Omar DIB

Position:

Associate Professor of Computer Science
College:

College of Science, Mathematics and Technology
Office:

CSMT 443
E-mail:

odib@kean.edu

EDUCATIONAL BACKGROUND

Ph.D. in Computer Science University of Burgundy – Franche-Comté, France

BEng in Computer Science University of Technology of Belfort-Montbéliard, France

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计算机科学博士，法国勃艮第-弗朗什-孔泰大学 (University of Burgundy – Franche-Comté)

计算机科学工程学士，法国贝尔福-蒙贝利亚尔技术大学 (University of Technology of Belfort-Montbéliard)

ACADEMIC EXPERIENCE

Faculty Positions
2025 - present Associate Professor (Tenured), Computer Science — Wenzhou-Kean University, China
2020 - 2025 Assistant Professor, Computer Science — Wenzhou-Kean University, China

Academic Leadership
2021 - present Director, Computer Science and AI Center (CSAI) - Wenzhou-Kean University
2021 - 2024 Director, M.S. Program in Computer Information Systems - Wenzhou-Kean University
2025 - present Chair, Reappointment and Tenure Committee - Wenzhou-Kean University

Prior Teaching & Research Appointments
2018 - 2019 Lecturer, Paris Sud University - IUT Orsay, France
2014 - 2018 Ph.D. Researcher, IRT SystemX / University of Technology Belfort-Montbéliard, France
2016 - 2017 Teaching Assistant, University of Technology Belfort-Montbéliard, France

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教师职位
2025 至今副教授（终身教职），计算机科学 —— 温州肯恩大学，中国
2020 - 2025 助理教授，计算机科学 —— 温州肯恩大学，中国

学术领导职务
2021 至今计算机科学与人工智能中心（CSAI）主任 - 温州肯恩大学
2021 - 2024 计算机信息系统硕士项目主任 - 温州肯恩大学
2025 至今续聘与终身教职委员会主席 - 温州肯恩大学

过往教学与科研经历
2018 - 2019 讲师，巴黎南大学 - IUT Orsay，法国
2014 - 2018 博士研究员，IRT SystemX / 贝尔福-蒙贝利亚尔技术大学，法国
2016 - 2017 助教，贝尔福-蒙贝利亚尔技术大学，法国

BIOGRAPHY

Dr. Omar Dib is a Tenured Associate Professor of Computer Science at Wenzhou-Kean University in Wenzhou, China. He holds a Ph.D. in Computer Science from the University of Burgundy Franche-Comté, France, and has previous industrial experience as a Research and Development Engineer. He served as Director of the Master's Program in Computer Information Systems from 2021 to 2024 and has taught courses in artificial intelligence, machine learning, algorithms, and software engineering.

His research focuses on Federated Learning and trustworthy distributed AI, particularly privacy-preserving learning, secure and robust distributed learning, blockchain, and secure multiparty computation, and edge intelligence. His recent work also examines federated multi-agent systems and risk-aware AI inference. These research directions are applied to areas including healthcare, cybersecurity, and industrial IoT. Dr. Omar Dib has established an independent research program in these areas, with recent publications as lead or sole author in Information Fusion, Computer Science Review, and Knowledge-Based Systems, as well as collaborative work published in Engineering Applications of Artificial Intelligence and Internet of Things. He has also received research funding and recognition for his scholarly contributions. His academic activities include supervising graduate and undergraduate research, collaborating with interdisciplinary teams, and leading academic programs.

