World's Best Scientists 2026 revealed!
Award Badge
Computer Science
USA
2026

D-Index & Metrics

Computer Science

D-Index
117
Citations
55107
World Ranking
169
National Ranking
99

Research.com Recognitions

  • 2026 - Research.com Computer Science in United States Leader Award
  • 2025 - Research.com Computer Science in United States Leader Award
  • 2023 - Research.com Computer Science in United States Leader Award
  • 2022 - Research.com Computer Science in United States Leader Award
  • 2001 - ACM Fellow For the development of the theory of dynamic failure in real-time fault-tolerant computing.
  • 1992 - IEEE Fellow For contributions to the theory of dynamic failure in real-time computing systems

Overview

Kang G. Shin is affiliated with the University of Michigan-Ann Arbor in the United States. Their research spans multiple fields, primarily focused on engineering and computer science. Within these broad domains, their work concentrates on subfields such as electrical and electronic engineering, computer networks and communications, transportation, artificial intelligence, and hardware and architecture.

The scientist has contributed extensively in topics related to advanced wireless communication technologies, advanced malware detection techniques, vehicular ad hoc networks (VANETs), advanced MIMO systems optimization, real-time systems scheduling, autonomous vehicle technology and safety, and privacy, security, and data protection.

Their recent publications include:

  • "SpecHammer: Combining Spectre and Rowhammer for New Speculative Attacks" (2022) published in the 2022 IEEE Symposium on Security and Privacy (SP)
  • "Automated Extraction and Presentation of Data Practices in Privacy Policies" (2021) published in Proceedings on Privacy Enhancing Technologies
  • "S2-CAN: Sufficiently Secure Controller Area Network" (2021) published in the Annual Computer Security Applications Conference
  • "A Survey on Controller Area Network Reverse Engineering" (2023) published in IEEE Communications Surveys & Tutorials
  • "Fuzzing Hardware Like Software" (2021) published in arXiv (Cornell University)

Kang G. Shin collaborates frequently with several coauthors, including Suining He, Zheng Yan, Zhao Li, Jia Liu, and Mert D. Pesé. These partnerships have contributed to a variety of studies across the multiple subfields of their research.

The scientist often publishes in venues such as arXiv (Cornell University), IEEE Transactions on Mobile Computing, Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies, Proceedings on Privacy Enhancing Technologies, and IEEE Transactions on Knowledge and Data Engineering.

Recognition for their contributions includes distinctions as an ACM Fellow in 2001 for the development of the theory of dynamic failure in real-time fault-tolerant computing, and as an IEEE Fellow in 1992 for contributions to the theory of dynamic failure in real-time computing systems.

Best Publications

  • Real-time dynamic voltage scaling for low-power embedded operating systems

    Padmanabhan Pillai;Kang G. Shin

  • Minimum-time control of robotic manipulators with geometric path constraints

    Kang Shin;N. McKay

  • Efficient Discovery of Spectrum Opportunities with MAC-Layer Sensing in Cognitive Radio Networks

    Hyoil Kim;K.G. Shin

  • Detecting SYN flooding attacks

    Haining Wang;Danlu Zhang;Kang G. Shin

  • A self-configuring RED gateway

    W.-C. Feng;D.D. Kandlur;D. Saha;K.G. Shin

  • The BLUE active queue management algorithms

    Wu-chang Feng;Kang G. Shin;Dilip D. Kandlur;Debanjan Saha

  • Performance guarantees for Web server end-systems: a control-theoretical approach

    T.F. Abdelzaher;K.G. Shin;N. Bhatti

  • Adaptive control of virtualized resources in utility computing environments

    Pradeep Padala;Kang G. Shin;Xiaoyun Zhu;Mustafa Uysal

  • Goodput analysis and link adaptation for IEEE 802.11a wireless LANs

    Daji Qiao;Sunghyun Choi;K.G. Shin

  • Hop-count filtering: an effective defense against spoofed DDoS traffic

    Cheng Jin;Haining Wang;Kang G. Shin

  • Automated control of multiple virtualized resources

    Pradeep Padala;Kai-Yuan Hou;Kang G. Shin;Xiaoyun Zhu

  • On task schedulability in real-time control systems

    D. Seto;J.P. Lehoczky;L. Sha;K.G. Shin

  • Real-time computing: a new discipline of computer science and engineering

    K.G. Shin;P. Ramanathan

  • A dynamic programming approach to trajectory planning of robotic manipulators

    Kang Shin;N. McKay

  • Defense against spoofed IP traffic using hop-count filtering

    Haining Wang;Cheng Jin;Kang G. Shin

  • Fingerprinting electronic control units for vehicle intrusion detection

    Kyong-Tak Cho;Kang G. Shin

  • E-MiLi: Energy-Minimizing Idle Listening in Wireless Networks

    Xinyu Zhang;Kang G. Shin

  • Behavioral detection of malware on mobile handsets

    Abhijit Bose;Xin Hu;Kang G. Shin;Taejoon Park

  • Large-scale malware indexing using function-call graphs

    Xin Hu;Tzi-cker Chiueh;Kang G. Shin

  • CIRCA: a cooperative intelligent real-time control architecture

    D.J. Musliner;E.H. Durfee;K.G. Shin

  • Real-time communication in multihop networks

    D.D. Kandhlur;K.G. Shin;D. Ferrari

Frequent Co-Authors

Sunghyun Choi
Sunghyun Choi Samsung (South Korea)
Victor C. M. Leung
Victor C. M. Leung Shenzhen University
Edmund H. Durfee
Edmund H. Durfee University of Michigan–Ann Arbor
Tarek Abdelzaher
Tarek Abdelzaher University of Illinois at Urbana-Champaign
Jennifer Rexford
Jennifer Rexford Princeton University
Xinyu Zhang
Xinyu Zhang University of California, San Diego
Wu-chang Feng
Wu-chang Feng Portland State University
Haining Wang
Haining Wang Virginia Tech
Kyu-Han Kim
Kyu-Han Kim Pathlight - Performance Intelligence Platform
Ming-Syan Chen
Ming-Syan Chen National Taiwan University

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring computer science opens the door to a variety of online degrees and fast-track career options. For students seeking affordability, you might consider pursuing the cheapest data science degree in the USA. This path can provide valuable analytical and technical skills at a lower cost, making it ideal for budget-conscious learners.

Engineering-focused students may be interested in an online master’s in electrical engineering degree. This is a popular choice for those wanting to expand their expertise in technology and innovation, all while maintaining flexibility through online learning.

If you’re eager to enter the workforce quickly, there are short certificate programs that pay well. These targeted certifications can help you secure high-demand roles without the time or cost commitment of a longer degree.

For those aiming to advance their careers rapidly, consider the quickest masters degree online. These accelerated programs are designed to help you complete your education faster, giving you a competitive edge in the tech field.

Best Scientists Citing Kang G. Shin

Trending Scientists

Recently Published Articles