Dr. Kadhim Mustafa Raad Kadhim

Name	Dr. Kadhim Mustafa Raad Kadhim
Nationality	Iraqi
Date of Birth	1991-05-21
Email	mustafa@xmu.edu.cn
Phone	+9647780054366 / +8613084428131
Academic Title	Postdoctoral Researcher
Workplace	School of Informatics, Xiamen University, China
Languages	Arabic, English, and Chinese

Dr. Mustafa Kadhim is an Iraqi citizen born in January 1991. He obtained his Ph.D. in 2022 from the University of Electronic Science and Technology of China (UESTC), specializing in Artificial Intelligence. He is currently a full-time Postdoctoral Researcher at the School of Informatics, Xiamen University, China. His main research focuses on applications of artificial intelligence in life sciences, particularly in the autonomous endoscopic resection of cancerous tumors in the lungs, kidneys, liver, and other organs, as well as related techniques. In addition, he works on building collaborative relationships between Xiamen University, Chinese companies, and Iraqi governmental and private institutions. Furthermore, he founded the Innovative Intelligence Center (inX) in Iraq — a center dedicated to developing unique artificial intelligence technologies tailored to the Iraqi market’s needs, as well as providing studies and consultations for entities seeking to integrate AI technologies into their systems.

In 2009, he enrolled at Al-Rafidain University College and obtained a Bachelor's degree in Software Engineering. In 2013, he worked as the Director of the Software Department at New Vision Company in Iraq, while simultaneously starting his own software development project. In 2015, he joined Southwest Jiaotong University, where he earned a Master of Engineering degree in Computer Science and Technology. In 2018, he enrolled at the University of Electronic Science and Technology of China (UESTC) and obtained a Doctor of Engineering degree in Software Engineering and Artificial Intelligence. In 2023, he worked at the same university as a research scientist specializing in artificial intelligence applications. In 2025, he began working at Xiamen University as a research scientist in the field of artificial intelligence in life sciences. In the same year, he founded the Smart Innovation Center for Artificial Intelligence.

His current research focuses on integrating artificial intelligence with medical applications, including neoantigen identification, tumor biomarker prediction, flexible autonomous bronchoscopy, endoscopic navigation, and motion path optimization. In parallel, he is extensively involved in the field of machine learning and its applications, which include data clustering, data classification, anomaly detection, depression detection, deep neural networks, adversarial attacks, federated learning, knowledge graphs, large language models, as well as drone path planning and intelligent decision-making.

He has supervised and managed five Iraqi government projects, three of which are major national projects, and has also participated in several projects funded by the National Natural Science Foundation of China (NSFC). His contributions include authoring a single-authored publication titled *“Self-Learning Detection Models for Data Analysis Based on Clustering”*, and publishing over fifteen research papers in leading international journals and conferences such as COSE, IEEE Internet of Things Journal (IoTJ), IET Communications, JKSUCIS, IJCNN, ICCWAMTIP, FedCSIS, IJMLC, FLINS, and APF. Additionally, he holds three national patents, has supervised students in scientific research, and has served as a reviewer for journals including JKSUCIS and IJCNN.

He received the First Prize at the provincial level and a Global Nomination Award in the 2023 High School Science Competition as a supervisor. He was also honored as a Graduate Supervisor of the Academic Year 2023/2024 at the University of Electronic Science and Technology of China (UESTC). Moreover, he served as the country representative at the same university from 2018/2019 to 2021/2022.

Academic Degree	Major	College/University	Period
Ph.D. Degree	Software Engineering Artificial Intelligence	School of Information and Software Engineering University of Electronic Science and Technology of China	2018.09 2022.12
MSc Degree	Software Engineering Artificial Intelligence	School of Information Science and Technology Southwest Jiaotong University	2015.09 2018.06
BSc Degree	Software Engineering	School of Software Engineering Al-Rafidain University College	2009.09 2013.08