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Dr. Omar Dib 是温州肯恩大学计算机科学专业的终身副教授。他拥有法国勃艮第-弗朗什-孔泰大学计算机科学博士学位，并曾担任研发工程师，具备丰富的工业界经验。他曾于2021年至2024年担任计算机信息系统硕士项目主任，并教授过人工智能、机器学习、算法和软件工程等课程。

他的研究方向聚焦于联邦学习与可信分布式人工智能，特别是隐私保护学习、安全稳健的分布式学习、区块链、安全多方计算以及边缘智能。他近期的研究还涉及联邦多智能体系统和风险感知的AI推理。这些方向广泛应用于医疗健康、网络安全和工业物联网领域。Dr. Omar Dib 在这些领域建立了独立的研究计划，以第一作者或唯一作者身份在《Information Fusion》、《Computer Science Review》和《Knowledge-Based Systems》等期刊发表了最新论文，并在《Engineering Applications of Artificial Intelligence》和《Internet of Things》上发表了合作成果。他还获得了科研经费和学术认可。他的学术活动包括指导研究生和本科生科研、跨学科团队合作以及领导学术项目。

RESEARCH INTEREST

1. Federated & Privacy-Preserving Learning — designing distributed learning systems that protect data through secure multi-party computation, blockchain, and differential privacy mechanisms.

2. Trustworthy Edge AI — robust, attack-resilient distributed AI for edge environments including IIoT, with efficient inference via adaptive routing and early-exit architectures.

3. Agentic AI Systems — federated multi-agent frameworks and LLM-driven edge intelligence, with applications in healthcare, cybersecurity, and industrial AI

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1. 联邦学习与隐私保护学习 —— 通过安全多方计算、区块链和差分隐私机制，设计能够保护数据的分布式学习系统。

2. 可信边缘人工智能 —— 面向边缘环境（包括工业物联网）的稳健、抗攻击分布式人工智能，通过自适应路由和早退架构实现高效推理。

3. 智能体人工智能系统 —— 联邦多智能体框架与大语言模型驱动的边缘智能，应用于医疗健康、网络安全和工业人工智能领域。

COURSES TAUGHT

· CPS 5801: Advanced Artificial Intelligence (Graduate)
· CPS 5802: Machine Learning Innovations (Graduate)
· CPS 5440: Advanced Analysis of Algorithms (Graduate)
· CPS 5995: Capstone in Computer Information Systems (Graduate)
· CPS 4851: Foundations of Edge AI (UG)
· CPS 4981: Generative AI (UG)
· CPS 3440: Analysis of Algorithms (UG)
· CPS 3962: Object-oriented Analysis and Design (UG)
· CPS 3410: Applied Algorithms and Data Structures (UG)

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· CPS 5801：高级人工智能（研究生课程）
· CPS 5802：机器学习创新（研究生课程）
· CPS 5440：高级算法分析（研究生课程）
· CPS 5995：计算机信息系统毕业设计（研究生课程）
· CPS 4851：边缘人工智能基础（本科课程）
· CPS 4981：生成式人工智能（本科课程）
· CPS 3440：算法分析（本科课程）
· CPS 3962：面向对象分析与设计（本科课程）
· CPS 3410：应用算法与数据结构（本科课程）

SELECTED PUBLICATIONS

Omar Dib*. "Blockchain-enabled defenses in federated learning: A comprehensive survey." Computer Science Review (2026): 100932.
Omar Dib*. "Communication-Efficient Agentic Edge Intelligence: A Survey of Federated Multi-Agent Information Fusion for LLM-Driven Edge AI." Information Fusion (2026): 104577.
Omar Dib*. "When to stop: Learned routing and risk control for early exit networks." Knowledge-Based Systems (2026): 116702.
Omar Dib*, Shiyun Li, Zhengkun Li. "Towards Robust and Privacy-Preserving Federated Learning: SMPC-Enhanced Defense and Optimization for Edge-IIoTset." Internet of Things (2026): 102084.
Zhengkun Li, Omar Dib*, Shiyun Li. "Data-centric federated learning for neuro-oncology: Addressing heterogeneity via privacy-preserving generative augmentation." Engineering Applications of Artificial Intelligence (2026): 114351.
Omar Dib*. "Secure and Incentivized Federated Learning for Resilient Telemedicine Diagnostics." Knowledge-Based Systems (2025): 114622.
Omar Dib*, Shiyun Li, Zhengkun Li, Rouwaida Abdallah, Elhacen Diallo. "FL-SMPC++: A Robust Framework for Privacy-Preserving Federated Learning." Results in Engineering (2025): 107380.

