cv
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Basics
| Name | Siqi Li |
| Label | PhD Student in Computer Engineering |
| siqi.li@uci.edu | |
| Phone | (415) 515-9562 |
| Url | https://siqilii.github.io |
| Summary | Machine learning researcher focused on AI alignment and safety, including adversarial robustness, vision-language-action models, and LLM reasoning. Committed to building reliable AI systems through robust, systematic evaluation. |
Work
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2024.09 - Present PhD Student — Resilient Cyber-Physical Systems Lab
University of California, Irvine
Research on AI alignment and safety under Prof. Yasser Shoukry. Developing adversarial detection methods with formal guarantees, progress-monitored verification for VLA models, and LLM preference personalization.
- KoALA: Adversarial detector with provable guarantees (ICLR'26 submission)
- Progress-monitored verification for vision-language-action robot policies
- Reinforcement fine-tuning for LLM preference following
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2022.12 - 2024.05 Visiting Student Researcher
California Institute of Technology
Research on human-robot collaboration under Prof. John Doyle. Combined large language models with model-predictive control for task planning and trajectory optimization.
- Human natural language to robotic skills and control
- LLM + MPC integration for robot task planning
- Visual-language model feedback for improved performance
Education
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2024.09 - Present Irvine, CA, USA
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2020.11 - 2022.11 Karlsruhe, Germany
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2015.09 - 2020.07 Shanghai, China
Awards
- 2024.09.01
Graduate Dean's Recruitment Fellowship
University of California, Irvine
Awarded to top 2% of incoming graduate students.
- 2024.09.01
AGS Conference Stipend
University of California, Irvine
Awarded to top 5% of graduate students for conference travel.
- 2020.01.01
China Automotive Science and Technology Award
China Society of Automotive Engineers
Highest prize for cloud control energy-saving algorithm development.
Publications
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2025.01.01 KoALA: KL-L0 Adversarial Detector via Label Agreement
arXiv (under review at ICLR 2026)
Adversarial detection method combining KL divergence with L0-based label agreement, with formal detection guarantees.
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2024.11.01 Optimizing Rare Word Accuracy in Direct Speech Translation with a Retrieval-and-Demonstration Approach
EMNLP 2024
Retrieval-augmented approach for rare word translation in end-to-end speech translation, achieving 17.6% improvement.
Skills
| Machine Learning | |
| Vision-Language Models | |
| Adversarial Robustness | |
| Reinforcement Learning | |
| LLM Fine-tuning | |
| Retrieval-Augmented Generation |
| Programming | |
| Python | |
| C/C++ | |
| MATLAB | |
| Julia | |
| ROS |
Languages
| Mandarin | |
| Native speaker |
| English | |
| Professional |
| German | |
| Professional |
Interests
| AI Safety & Alignment | |
| Adversarial Robustness | |
| Formal Verification | |
| Trustworthy AI |
| Robotics | |
| Vision-Language-Action Models | |
| Human-Robot Collaboration | |
| Autonomous Systems |