Qi Alfred Chen
Computer Science · Purdue University West Lafayette
Publications
156
Citations
2,837
Est. group size
~1
Recurring co-author estimate
Active years
13
Publishing since 2014
Qi Alfred Chen's research focuses on the security and safety of autonomous driving systems and other cyber-physical systems, particularly how sensors like LiDAR, cameras, and thermal imagers can be attacked or spoofed, and how such vulnerabilities can be detected and defended against. Recent work also explores security risks in vision-language models and large language models applied to driving perception and planning, as well as hardware-level attacks such as keystroke eavesdropping. This work sits at the intersection of computer security, autonomous vehicle technology, and machine learning robustness.
Publication output grew substantially from 2017-2018 through a peak around 2021, and has remained fairly high (roughly 13-29 papers per year) over the past five years, though counts have declined somewhat in 2025-2026.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- BEVLM: Distilling Semantic Knowledge from LLMs into Bird's-Eye View Representations
Open MIND · 2026
- BEVLM: Distilling Semantic Knowledge from LLMs into Bird's-Eye View Representations
arXiv (Cornell University) · 2026
- DeFT: Maintaining Determinism and Extracting Unit Tests for Autonomous Driving Planning
Zenodo (CERN European Organization for Nuclear Research) · 2026
- DualStrike: Accurate, Real-time Eavesdropping and Injection of Keystrokes on Commodity Keyboards
2026
- The Heat is On: Understanding and Mitigating Vulnerabilities of Thermal Image Perception in Autonomous Systems
2026
- DeFT: Maintaining Determinism and Extracting Unit Tests for Autonomous Driving Planning
Zenodo (CERN European Organization for Nuclear Research) · 2026
- From Lab to Road: Realizing and Detecting LiDAR Spoofing Attacks Against Autonomous Vehicles at High Speed and Long Distance
IEEE Sensors Journal · 2025
- A Comprehensive Study of Bug-Fix Patterns in Autonomous Driving Systems
Proceedings of the ACM on software engineering. · 2025
- Breaking the Shield: Systematic Security Analysis on Pulse Fingerprinting LiDAR Systems for Autonomous Driving
IEEE Sensors Journal · 2025
- On the Realism of LiDAR Spoofing Attacks against Autonomous Driving Vehicle at High Speed and Long Distance
2025
- Revisiting Physical-World Adversarial Attack on Traffic Sign Recognition: A Commercial Systems Perspective
2025
- Slamspoof: Practical Lidar Spoofing Attacks on Localization Systems Guided by Scan Matching Vulnerability Analysis
2025
- ControlLoc: Physical-World Hijacking Attack on Camera-based Perception in Autonomous Driving
2025
- Are VLMs Ready for Autonomous Driving? An Empirical Study from the Reliability, Data, and Metric Perspectives
2025
- SLAMSpoof: Practical LiDAR Spoofing Attacks on Localization Systems Guided by Scan Matching Vulnerability Analysis
arXiv (Cornell University) · 2025
- arXiv (Cornell University)×38
- USENIX Security Symposium×3
- Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security×3
- IEEE Transactions on Intelligent Transportation Systems×2
- IEEE Sensors Journal×2
- Guangyu Shen
Computer Science · Purdue University West Lafayette
- Shengwei An
Computer Science · Purdue University West Lafayette
- Wenbo Guo
Computer Science · Purdue University West Lafayette
- Guanhong Tao
Computer Science · Indiana University
- Qiuling Xu
Computer Science · Purdue University West Lafayette
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 20, 2026.
Claim or correct this profile