Welcome to my academic profile! I am Qingli Zeng, a PhD in Computer Science at the University of Missouri - Kansas City (UMKC). My research is primarily focused on Unmanned Aerial Vehicle (UAV) networks, with a particular interest in enhancing the security, efficiency, and autonomy of these systems through advanced machine learning techniques and bio-inspired algorithms. I am passionate about exploring the intersection of UAV technology, cybersecurity, and artificial intelligence, aiming to develop innovative solutions that address real-world challenges in these fields.
My current projects include the development of robust intrusion detection systems for UAV networks, the creation of dynamic routing protocols inspired by biological systems, and the use of reinforcement learning to improve the coordination of drone swarms. I am dedicated to advancing knowledge in my field and am always excited to collaborate with fellow researchers and industry professionals to push the boundaries of what is possible in UAV and cybersecurity technologies. You can find my papers at google scholar.
📝 Publications
Enhancing UAV Network Security: A Human-in-the-Loop and GAN-Based Approach to Intrusion Detection.
IEEE Internet of Things Journal.
Qingli Zeng, Farid Nait-Abdesselam
Project/Dataset
Multi-Agent Reinforcement Learning-Based Extended Boid Modeling for Drone Swarms.
IEEE International Conference on Communication (ICC) 2024.
Qingli Zeng, Farid Nait-Abdesselam
- Multi-Agent Reinforcement Learning-Based Extended Boid Modeling for Drone Swarms.
IEEE International Conference on Communication (ICC) 2024.
Qingli Zeng, Farid Nait-Abdesselam
- Leveraging Human-In-The-Loop Machine Learning and GAN-Synthesized Data for Intrusion Detection in Unmanned Aerial Vehicle Networks.
- Cooperative and Autonomous Flocking of Drones Using an Extended BOID Model,Qingli Zeng, Harir Razzazi, Farid Nait-Abdesselam, IEEE Global Communications Conference (GLOBECOM) 2024.
- A HITL-Integrated Machine Learning Approach to Secure Drone Networks for IIoT Applications, Qingli Zeng, Farid Nait-Abdesselam, ZhiQiang Chen, IEEE Globecom Workshops (GC Wkshps) 2023.
- Realtime Intrusion Detection In Unmanned Aerial Vehicles Using Active Learning and Generative Adversarial Networks, Qingli Zeng, Kailynn Barnt, Luke Ragan, Farid Nait-Abdesselam, 2023 IEEE 29th International Conference on Parallel and Distributed Systems (ICPADS).
- An Enhanced Online K-Means Algorithm for Flooding Attacks Detection in Vehicular Networks, Harir Razzazi, Qingli Zeng, Farid Nait-Abdesselam, 2024 International Wireless Communications and Mobile Computing (IWCMC).
- FGA-IDS: A Federated Learning and GAN-Augmented Intrusion Detection System for UAV Networks, Qingli Zeng, Semire Olatunde-Salawu, and Farid Nait-Abdesselam, The 10th IEEE International Conference on Collaboration and Internet Computing (CIC) 2024.
- Scalable and Probabilistic Point-Cloud Generation for UAS-Based Structural Assessment, Qingli Zeng, ZhiQiang Chen, EVACES 2021.
- Human-in-the-loop robotic inspection-framework and Point Cloud assessment, ZhiQiang Chen, Qingli Zeng, AI・データサイエンス論文集.
🎖 Honors and Awards
- Spring 2024, 53rd class of Women’s Council GAF Awards(Merit).
- Spring 2025, 54th class of Woman’s Council GAF Awards(Merit).
- Academic year 2024-2025, UMKC Research Grants.
- Fall 2023, Spring 2024,UMKC SGS Travel grant and Balaji travel grant.
- 2018, Robocup first prize.
- 2024, Usenix OSDI student travel grant.
- 2024, UMKC Hack a Roo Competition.
📖 Educations
- 2020.09 - 2025.05, PhD, Computer Science, University of Missouri Kansas City, Kansas City, MO, USA.
- 2020.01 - 2021.10, Master, Computer Science, University of Missouri Kansas City, Kansas City, MO, USA.
- 2016.09 - 2020.09, Undergraduate, Automation, Beijing Information Science and Technology University, Beijing, China.
💻 Work Experience
- Graduate Research Assistant, Jan 2021 - August 2022, Jun 2023 - Sep 2023, Jun 2024 - Sep 2024.
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Developed AR Flooding Project for KC Water Company, including city modeling, rendering, 3D printing, and developing an AR simulation to visualize and analyze flooding scenarios. (Jan 2021 – Aug 2022). Project link.
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Research for intrusion detection system and routing protocol for UAVs swarm networks. (Jun 2023 - Sep 2023, Jun 2024 - Sep 2024).
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Mentored 6 undergraduate students from UMKC. (Jun 2023 - Sep 2023, Jun 2024 - Sep 2024, Jan 2025- May 2025).
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Assisted in conducting a Cybersecurity Summer Camp for high school students, providing hands-on guidance.(June–September 2023, June–September 2024).
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Graduate Teaching Assistant, Sep 2022 - Present.
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Network Architecture (Sep 2022 - May 2024).
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Python Programming (Jan 2024 - Present).
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🧑🏫 Mentoring
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For undergraduate students Kailynn Barnt, Luke Ragan （Jun 2023 - Sep 2023）.
Kailynn and Luke worked with me on the Realtime intrusion detection for UAV networks. This work was accepted by IEEE ICPADS 2023.
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For undergraduate student Abdalrahman Bashir（Since Jun 2024) .
Abdalrahman works with me on the Bio-Inspired Routing Solution for UAV Swarms. This work was submitted to INFOCOM 2025. With submissions based on this work, Abdalrahman won UMKC Hack a Roo competition 2024. Abdalrahman is looking into producing the intrusion detection dataset for UAV swarm networks.
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For undergraduate student Semire Olatunde-Salawu （Jun 2024 - Sep 2024）.
Semire worked with me on Federated Learning based IDS for UAV swarm networks. This work was accepted by IEEE CIC 2024.
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For undergraduate student Gregory Linville （Jun 2024 - Sep 2024）.
Gregory worked with me on Efficient Data Compression for Large-Scale Storage Systems.
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For undergraduate student Samuel Yohannes （January 2025 - May 2025）.
Samuel will work with me from January 2025, he is going to explore the LSTM and Neural Networks based IDS for UAV swarms networks.
🏢 Professional Service
- Reviewing
- 2023 International Conference on Modeling & E-Information Research, Artificial Learning and Digital Applications (ICMERALDA) (19).
- 2023 IEEE Global Communications Conference: Mobile and Wireless Networks (1).