Assoc. Prof. Dr. Bei Guan | Computer Science | Best Researcher Award
Assoc. Prof. Dr. Bei Guan, Institute of Software, Chinese Academy of Sciences, China
Dr. Bei Guan is a distinguished Senior Engineer (Associate Professor) at the Institute of Software, Chinese Academy of Sciences. With deep-rooted expertise in Big Data Analytics, Cyber Security, and Knowledge Graph-based systems, he has established himself as a key contributor to intelligent system development. Dr. Guan earned prominence through innovative work in operating system virtualization, malicious domain detection, and traditional Chinese medicine analytics. His postdoctoral research at QCRI, Qatar, led to the breakthrough “Guilt by Association” framework for cyber threat detection. Beyond academia, he has led impactful national and industrial projects ranging from AI in civil aviation to smart manufacturing platforms. Passionate about applying data science to real-world problems, Dr. Guan consistently pushes the frontier of technological application in intelligent diagnostics and threat intelligence systems. His career exemplifies a balance of theoretical rigor and practical innovation in computer science.
Profile
Suitability Summary for Research for Best Researcher Award: Bei Guan
Bei Guan demonstrates strong qualifications that align well with the prestigious Research for Best Researcher Award. As a Senior Engineer (Associate Professor) at the Institute of Software, Chinese Academy of Sciences, his academic and professional journey shows a deep and sustained commitment to cutting-edge research in multiple high-impact areas such as Big Data Analytics, Cyber Security Analytics, Threat Intelligence, Virtualization, and Knowledge Graphs.
His research portfolio reflects significant contributions, particularly in developing novel algorithms and systems for detecting malicious cyber activities—work that has practical applications in national and global cybersecurity. The “Guilt by Association” graph inference technique he helped develop has been recognized as a major achievement, evidencing not only innovation but also real-world impact. Moreover, his leadership roles in major funded projects (with grants up to 1.5 million RMB) on intelligent diagnosis in Traditional Chinese Medicine and big data applications in industrial manufacturing highlight his capability to manage complex, interdisciplinary research programs successfully.
🎓 Education
Dr. Bei Guan holds a Ph.D. in Computer Science, during which he cultivated his proficiency in virtualization, cloud computing, and security systems. His academic training emphasized system-level design and optimization, culminating in research focused on enhancing VM communication efficiency and integrity measurement in virtual environments. Notably, he contributed to Google Summer of Code (GSoC) projects from 2011 to 2013, where he optimized I/O performance in Xen environments and advanced support for OVMF virtual firmware. These global collaborations provided hands-on experience with open-source communities and cutting-edge system architecture. Additionally, he participated in the prestigious Chinese Academy of Sciences (CAS) Main Direction Program for Cloud OS development, solidifying his role in trusted computing. This rigorous academic foundation, enriched by diverse international projects, laid the groundwork for Dr. Guan’s pioneering efforts in secure computing and big data analysis, which now anchor his research and leadership roles at the Chinese Academy of Sciences.
💼 Professional Experience
Dr. Bei Guan currently serves as a Senior Engineer (Associate Professor) at the Institute of Software, Chinese Academy of Sciences, where he has led national and industry-backed projects since 2018. Before that, from 2014 to 2018, he was a postdoctoral researcher at Qatar Computing Research Institute (QCRI), contributing to the renowned MADA project on malicious activity intelligence. His key roles involved developing graph-based inference systems to detect stealthy domains and contributing to one of QCRI’s major milestones, the “Guilt by Association” algorithm. At ISCAS, he spearheaded intelligent diagnostic systems using Traditional Chinese Medicine (TCM) data and big data analytics. He also managed AI-centric platforms in industrial manufacturing and civil aviation, employing microservices and neural networks for predictive analytics. Earlier in his career, he made significant contributions to virtualization and system security under GSoC and CAS initiatives. His work bridges academic excellence with practical, scalable system deployments.
