Andreea Bobu is an Assistant Professor at MIT in AeroAstro and CSAIL. She leads the Collaborative Learning and Autonomy Research Lab (CLEAR Lab), where they develop autonomous agents that learn to do tasks for, with, and around people. Their goal is to ensure that these agents' behavior is consistent with human expectations, whether they interact with expert designers or novice users.

Her work looks at: 1) getting the right data to supervise agents, whether directly from people or via priors; 2) enabling humans and robots to efficiently and interactively arrive at shared task representations; 3) quantifying and addressing misalignment caused by different human modeling choices. She ground her work in experiments and user studies with AI systems like assistive robot arms or LLMs, and draw upon methods from deep learning, mathematical human modeling, inverse reinforcement learning, and Bayesian inference.

She obtained her Ph.D. in Electrical Engineering and Computer Science at UC Berkeley with Anca Dragan. You can read her thesis here. Before MIT, she was also a Research Scientist at the AI Institute and an intern at NVIDIA in the Robotics Lab. Prior to her graduate degree, she received a B.S. in Computer Science at MIT.

Professor Bobu is primarily interested in mentoring a research project on computer use agents and safety railguards for them.

In terms of hard skills, ideal candidates should have one or more of the following:

• Previous research experience in machine learning (or related fields), ideally with published work.

• A strong software engineering background and familiarity with machine learning tools and techniques.

• Experience with computer use agents (Anthropic Computer Use, OpenAI Operator) is a plus.

• Experience with running human subject experiments and statistical analyses is a plus.

As for soft skills:

• The ability to communicate clearly.

• Strong intrinsic motivation and curiosity for learning.

• A desire to publish an academic paper.

• A sense for how to build a story is useful, in that doing good, impactful research also involves communicating said research in a way that the community is drawn to and compelled by.