Andreea Bobu
Berkeley Artificial Intelligence Research
Electrical Engineering and Computer Science
University of California Berkeley
8043-5 Berkeley Way West, 2121 Berkeley Way, Berkeley, CA 94704
I am on the faculty job market in Fall 2022.
I am a Ph.D. candidate at UC Berkeley in EECS, where I am advised by Anca Dragan in the InterACT Lab. My Ph.D. is supported by the Apple AI/ML Fellowship. I previously received a B.S. in Computer Science and Engineering at MIT in 2017.
I work at the intersection of robotics, mathematical human modeling, and deep learning. In my research, I study algorithmic human-robot interaction, with a focus on how robots and humans can efficiently arrive at shared representations of their tasks for more seamless and reliable interaction. I ground my work in experiments with robotic systems like assistive robot arms and in user studies with real human participants.
news
Organizing a workshop on "Aligning Robot Representations with Humans " at the Conference on Robot Learning 2022.
Giving an invited talk at the Robotics Colloquium at UW.
Giving an invited talk at the New Trends in Aerospace Seminar Series at MIT.
New paper accepted to HRI, "SIRL: Similarity-based Implicit Representation Learning", where we enable robots to learn salient feature representations by asking humans to gauge how similar different behaviors are.
I gave an invited talk at the Robotics Seminar at Cornell.
I was invited to speak at University of Utah's CS 6960: Human-AI Alignment graduate course.
I gave an invited talk in the Robot Autonomy and Interactive Learning (RAIL) Lab at Georgia Tech.
Our paper on Time-Efficient Reward Learning via Visually Assisted Cluster Ranking has been accepted to the Human-in-the-loop Learning (HILL) Workshop at NeurIPS 2022.
I gave an invited talk at the Illinois Robotics Seminar at UIUC.
I gave an invited talk in the Intelligent and Interactive Autonomous Systems Group (ILIAD) Group at Stanford.
I am grateful to have been selected for the Rising Star in EECS Academic Career Workshop!
I gave an invited talk at the Workshop on Complex Feedback in Online Learning at ICML.
Co-organized a workshop on "Social Intelligence in Humans and Robots" at Robotics: Science and Systems 2022.
New paper accepted to IROS, "Teaching Robots to Span the Space of Functional Expressive Motion", where we enable people to efficiently teach robots expressive motions during task execution.
New paper accepted to Robotics and Automation Letters, "Learning Perceptual Concepts by Bootstrapping from Human Queries". In this work, we ask for human input to learn a low-dimensional variant of the perceptual concept, then use it to generate a larger data set for learning the concept in the high-dimensional space.
I gave an invited talk at Apple's AI/ML seminar.
I was named a Robotics: Science and Systems Pioneer!
Our paper on Aligning Robot Representations with Humans has been accepted to the Workshop on Collaborative Robots and the Work of the Future, at ICRA 2022.
Our paper "Inducing Structure in Reward Learning via Feature Learning" was accepted at the International Journal of Robotics Research.
I gave an invited talk at Aware-learning: how to benefit from priors, a workshop at the Conference on Decision and Control.
I gave an invited talk at MIT's Interactive Robotics Group.
I was named an Apple Scholar in AI and Machine Learning (AI/ML)!
Our journal paper "Quantifying Hypothesis Space Misspecification in Learning from Human-Robot Demonstrations and Physical Corrections" received an Honorable Mention for the 2020 IEEE Transactions on Robotics King-Sun Fu Memorial Best Paper Award.
Our paper on reward learning using feature traces, a novel type of human input, was nominated for a Best Paper Award at the ACM/IEEE International Conference on Human-Robot Interaction 2021.
Our paper "Situational Confidence Assistance for Lifelong Shared Autonomy" was accepted at the IEEE International Conference on Robotics and Automation 2021.