algebra, commutative algebra, non-commutative algebra, and non-associative algebra. His exploration of number theory extends to developing novel cryptographic schemes and error-correcting codes in coding theory, contributing significantly to data security and communication reliability. Dr. Sajjad’s research endeavors are characterized by a deep understanding of algebraic structures and their applications in practical domains like information security and data transmission. His work often involves innovative approaches to encoding and decoding methods, particularly in the context of higher-length cyclic codes over quaternion integers. This intersection of theoretical mathematics and real-world applications underscores Dr. Sajjad’s commitment to advancing both fundamental mathematical knowledge and its practical implementations in data science and engineering.

Publication Top Noted:

“A comparative study of nonlinear fractional Schrödinger equation in optics”

  • Authors: S Irshad, M Shakeel, A Bibi, M Sajjad, KS Nisar
  • Journal: Modern Physics Letters B
  • Volume/Issue: 37 (05)
  • Cited By: 13
  • Year: 2023

“Quaternion Integers Based Higher Length Cyclic Codes and Their Decoding Algorithm”

  • Authors: M Sajjad, T Shah, MM Hazzazi, AR Alharbi, I Hussain
  • Journal: Computers, Materials & Continua
  • Volume/Issue: 73 (1)
  • Cited By: 7
  • Year: 2022

“Designing Pair of Nonlinear Components of a Block Cipher over Gaussian Integers”

  • Authors: M Sajjad, T Shah, RJ Serna
  • Journal: Computers, Materials & Continua
  • Volume/Issue: 75 (3)
  • Cited By: 6
  • Year: 2023

“Fundamental Results of Cyclic Codes over Octonion Integers and Their Decoding Algorithm”

  • Authors: M Sajjad, T Shah, RJ Serna, ZE Suárez Aguilar, OS Delgado
  • Journal: Computation
  • Volume/Issue: 10 (12)
  • Cited By: 3
  • Year: 2022

“Construction and decoding of BCH-codes over the Gaussian field”

  • Authors: M Sajjad, T Shah, M Alammari, H Alsaud
  • Journal: IEEE Access
  • Cited By: 2
  • Year: 2023

 

Abdallah Soualmi | Cryptography | Best Researcher Award

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Dr. Abdallah Soualmi, Cryptography, Best Researcher Award

Doctorate at University Ferhat abbas setif 1, Algeria

Dr. Abdallah Soualmi completed his education with a Bachelor’s degree in Computer Science in June 2014, followed by a Master’s degree in Networks and Distributed Systems in June 2016. He achieved a Ph.D. in Machine Learning in May 2021, specializing in the protection of medical content using watermarking and cryptography.

Profile:

Education:

Dr. Abdallah Soualmi completed his Bachelor’s degree in Computer Science in June 2014, followed by a Master’s degree in Networks and Distributed Systems in June 2016. He achieved his Ph.D. in Machine Learning in May 2021, specializing in the protection of medical content using watermarking and cryptography.

Professional Experience:

Dr. Abdallah Soualmi’s professional experience spans academia and research, focusing on machine learning, data security, and cryptography. He began his career as a Research Fellow and Ph.D. Student at UFAS1 University, actively involved in cutting-edge research from September 30, 2016, to May 4, 2021. His work during this period contributed significantly to the fields of medical data security, cryptography, steganography, watermarking, data authenticity, authorship proofing, and data sharing monitoring. After completing his Ph.D., Dr. Soualmi transitioned to an academic role, initially as an Assistant Teacher at Cuillizi University from September 26, 2021, to September 26, 2022. He then progressed to become an Associate Lecturer at the same university, starting from September 26, 2022, until the present. In these roles, he has been instrumental in shaping the educational journey of students, imparting his knowledge in machine learning and computer science. Throughout his career, Dr. Soualmi has demonstrated a strong commitment to research excellence and academic development, with a focus on leveraging advanced technologies for enhancing data security and integrity. His contributions in both academia and research highlight his expertise and dedication to advancing the frontiers of machine learning and data protection.

Research Interest:

Dr. Abdallah Soualmi’s research interests are centered around machine learning, data security, and cryptography, with a particular focus on applications in medical data protection. He is passionate about exploring innovative approaches to ensure the security and integrity of sensitive medical information, employing techniques such as cryptography, steganography, watermarking, and data authenticity verification. Dr. Soualmi is also interested in data sharing monitoring mechanisms to enhance privacy and prevent unauthorized access to medical data. His research aims to contribute to the development of robust and reliable solutions for safeguarding healthcare information in an increasingly digital and interconnected world.

Publication Top Noted:

A new blind medical image watermarking based on weber descriptors and Arnold chaotic map

  • Authors: A Soualmi, A Alti, L Laouamer
  • Journal: Arabian Journal for Science and Engineering
  • Volume: 43
  • Issue: 12
  • Pages: 7893-7905
  • Citations: 43
  • Year: 2018

A novel blind medical image watermarking scheme based on Schur triangulation and chaotic sequence

  • Authors: A Soualmi, A Alti, L Laouamer
  • Journal: Concurrency and Computation: Practice and Experience
  • Volume: 34
  • Issue: 1
  • Pages: e6480
  • Citations: 20
  • Year: 2022

A novel blind watermarking approach for medical image authentication using MinEigen value features

  • Authors: A Soualmi, A Alti, L Laouamer
  • Journal: Multimedia Tools and Applications
  • Volume: 80
  • Issue: 2
  • Pages: 2279-2293
  • Citations: 17
  • Year: 2021

An imperceptible watermarking scheme for medical image tamper detection

  • Authors: A Soualmi, A Alti, L Laouamer
  • Journal: International Journal of Information Security and Privacy (IJISP)
  • Volume: 16
  • Issue: 1
  • Pages: 1-18
  • Citations: 16
  • Year: 2022

A blind image watermarking method for personal medical data security

  • Authors: A Soualmi, A Alti, L Laouamer
  • Conference: 2019 International Conference on Networking and Advanced Systems (ICNAS)
  • Pages: 1-5
  • Citations: 10
  • Year: 2019