🏅 Awards and Recognition
Dr. Bei Guan has earned notable recognition for his impactful research in cybersecurity and big data systems. His co-authored paper, “A Domain is only as Good as its Buddies,” presented at CODASPY 2018, received the Best Paper Award, affirming the importance of his graph-based malicious domain inference technique. His breakthrough work under the “Guilt by Association” framework was also prominently highlighted on the official website of QCRI as one of their leading achievements. In addition, Dr. Guan was a three-time recipient of Google’s highly selective Summer of Code (GSoC) grant, which underscored his technical innovation and collaboration with the open-source community. His continued success in securing significant national funding, including 1.5 million RMB from China’s Ministry of Science and Technology for TCM diagnostics, showcases the trust placed in his leadership. These honors reflect Dr. Guan’s ability to merge academic rigor with real-world impact in computer science.
🌍 Research Skills On Computer Science
Dr. Bei Guan demonstrates a multidisciplinary research portfolio combining system security, data analytics, knowledge representation, and AI. He is proficient in developing inference algorithms, designing knowledge graphs, and building data pipelines in complex domains like Traditional Chinese Medicine, civil aviation, and manufacturing. His core technical skills include graph-based anomaly detection, neural networks, virtualization technologies (Xen, OVMF), and microservice architecture. Dr. Guan effectively utilizes big data frameworks such as Hadoop and applies machine learning to detect malicious activity in DNS logs, IP clusters, and online behavior. His “Guilt by Association” model represents a milestone in cybersecurity analytics. Equally adept at theoretical modeling and system deployment, he integrates entity extraction, deep learning, and natural language processing in domain-specific knowledge bases. As a project manager and team leader, he brings strategic vision and execution capability to research translation. His dynamic skills enable him to contribute effectively across academic and industrial research collaborations.
Publication Top Notes
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Large language models meet nl2code: A survey
Authors: D. Zan, B. Chen, F. Zhang, D. Lu, B. Wu, B. Guan, Y. Wang, J.G. Lou
Citation: 202
Year: 2022 -
CERT: Continual pre-training on sketches for library-oriented code generation
Authors: D. Zan, B. Chen, D. Yang, Z. Lin, M. Kim, B. Guan, Y. Wang, W. Chen, J.G. Lou
Citation: 140
Year: 2022 -
Discovering malicious domains through passive DNS data graph analysis
Authors: I. Khalil, T. Yu, B. Guan
Citation: 135
Year: 2016 -
When language model meets private library
Authors: D. Zan, B. Chen, Z. Lin, B. Guan, Y. Wang, J.G. Lou
Citation: 79
Year: 2022 -
CIVSched: A Communication-aware Inter-VM Scheduling Technique for Decreased Network Latency between Co-located VMs
Authors: B. Guan, J. Wu, Y. Wang, S.U. Khan
Citation: 48
Year: 2014 -
Private-library-oriented code generation with large language models
Authors: D. Zan, B. Chen, Y. Gong, J. Cao, F. Zhang, B. Wu, B. Guan, Y. Yin, Y. Wang
Citation: 32
Year: 2023 -
Predictive value of serum thyroglobulin for structural recurrence following lobectomy for papillary thyroid carcinoma
Authors: S. Xu, H. Huang, X. Zhang, Y. Huang, B. Guan, J. Qian, X. Wang, S. Liu, Z. Xu, …
Citation: 31
Year: 2021 -
A domain is only as good as its buddies: Detecting stealthy malicious domains via graph inference
Authors: I.M. Khalil, B. Guan, M. Nabeel, T. Yu
Citation: 30
Year: 2018 -
Following passive DNS traces to detect stealthy malicious domains via graph inference
Authors: M. Nabeel, I.M. Khalil, B. Guan, T. Yu
Citation: 28
Year: 2020 -
Return-Oriented Programming Attack on the Xen Hypervisor
Authors: B. Ding, Y. Wu, Y. He, S. Tian, B. Guan, G. Wu
Citation: 27
Year: 2012
Dr. WEI-CHENG LIEN, Hyson Technology Inc, Taiwan
Research for Best Researcher Award: Wei-Cheng Lien
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