Henrik I. Christensen (Qualcomm)
Prof. Henrik I. Christensen is the Qualcomm Chancellor's Chair of Robot Systems and a Professor of Computer Science at
Dept. of Computer Science and Engineering UC San Diego. He is also the director of the Institute for Contextual Robotics. His research has a strong emphasis on "real problems with real solutions".
*Topic: Robust grasp preimages under unknown mass and friction distributions.
Tamim Asfour (KIT)
Tamim Asfour is full Professor at the Institute for Anthropomatics and Robotics, where he holds the chair of
Humanoid Robotics Systems and is head of the High Performance Humanoid Technologies Lab (H2T). His current research interest is high performance 24/7 humanoid robotics.
*Topic: Current Successes and Future Challenges in Humanoid Grasping and Manipulation in
the Real World.
Serena Ivaldi (INRIA)
Serena is a tenured research scientist in INRIA Nancy Grand-Est (France), working in the project-team LARSEN.
Serena is currently focused on robots collaborating with humans. She is interested into combining ML with control to improve the prediction and interaction skills of robots.
*Topic: Teaching a Robot to Grasp Irregular Objects with Machine Learning and
Hao Su (UC San Diego)
Hao Su has been in UC San Diego as Assistant Professor of Computer Science and Engineering since July 2017. He is affiliated with the Contextual Robotics Institute and
Center for Visual Computing. He served on the program committee of multiple conferences and workshops on computer vision, computer graphics, and machine learning. He is the Area Chair of CVPR'19.
*Topic: Semantic Scene Segmentation using PartNet Models.
Luis Seabra Lopes (Uni. of Aveiro)
Luis Seabra Lopes
is Associate Professor of Informatics in the Department of Electronics,
Telecommunications and Informatics of the University of Aveiro, Portugal. He received a PhD
in Robotics and Integrated Manufacturing from the New University of Lisbon, Portugal, in 1998.
Luís Seabra Lopes has long standing interests in robot learning, cognitive robotic architectures,
and human-robot interaction.
*Topic: Interactive Open-Ended Learning Approaches for 3D Object Recognition.
Yukie Nagai (Uni. of Tokyo)
Yukie Nagai has been investigating underlying neural mechanisms for social cognitive development by means of computational approach.
She designs neural network models for robots to learn to acquire cognitive functions such as self-other cognition, estimation of others’ intention and emotion, altruism,
and so on based on her theory of predictive learning.
*Topic: Cognitive Development Based on Sensorimotor Predictive Learning..
Shuran Song (Columbia Uni.)
Shuran Song will be joining the School of Computing Science at Columbia University in New York, as an Assistant Professor in 2019.
She earned her Ph.D. degree in Computer Science at Princeton University in 2018. During her Ph.D., she spent time working at Microsoft and Google.
Her research interests lie at the intersection of computer vision, computer graphics, and robotics.
*Topic: Robotic Pick-and-Place of Novel Objects in Clutter with Multi-Affordance Grasping.
Carlos Celemin Paez (Delft Uni.)
Carlos is a Postdoctoral researcher in the Cognitive Robotics Department at Delft University of Technology, in the group of Learning and Autonomous
Control. His research is focused on Machine Learning for robot control, combining Reinforcement learning and human feedback in order to obtain data efficient methods which make
feasible to learn directly on real systems.
*Topic: Teaching Robots Interactively from few corrections: Learning Policies and Objectives.
Julian Ibarz (Google AI)
Julian Ibarz is a Staff Software Engineer at Google AI. He is a technical lead within the Google Brain Robotics team and
work on making robots smarter with deep reinforcement learning techniques. Prior to that, he worked 5 years in the Google Maps team helping automating mapping using deep learning.
*Topic: Challenges of Self-Supervision via Interaction in Robotics.
Luca Carlone (MIT)
Luca Carlone is the Charles Stark Draper Assistant Professor in the Department of Aeronautics and
Astronautics at the Massachusetts Institute of Technology, and a Principal Investigator in the Laboratory for Information & Decision Systems (LIDS).
He received his PhD from the Polytechnic University of Turin in 2012. His research interests include nonlinear estimation, numerical
and distributed optimization, and probabilistic inference, applied to sensing, perception, and decision-making in single and multi-robot systems.
*Topic: It kinda works! Challenges and Opportunities for Robot Perception in the Deep Learning Era.