Bernadette Bucher

Bernadette Bucher

About

I am a computer science PhD Student in the GRASP lab at University of Pennsylvania co-advised by Dr. Kostas Daniilidis and Dr. Nikolai Matni. During my PhD studies, I completed a M.S.E. in Robotics from University of Pennsylvania in 2020 and was awarded the Haidas and Chryssikou Fellowship for my research.

My research interests lie in the intersection of robotics, computer vision, and machine learning. The focus of my PhD research is on improving the generalization ability of vision-based models for robotic manipulation and navigation to novel data.

During my PhD, I interned in the Seattle Robotics Lab at NVIDIA Research. Prior to starting my PhD, I was a Senior Software Engineer at Lockheed Martin Corporation where I worked from 2014 to 2019. I received an M.A. in Mathematics, M.A. in Economics, and B.S. in Mathematics and Economics from The University of Alabama in 2014.

Publications

Learning to Map

Georgios Georgakis*, Bernadette Bucher*, Karl Schmeckpeper, Siddharth Singh, Kostas Daniilidis.
Learning to Map for Active Semantic Goal Navigation.
ICLR, 2022.

arXiv / project page / code / bibtex

Bridge Data

Frederik Ebert, Yanlai Yang, Karl Schmeckpeper, Bernadette Bucher, Georgios Georgakis, Kostas Daniilidis, Chelsea Finn, Sergey Levine.
Bridge Data: Boosting Generalization of Robotic Skills with Cross-Domain Datasets.
RSS, 2022.
NeurIPS Workshop on Deep Reinforcement Learning, 2021.

arXiv / project page (code and dataset) / bibtex

Uncertainty-driven Planner

Georgios Georgakis, Bernadette Bucher, Anton Arapin, Karl Schmeckpeper, Nikolai Matni, Kostas Daniilidis.
Uncertainty-driven Planner for Exploration and Navigation.
ICRA, 2022.

arXiv / project page / code / bibtex

Adversarial Exploration

Bernadette Bucher*, Karl Schmeckpeper*, Nikolai Matni, Kostas Daniilidis.
An Adversarial Objective for Scalable Exploration.
IROS, 2021.

arXiv / project page / code / bibtex

RoboNet

Sudeep Dasari, Frederik Ebert, Stephen Tian, Suraj Nair, Bernadette Bucher, Karl Schmeckpeper, Siddharth Singh, Sergey Levine, Chelsea Finn.
RoboNet: Large-Scale Multi-Robot Learning.
CoRL, 2019.
NeurIPS Workshop on Deep Reinforcement Learning, 2019.

arXiv / project page / code / bibtex

Workshop Papers and Preprints

Curiosity Increases Equality

Bernadette Bucher*, Siddharth Singh*, Clélia de Mulatier, Kostas Daniilidis, Vijay Balasubramanian.
Curiosity Increases Equality in Competitive Resource Allocation.
ICLR Workshop on Bridging AI and Cognitive Science, 2020.

paper / bibtex

Action for Better Prediction

Bernadette Bucher*, Karl Schmeckpeper*, Nikolai Matni, Kostas Daniilidis.
Action for Better Prediction.
RSS Workshop on Visual Learning and Reasoning for Robotic Manipulation, 2020.

paper / project page / bibtex

Portrait Style Representations

Sadat Shaik*, Bernadette Bucher*, Nephele Agrafiotis, Stephen Phillips, Kostas Daniilidis, William Schmenner.
Learning Portrait Style Representations.
arXiv Preprint, 2020.

arXiv / dataset / labeling tool / bibtex

Perception-Driven Curiosity

Bernadette Bucher, Anton Arapin, Ramanan Sekar, Feifei Duan, Marc Badger, Kostas Daniilidis, Oleh Rybkin.
Perception-Driven Curiosity with Bayesian Surprise.
RSS Workshop on Combining Learning and Reasoning Towards Human-Level Robot Intelligence, 2019.

paper / bibtex

Unsupervised Monocular Depth

Kenneth Chaney*, Bernadette Bucher*, Evangelos Chatzipantazis, Jianbo Shi, Kostas Daniilidis.
Unsupervised Monocular Depth And Latent Structure.
CVPR Workshop on 3D Scene Understanding for Vision, Graphics, and Robotics, 2019.

paper / bibtex