Roberto Calandra

Research Scientist

I am a research scientist working on robotics and machine learning.

Previously, I was a postdoctoral scholar at UC Berkeley in the Berkeley Artificial Intelligence Research Laboratory working with Sergey Levine.

I received a PhD from TU Darmstadt (Germany) under the supervision of Jan Peters and Marc Deisenroth, an MSc in machine learning and data mining from the Aalto university (Finland), and a BSc in computer science from the Università degli studi di Palermo (Italy).


My scientific interests focus at the conjunction of Machine Learning and Robotics, in what is known as Robot Learning.

Related Links

Personal Website

Latest Publications

ICLR - May 4, 2021

Learning Invariant Representations for Reinforcement Learning without Reconstruction

Amy Zhang, Rowan McAllister, Roberto Calandra, Yarin Gal, Sergey Levine

AISTATS - April 13, 2021

On the Importance of Hyperparameter Optimization for Model-based Reinforcement Learning

Baohe Zhang, Raghu Rajan, Luis Pineda, Nathan Lambert, André Biedenkapp, Kurtland Chua, Frank Hutter, Roberto Calandra

RA-L - February 8, 2021

Model-Based Meta-Reinforcement Learning for Flight with Suspended Payloads

Suneel Belkhale, Rachel Li, Gregory Kahn, Rowan McAllister, Roberto Calandra, Sergey Levine

NeurIPS - December 7, 2020

3D Shape Reconstruction from Vision and Touch

Edward J. Smith, Roberto Calandra, Adriana Romero, Georgia Gkioxari, David Meger, Jitendra Malik, Michal Drozdzal

NeurIPS - October 22, 2020

Re-Examining Linear Embeddings for High-dimensional Bayesian Optimization

Benjamin Letham, Roberto Calandra, Akshara Rai, Eytan Bakshy

MICCAI - October 5, 2020

Active MR k-space Sampling with Reinforcement Learning

Luis Pineda, Sumana Basu, Adriana Romero, Roberto Calandra, Michal Drozdzal

ECCV - August 25, 2020

Adversarial Continual Learning

Sayna Ebrahimi, Franziska Meier, Roberto Calandra, Trevor Darrell, Marcus Rohrbach

Learning for Dynamics & Control (L4DC) - June 10, 2020

Plan2vec: Unsupervised Representation Learning by Latent Plans

Ge Yang, Amy Zhang, Ari Morcos, Joelle Pineau, Pieter Abbeel, Roberto Calandra

Learning for Dynamics & Control (L4DC) - June 10, 2020

Objective Mismatch in Model-based Reinforcement Learning

Nathan Lambert, Brandon Amos, Omry Yadan, Roberto Calandra

IEEE RA-L - June 1, 2020

DIGIT: A Novel Design for a Low-Cost Compact High-Resolution Tactile Sensor with Application to In-Hand Manipulation

Mike Lambeta, Po-Wei Chou, Stephen Tian, Brian Yang, Benjamin Maloon, Victoria Rose Most, Dave Stroud, Raymond Santos, Ahmad Byagowi, Gregg Kammerer, Dinesh Jayaraman, Roberto Calandra

ICRA - June 1, 2020

Learning Generalizable Locomotion Skills with Hierarchical Reinforcement Learning

Tianyu Li, Nathan Lambert, Roberto Calandra, Franziska Meier, Akshara Rai

CoRL - October 30, 2019

Data-efficient Co-Adaptation of Morphology and Behaviour with Deep Reinforcement Learning

Kevin Sebastian Luck, Heni Ben Amor, Roberto Calandra

IROS - July 29, 2019

Low Level Control of a Quadrotor with Deep Model-Based Reinforcement Learning

Nathan O. Lambert, Daniel S. Drew, Joseph Yaconelli, Sergey Levine, Roberto Calandra, Kristofer S. J. Pister