Bio

Anka Reuel is a Computer Science Ph.D. student (with a Ph.D. minor in Political Science), advised by Prof. Mykel Kochenderfer and Prof. Sanmi Koyejo. She served as a vice chair for the European Commission in the recently concluded General-Purpose AI Code of Practice Process and was a 2024-25 Technology & Geopolitics Fellow at the Belfer Center at Harvard Kennedy School. Anka was the Responsible AI Lead for the 2024 and 2025 Stanford AI Index and the Lead AI Researcher for the Stanford Emerging Technology Review 2024 and 2025. Her work focuses on technical AI governance and in particular on improving the robustness and informativeness of evaluations for AI systems. Anka is further involved in national and international AI governance efforts. She is also a Stanford Interdisciplinary Graduate Fellow.

Anka was a Stanford HAI Graduate Fellow, a Fellow at the German National Academic Foundation, at the Hans-Weisser-Stiftung, and at the German Academic Exchange Program, and has won multiple awards for her work, including UPenn's Outstanding Academic Award 2022 and the Top Talents Under 25 Award. Anka is a first-generation, low-income student and a careleaver. To date, she keeps advocating in various roles to improve the conditions and opportunities for both of these groups. In her spare time, she is an avid traveler: Anka has visited 60 countries and lived in ten of them. She is also a casual triathlete.

Education & Certifications

  • MSE, University of Pennsylvania, Computer Science (2022)
  • MSc, London School of Economics, Management & Strategy (2016)
  • BSc, University of Hagen, Economic Sciences (2015)

Contact

  • Academic
    University - Student Department: Computer Science Position: Graduate

Additional Info

Current Research and Scholarly Interests

Inspired by the potential of intelligent technologies to improve lives, Anka began her M.S. in Computer Science at UPenn in 2020. She took the course CIS 522 'Deep Learning', which repeatedly raised the question of how developers can design more ethical algorithms. Interested in how the industry approaches the topic, she reached out to former colleagues and contacts, asking about how their companies manage the ethical implications of AI. Surprisingly, no one had an answer. They weren't managing adverse outcomes because they didn't know how. The problem was confirmed when she dived into research on the topic: Compared to the technical advancements in AI, the area of technical AI ethics was significantly understudied. Novel, complex autonomous systems were being developed without devoting enough time to their potential negative implications and how they can be mitigated. Given the increasing use of such systems throughout society, this discrepancy sparked her interest in contributing to research in responsible AI.

After working on technical projects on responsible AI, including using adaptive stress testing to avoid ethical dilemmas in autonomous decision-making, she also engaged with decision-makers on the AI governance side. These encounters expanded her research interests to not only making AI more ethical from a technical perspective but also designing effective AI governance interventions and ensuring that people without a technical background understand the technology and its implications better.

2025-26 Courses