Institution	Job Title	Location	Period	Responsibilities
Xiamen University	Full-time Postdoctoral Researcher	Xiamen, Fujian, China	2025-09 Present	Applying artificial intelligence in life sciences, particularly in the extraction and analysis of cancer tumors using autonomous endoscopy and related techniques. Building collaborations between Xiamen University and Chinese companies, and enhancing communication with Iraqi government institutions. Supervising students in their research projects and contributing to the management and acquisition of research projects funded by the National Natural Science Foundation of China (NSFC).
Innovative Intelligence Center (INX)	Founder	Baghdad, Iraq	2025-02 Present	Leading research and development in artificial intelligence solutions, integrating hardware with advanced algorithms to improve efficiency. Managing strategic partnerships with universities and companies, mentoring students, and ensuring successful project implementation from concept to application.
Al-Islamic University – Department of Computer Engineering Technologies	Faculty Member – Founder and Scientific Advisor	Diwaniyah, Iraq	2025-09 Present	Leading academic innovation and developing modern curricula in artificial intelligence, cloud computing, and the Internet of Things. Empowering students with future-ready skills, strengthening research partnerships, and supporting digital transformation in higher education.
School of Computer Science and Engineering (College of Cybersecurity), University of Electronic Science and Technology of China	Full-time Postdoctoral Researcher	Chengdu, Sichuan, China	2022-12 2024-12	Leading innovative research initiatives funded by NSFC, designing and implementing advanced research methodologies, and publishing scientific results in prestigious journals. Providing academic supervision for master’s and doctoral students and promoting their professional development.
Bright Education Training Center	Part-time Teaching Department Instructor	Chengdu, Sichuan, China	2015-12 2018-06	Guiding and training new foreign teachers and supporting them in adapting to the school environment. Providing training on teaching techniques and classroom management, developing teaching strategies, and offering feedback to enhance performance.
New Vision Company	Full-time Software Department Manager	Baghdad, Iraq	2014-01 2015-10	Analyzing client requirements, designing software, structuring databases, and managing projects. Solving technical problems and providing support and training for company staff and government departments.
Al-Baqir Software Office	Founder	Baghdad, Iraq	2013-09 2015-10	Analyzing, designing, and developing an integrated system for the Forensic Medicine Department at the Iraqi Ministry of Health to manage deceased individuals’ data. Organizing training courses on software design and data management.

No.	Patent Title	Inventors	Authority / Patent No.	License Date	Abstract
[1]	A Method for Mental Stress Recognition Based on Passive Domain Adaptation	Tian Ling, Kadhim Mustafa, Zhang Lizong, et al.	Sichuan Province: 2024110396263	2024-07-31	We propose a multi-domain method for stress recognition using electrocardiogram and physiological signals, incorporating self-supervised training and adaptive classifiers. This method addresses issues of low accuracy and weak transferability in traditional models. It is applicable in healthcare, driving safety, and occupational monitoring, enabling wearable devices to accurately classify stress levels.
[2]	A Temporal Knowledge Graph Reasoning Method Based on Historical Feature Representation Fusion	Gao Hui, Kadhim Mustafa, Lu Guangxi, et al.	Guangdong Province: 202411035366.2	2024-07-31	This invention proposes a reasoning method for temporal knowledge graphs using historical subgraphs, avoidance graphs, and attention mechanisms. It improves prediction accuracy and efficiency by integrating local structures with global background knowledge. Applications include intelligent question answering, recommendation systems, and event prediction.
[3]	A Multi-UAV Data Collection Method Considering Limited Endurance	Zhou Chengkai, Kadhim Mustafa, Wang Tingqi, et al.	Guangdong Province: 202410855086.X	2024-06-28	A secure method for multi-UAV data collection using encrypted backups (Shamir’s threshold scheme) and reward-based movement strategies. This method balances endurance limitations and security, preventing data loss and leakage. It is used in IoT sensing, disaster monitoring, and surveillance, ensuring efficient and secure collaboration among drone swarms.

No.	Project Title	Funding Agency	Project Number	Period	Funding	Status	Abstract
[1]	Research on Key Technologies of Federated Learning for Smart Cities	National Natural Science Foundation of China (NSFC)	No. 62372085	2024-01 2027-12	500,000 RMB	In Progress	Developing federated learning methods to enhance smart city applications. The project aims to ensure data privacy, improve system efficiency, and enable secure collaboration across distributed data sources.
[2]	Research on Explainable Hybrid Reasoning Technology for Knowledge Graphs	National Natural Science Foundation of China (NSFC)	No. 62376055	2024-01 2027-12	490,000 RMB	In Progress	This project investigates explainable hybrid reasoning techniques for knowledge graphs. It aims to integrate various reasoning approaches to make artificial intelligence decisions more transparent and applicable to complex real-world problems.

