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Service & Outreach

I enjoy organizational and mentoring activities which involves the broader robotics community. Below you will find some of the recent conference workshops I've co-organized as well as my outreach activies.

Workshops

Robotics for People (R4P): Perspectives on Interaction, Learning and Safety

Organizing committee, RSS 2021

By bridging the HRI, ML, and MP communities, this workshop aims to create a road map for developing safer and smarter robots.

RSS Pioneers

Co-chair, RSS 2021

RSS Pioneers aims to bring together a cohort of the world’s top early career researchers to foster creativity and collaborations surrounding challenges in all areas of robotics, as well as to help young researchers navigate their next career stages.

3rd Workshop on Long-term Human Motion Prediction

Co-organizer, ICRA 2021

This workshop is third in a series of ICRA 2019-2020 events. The aim of this workshop is to bring together researchers and practitioners from different communities and to discuss recent developments in this field, promising approaches, their limitations, benchmarking techniques and open challenges.

2nd Workshop on Robust Autonomy: Tools for Safety in Real-World Uncertain Environments

Co-organizer, RSS 2020

When autonomous systems such as self-driving cars and robotic manipulators are deployed in real-world environments, it is of the utmost importance to consider---and ideally to guarantee---safe runtime operation. Since these systems often operate in highly uncertain and dynamic environments, it is crucial for them to model and quantify environmental uncertainty, understand its impact on system dynamics, predict the motion of other agents, and make safe, risk-aware decisions. Safety and robustness have been studied extensively from a theoretical perspective, and there are several prominent success stories in application, e.g. in aviation. However, techniques with strong theoretical safety properties have yet to penetrate many new and exciting robotic application areas, such as autonomous driving, in which uncertainty in environmental perception and prediction overwhelm traditional safety analysis.

Robust Autonomy: Tools for Safety in Real-World Uncertain Environments

Co-organizer, RSS 2019

When autonomous systems such as self-driving cars and robotic manipulators are deployed in real-world environments, it is of the utmost importance to consider---and ideally to guarantee---safe runtime operation. Since these systems often operate in highly uncertain and dynamic environments, it is crucial for them to model and quantify environmental uncertainty, understand its impact on system dynamics, predict the motion of other agents, and make safe, risk-aware decisions. Safety and robustness have been studied extensively from a theoretical perspective, and there are several prominent success stories in application, e.g. in aviation. However, techniques with strong theoretical safety properties have yet to penetrate many new and exciting robotic application areas, such as autonomous driving, in which uncertainty in environmental perception and prediction overwhelm traditional safety analysis.

Outreach

BAIR Research Experience for Undergraduates (REU)

Mentor, Speaker, 2021

A paid research experience for students at Historically Black Colleges and Universities (HBCUs) and Predominately Black Institutions (PBIs) in order to help prepare students for careers in AI, whether in industry or academia. Demonstration of research potential is increasingly a critical prerequisite for graduate school admissions and AI-focused positions, and our hope is to provide more students with an opportunity and environment to perform exciting research and demonstrate their potential.

AI4ALL

Mentor, 2020

UC Berkeley AI4ALL gives high school students who are underrepresented in AI the opportunity to learn how to use AI to make a positive impact on their community while learning about career pathways in AI. Participants get hands-on experience with AI, hear from a diverse set of role models in AI on their work and research, and learn about how AI can be used to benefit society. After the camp, students will be invited to join the AI4ALL alumni community, Changemakers in AI, where they will have access to further support including mentorship, research and internship opportunities, and peer community.

Girls in Engineering Camp

Mentor, 2018 - 2019

A week-long, non-residential summer camp for San Francisco Bay Area students entering 6th, 7th, and 8th grades to explore different aspects of what it means to be an engineer in a fun, hands-on environment.

Berkeley Artificial Intelligence Research

Mentor, 2018

Monthly mentoring of an underrepresented student in research and career planning.