Service & Outreach

The workshop aimed to develop a shared community-level understanding of task specification in various formalisms and modalities. Topics of discussion covered defining a task specification, characteristics of task specification frameworks, communicating task specifications with robots, and compatibility with different specification formalisms, sensor modalities, and algorithms.

The workshop brought together (1) leaders in the areas of robot learning (e.g., imitation learning, inverse reinforcement learning), shared control/autonomy, and supervisory control and (2) experts in a range of applied areas (e.g., manufacturing, surgery) to discuss the relationship between task criteria, robot representations, context, and desired qualities for human interaction mechanisms.

The sixth iteration of this workshop discussed breakthroughs, open challenges, and limitations of recent techniques in human motion anticipation and long-term predictions of human movement trajectories, body poses, actions or activities.

The fourth edition of the workshop brought together interdisciplinary perspectives on real-world applications in HRI, including education, rehabilitation, elderly care, service, and companion robotics. The primary objective was to explore the concept of lifelong robot learning and the ability to continually adapt to users, contexts and environments in long-term HRI.

The workshop brought together interdisciplinary experts in interactive machine learning, reinforcement learning, human-computer interaction, cognitive science, and robotics to discuss interaction-grounded learning from multiple (potentially arbitraty) feedback signals, non-stationary human preferences and rewards, and the trade-off between pre-training and personalization.

I was the lead organizer and HRI representative for the DREAM/CPAR Seminar at UC Berkeley, a weekly seminar hosting professors/professionals in robotics, control, and human-centered autonomy.

This workshop brought together experts from representation learning, human-robot interaction, and cognitive science to discuss how the robot learning community can best benefit from learning representations from human input and vice-versa, and how the HRI community can best direct their efforts towards discovering more effective human-robot teaching strategies.

This workshop brought together experts from cognitive science and developmental psychology to better understand the principles and origins of human social intelligence, and experts from AI and Robotics, to discuss how to engineer socially intelligent artificial agents, and how these paradigms can be deployed in both virtual and real scenarios.

The workshop brought together AI and robotics experts to discuss the greatest challenges facing imitation learning for robotics. Topics discussed included interactive imitation learning, multi-modal imitation learning, deep inverse reinforcement learning, cognitive models for learning from demonstration and planning, few-shot imitation learning, and learning from non-expert demonstrations.

I co-organized the SemiAutonomous seminar at UC Berkeley, a well established weekly seminar series that brings together students and professors (internal and external to Berkeley) from machine learning, control theory, and robotics.

RoboLaunch is a robotics outreach and broadening participation initiative, making robotics more accessible. I was an invited speaker, and I presented state-of-the-art work in HRI, answered the teams' research questions, and discussed the intricacies of doing research in academia and industry.

GiE is a week-long non-residential summer camp where female middle school students can learn engineering in an engaging, hands-on environment. I co-organized one of the Self-Driving Cars workshops, where I taught the girls about sensing, planning, and control in autonomous driving, and mentored them in experimenting with an Evo robot.

AI4ALL is a 5-day non-residential summer program, that exposes Bay Area 9th to 11th grade students from underrepresented groups to AI. I mentored a team of students as they learned to train a deep reinforcement learning agent in MuJoCo.

As a BAIR mentor, I mentored underrepresented undergraduate students in research and career planning.

As a WiCSE mentor, I mentored early-stage female PhD students in career planning and the PhD journey.