No.	Title	Authors	Publisher / Conference	Year	Abstract
[1]	Exploring the reliability of clustering models: a case study on interpretation and overlapping issues	Mustafa Kadhim, Peilin Li*, Guangxi Lu, et al.	International Journal of Machine Learning and Cybernetics	2024	This study examines the reliability of clustering models with a focus on interpretability and cluster overlap issues. It presents methods for performance evaluation and ambiguous case analysis.
[2]	Lightweight On-edge Clustering for Wireless AI-driven applications	Mustafa Raad Kadhim*, Guangxi Lu, Yinong Shi, et al.	IET Communications Journal	2024	The research focuses on developing lightweight clustering techniques that can be executed on edge devices for wireless AI applications, aiming to enhance efficiency and reduce energy consumption.
[3]	Multi-UAV path planning for multiple emergency payloads delivery in natural disaster scenarios	Zarina Kutpanova, Mustafa Raad Kadhim, Xu Zheng*, et al.	Journal of Electronic Science and Technology	2024	This paper discusses multi-UAV path planning for delivering emergency payloads in natural disasters using efficient algorithms to achieve reliable and rapid delivery.
[4]	Multi-UAVs path planning for data harvesting in adversarial scenarios	Zhou Chengkai, Kadhim Mustafa Raad Kadhim*, et al.	Computer Communications	2024	The research addresses UAV path planning for data collection in adversarial environments using risk-avoidance and adaptive techniques for dynamic conditions.
[5]	Self-learning Detection Models for Data Analysis Based on Cluster Ensemble	Kadhim Mustafa Raad Kadhim, Wenhong Tian	University of Electronic Science and Technology of China Press	2024	This work presents self-learning detection models based on cluster ensemble methods for data analysis, improving classification accuracy with minimal human intervention.
[6]	A novel self-directed learning framework for cluster ensemble	Mustafa R. Kadhim, Guangyao Zhou, Wenhong Tian*	Journal of King Saud University-Computer and Information Sciences	2022	This paper proposes a new self-directed learning framework using cluster ensemble techniques to automatically improve clustering performance and reduce errors.
[7]	SentKB-BERT: Sentiment-filtered Knowledge-based Stance Detection	Chen Hongzhou, Ke Yan*, Mustafa Raad Kadhim, et al.	International Joint Conference on Neural Networks (IJCNN)	2024	This study integrates natural language processing techniques with BERT for knowledge-based stance detection, enhancing the accuracy of opinion recognition in texts.
[8]	A Novel Side-Information for Unsupervised Cluster Ensemble	Mustafa Raad Kadhim et al.	ICCWAMTIP Conference	2021	This paper introduces new side-information to improve unsupervised cluster ensemble performance, increasing clustering accuracy and reducing result variance.
[9]	A Novel Cluster Ensemble based on a Single Clustering Algorithm	Khan Tahseen, Wenhong Tian*, Mustafa R. Kadhim, et al.	FedCSIS Conference	2021	This research proposes a new cluster ensemble approach based on a single clustering algorithm to simplify the process and reduce computational resources.
[10]	Rapid clustering with semi-supervised ensemble density centers	Mustafa R. Kadhim, Wenhong Tian*, Tahseen Khan	ICCWAMTIP Conference	2019	This study presents a rapid clustering method based on semi-supervised ensemble density centers for fast and efficient large-scale data analysis.
[11]	Semi-supervised cluster ensemble based on density peaks	Mustafa Kadhim et al.	FLINS Conference	2018	This research develops a semi-supervised clustering approach based on density peaks to improve group identification accuracy and reduce overlap.
[12]	Comparison of Time Interval Statistic and Pulse Shape Discrimination in Fast Neutron Detection Method with Liquid Scintillation Detector Loaded Gd	Al-jumaili M. A. J., Qiang D., Jingjun Z., Xinde L., Wenbin L., Changjian T., Mustafa R. K., et al.	Applied Physics Frontier	2017	This paper compares two fast neutron detection methods using a gadolinium-loaded liquid scintillation detector to determine the most accurate and reliable approach.

No.	Title of Work / Research	Authors / Students	Publisher / Conference	Year	Abstract
[1]	A method for elevated ducts refinement based on convolutional neural network	Zhu, Xunyang; Ke Yan; Liquan Jiang; et al.	Radio Science	2024	This study proposes a method to improve the accuracy of analyzing elevated atmospheric ducts using convolutional neural networks, enhancing the estimation of atmospheric characteristics with higher precision.
[2]	Adversarial Cross-laser Attack: Effective Attack to DNNs in the Real World	Wu, Hanyu; Ke Yan; Peng Xu; et al.	12th International Symposium on Digital Forensics and Security (ISDFS)	2024	This research presents a practical adversarial laser-based attack on deep neural networks in the real world, exposing significant security vulnerabilities in intelligent systems.

No.	Title	Authors	Organization / Status	Abstract
[1]	Hybrid Transformer-CNN U-Net For 3D Renal Artery Segmentation	Mustafa Kadhim, et al.	IEEE ICASSP (Submitted)	This research presents a hybrid model that combines Transformer and CNN within a 3D U-Net architecture for renal artery segmentation from medical images, focusing on improving fine-detail accuracy in 3D vascular segmentation.
[2]	Lightweight Semi-supervised Gravitational Clustering for Growing Data in Internet of Medical Things	Mustafa Kadhim, et al.	IEEE Internet of Things Journal (2024) — Under Submission	This work proposes a lightweight semi-supervised clustering approach based on a gravitational model to handle growing data in the Internet of Medical Things (IoMT), emphasizing computational efficiency and reduced resource consumption for constrained devices.

No.	Achievement / Activity	Year	Description / Role
[1]	First Regional Prize in S.-T. Yau High School Science Award	2023	Received the First Regional Prize as a mentor in recognition of his efforts in supervising high school students participating in the international science competition.
[2]	Global Nomination Award in S.-T. Yau High School Science Award	2023	Earned the Global Nomination Award as a mentor for students participating in the international science competition, acknowledging his academic and advisory contributions.
[3]	Graduate Supervisor of the Academic Year at UESTC	2023/2024	Provided academic guidance and research support to postgraduate students at the University of Electronic Science and Technology of China (UESTC).
[4]	Representative of Iraqi Students at UESTC	2018/2019 - 2019/2020	Served as the representative of Iraqi students at the university, organizing cultural and academic events and strengthening international student relations.