Cristina Gârbacea

Postdoctoral Scholar at UChicago DSI | Incoming Tenure-Track Faculty & Chief Scientist at CISPA

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🚀 Prospective PhD Students, Postdocs, and Research Interns: Starting September 2026, I will join the CISPA Helmholtz Center for Information Security as Tenure-Track Faculty & Chief Scientist, where I am founding the 💎 CRISTAL LabCommunication, Reasoning, Intelligence & Safety for Trustworthy ALignment.

I am actively recruiting fully funded PhD students, Postdocs, and Research Interns to join our founding team! If you are interested in LLM alignment, AI safety, agentic reasoning, continual learning, or related topics, see application details.


Biography

I am a Postdoctoral Scholar at the University of Chicago, Data Science Institute, working with Prof. Chenhao Tan and the Chicago Human+AI (CHAI) research group. I previously collaborated with Prof. Victor Veitch.

I earned my PhD in Computer Science and Engineering from the University of Michigan, advised by Prof. Qiaozhu Mei. My academic background also includes an MSc in Artificial Intelligence (cum laude) from the University of Amsterdam, and a double BSc in Computer Science and Electrical Engineering from Transilvania University of Brasov.

Complementing my academic work, I have completed several Research Scientist internships at Google DeepMind (London) and Microsoft Research (Redmond, Montreal, Cambridge) during my graduate studies.


Research Vision & Core Pillars

My research focuses on building human-aligned, safe, trustworthy and continuously adaptable AI systems. As foundation models transition from static text generators to active real-world agents, my work addresses core alignment, safety and adaptability challenges across the following key pillars:

  • 🎯 LLM Alignment: Developing principled, scalable methods to ensure foundation models adhere to human intent, values, and context-aware expectations across diverse user preferences.

  • 🛡️ AI Safety & Robustness: Developing verifiable alignment mechanisms, safety guarantees, and risk mitigation strategies for foundation models against unexpected failures and adversarial exploits.

  • 🤖 Agentic AI & Continual Learning: Investigating autonomous reasoning systems capable of long-horizon planning and tool interaction that adapt over time without safety drift or catastrophic forgetting.

  • 📊 Benchmarking & Evaluation: Creating evaluation environments resilient to benchmark contamination to accurately measure evolving AI capabilities and track real-world alignment progress.


News

Contact

If you would like to discuss potential research collaborations or prospective 💎 CRISTAL Lab opportunities, feel free to reach out at garbacea@uchicago.edu or garbacea@umich.edu.