Anca Dragan

Anca Dragan is a computer scientist and roboticist known for work on human-robot interaction, inverse reinforcement learning, and safe AI. She is a faculty member at the University of California, Berkeley and has contributed to research at institutions such as the Massachusetts Institute of Technology, Carnegie Mellon University, and Google. Her work bridges technical areas including machine learning, control theory, and ethics, engaging with communities from the Association for the Advancement of Artificial Intelligence to the IEEE.

Early life and education

Dragan completed undergraduate and graduate training at institutions including the Massachusetts Institute of Technology, where she studied under advisors connected to research labs such as the Computer Science and Artificial Intelligence Laboratory and the Lab for Information and Decision Systems. Her doctoral work drew on methods from reinforcement learning, probabilistic robotics, and human-robot collaboration developed alongside researchers at Stanford University, Carnegie Mellon University, and Cornell University. Early influences include scholars from the University of California, Berkeley, the University of Washington, and the California Institute of Technology, as well as connections to conferences like the Conference on Neural Information Processing Systems, the International Conference on Robotics and Automation, and the International Joint Conference on Artificial Intelligence.

Academic career and positions

Dragan holds a faculty position at the University of California, Berkeley in the Department of Electrical Engineering and Computer Sciences and is affiliated with research centers including the Berkeley Artificial Intelligence Research Lab and the Center for Human-Compatible Artificial Intelligence. She has collaborated with researchers at Google DeepMind, OpenAI, Facebook AI Research, Microsoft Research, and IBM Research, and has held visiting roles connected to institutions such as ETH Zurich, MIT, and Princeton University. Her academic appointments involve teaching courses related to topics featured at venues like the Neural Information Processing Systems, the International Conference on Machine Learning, the Association for Computing Machinery, and the Institute of Electrical and Electronics Engineers.

Research contributions

Dragan's research spans inverse reinforcement learning, preference learning, and safe human-aware motion planning, intersecting with work by scholars from Stanford University, Carnegie Mellon University, and the Swiss Federal Institute of Technology. She has published at conferences including the Conference on Neural Information Processing Systems, the International Conference on Robotics and Automation, the International Conference on Machine Learning, and the Association for the Advancement of Artificial Intelligence. Her contributions connect to methods from reinforcement learning pioneered by researchers at DeepMind, Berkeley, and OpenAI, and to motion planning frameworks developed at MIT, Carnegie Mellon, and Stanford. She has advanced algorithms that build on probabilistic models used by the University of Oxford, University of Cambridge, and the University of Toronto, and her work informs applications in autonomous driving explored by Waymo, Tesla, Uber, and NVIDIA. Collaborations and citations link her work to scholars at Harvard University, Yale University, Columbia University, and Johns Hopkins University, and to laboratories such as the Robotics Institute, Google Brain, Microsoft Research, and the Allen Institute for Artificial Intelligence.

Awards and honors

Dragan has received recognition from professional societies and conferences including the Association for the Advancement of Artificial Intelligence, the Institute of Electrical and Electronics Engineers, and the Association for Computing Machinery. Her honors are in the context of awards presented at venues like the International Conference on Robotics and Automation, the Conference on Robot Learning, and the Neural Information Processing Systems. Colleagues at institutions such as Stanford University, MIT, Carnegie Mellon University, and UC Berkeley feature in award panels and program committees alongside recipients from Google, Facebook, Amazon, and Microsoft.

Outreach and public engagement

Dragan engages with public audiences through talks at symposiums and panels hosted by organizations including the National Academies, the World Economic Forum, the Brookings Institution, and the Royal Society. She participates in workshops and seminars associated with the IEEE, the ACM, the Alan Turing Institute, and the Centre for Future Studies, and collaborates with policy groups at the United Nations, the European Commission, and the Partnership on AI. Her outreach reaches media outlets and podcasts that cover developments at institutions such as MIT Technology Review, Nature, Science, The New York Times, The Washington Post, and BBC.

Category:Computer scientists Category:Roboticists