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Omar Dib*。“联邦学习中的区块链赋能防御：一项综合综述。”《计算机科学评论》（2026）：100932。
Omar Dib*。“通信高效的智能体边缘智能：面向大语言模型驱动边缘AI的联邦多智能体信息融合综述。”《信息融合》（2026）：104577。
Omar Dib*。“何时停止：早退网络的学习路由与风险控制。”《知识型系统》（2026）：116702。
Omar Dib*，Shiyun Li，Zhengkun Li。“迈向稳健且隐私保护的联邦学习：针对Edge-IIoTset的SMPC增强防御与优化。”《物联网》（2026）：102084。
Zhengkun Li，Omar Dib*，Shiyun Li。“以数据为中心的神经肿瘤学联邦学习：通过隐私保护生成式增强解决异质性问题。”《人工智能工程应用》（2026）：114351。
Omar Dib*。“面向弹性远程医疗诊断的安全激励机制联邦学习。”《知识型系统》（2025）：114622。
Omar Dib*，Shiyun Li，Zhengkun Li，Rouwaida Abdallah，Elhacen Diallo。“FL-SMPC++：一个用于隐私保护联邦学习的稳健框架。”《工程成果》（2025）：107380。

BOOK CHAPTERS

Diallo, El-Hacen, Omar Dib, and Khaldoun Al Agha. "A blockchain-based approach to track traffic messages in vehicular networks." In Proceedings of Academia-Industry Consortium for Data Science: AICDS 2020, pp. 345-362. Singapore: Springer Nature Singapore, 2022.
Nan, Zhenghan, Xiao Wang, and Omar Dib*. "Metaheuristic enhancement with identified elite genes by machine learning." In International Symposium on Knowledge and Systems Sciences, pp. 34-49. Singapore: Springer Nature Singapore, 2022.
Zhenghan, Nan, and Omar Dib*. "Agriculture stimulates Chinese GDP: a machine learning approach." In International Conference on Big Data Engineering and Technology, pp. 21-36. Cham: Springer International Publishing, 2022.
Liu, Yinhao, Xu Chen, and Omar Dib*. "Application of Metaheuristic Algorithms and Their Combinations to Travelling Salesman Problem." In International Conference on Intelligent Computing & Optimization, pp. 3-18. Cham: Springer Nature Switzerland, 2023.

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Diallo, El-Hacen，Omar Dib 与 Khaldoun Al Agha。“一种基于区块链的车载网络交通消息追踪方法。” 载于《产学研数据科学联盟会议论文集：AICDS 2020》，第 345-362 页。新加坡：施普林格·自然新加坡，2022 年。
Nan, Zhenghan，Xiao Wang 与 Omar Dib*。“基于机器学习识别精英基因的元启发式算法增强。” 载于《知识与系统科学国际研讨会论文集》，第 34-49 页。新加坡：施普林格·自然新加坡，2022 年。
Zhenghan, Nan 与 Omar Dib*。“农业拉动中国GDP：一种机器学习方法。” 载于《大数据工程与技术国际会议论文集》，第 21-36 页。瑞士CHAM：施普林格国际出版，2022 年。
Liu, Yinhao，Xu Chen 与 Omar Dib*。“元启发式算法及其组合在旅行商问题中的应用。” 载于《智能计算与优化国际会议论文集》，第 3-18 页。瑞士CHAM：施普林格·自然瑞士，2023 年。

GRANTS

2023–2025 WKU International Collaborative Research Programs (ICRP) Secure Traffic Related Messages in VANETs Using Blockchain.
2021–present CSAI — Center of Computer Science and Artificial Intelligence, Interdisciplinary Research in AI and Applied Computer Science.
2024–2025 WKU Student–Faculty Research Programs (SPF) Sustainable Federated Learning for Enhancing Diabetic Retinopathy Detection.
2021–2025 WKU Internal Faculty Research Support Programs (IRSP) New Digital Systems Based on Blockchain and IoT for Safe Vaccine Supply.
2021–2023 WKU SPF / SSPF (3 grants): IoV intrusion detection; evolutionary algorithms; multimodal route planning.