Description

An in-person social event focused on supporting the queer community in robotics and AI research. We’ll meet up at 12:15 in front of the conference venue so we can go to the restaurant (Camino King’s Cross) together. Please sign up in advance if you want to attend.

Description

A social event focused on supporting the queer community in robotics and AI research, including an exciting talk over Zoom followed by a social in Gather.Town. Please sign up in order to get the event links. 

Abstract

“This talk discusses how robotics, algorithms, and so-called artificial intelligence are embedded within society and human lives, and the implications for the future of study and research into these fields. These implications concern both human lives and technological systems. Using multiple case studies to highlight places of tension where these technologies as they currently exist fail to account for the needs, experiences, and material conditions of multiple modes of human life, I make the case for an interdisciplinary program which foregrounds the lived experiential knowledge of marginalized people.”

Bio

Damien Patrick Williams is a PhD candidate in the Department of Science, Technology, and Society, at Virginia Tech in the United States. Damien researches how technologies such as algorithms, machine intelligence, and biotechnological interventions are impacted by the values, knowledge systems, philosophical explorations, social structures, and even religious beliefs of human beings. He is especially concerned with how the consideration and treatment of marginalized peoples will affect the creation of so-called artificially intelligent systems and other technosocial structures within human societies. More on Damien's research can be found at AFutureWorthThinkingAbout.com/?page_id=5038

Description

The panelists will present their research and engage each other in a discussion on their respective journeys to becoming roboticists. A virtual social for discussing the panel and networking will take place after.

Bios

Dr. Chollette Olisah received the B.Sc. degree in Computer Science from Anambra State University, Uli. She received her M.Sc. and Ph.D. degrees in Computer Science from the Universiti Teknologi Malaysia in 2011 and 2015, respectively. She began her academic career in 2016 and in 2019 progressed to Senior Lecturer at Baze University, Abuja, Nigeria. In 2017 she became a Fellow of the distinguished Massachusetts Institute of Technology Empowering the Teachers (MIT-ETT) Fellowship program held in fall, 2017. She is currently a Research Fellow in Computer Vision and Machine Learning with the Centre for Machine Vision at the University of the West of England, Bristol, UK. Dr. Chollette has authored over 18 peer-reviewed scholarly, conference, journal, and book chapter articles. Her research interests are in machine learning, computer vision, image processing, face recognition, image understanding, and analysis. Dr. Chollette has served as a reviewer for local and international journals and conferences.

Selim Tudgey graduated from the University of the West of England (UWE) with a degree in Aerospace Engineering whilst working in the automation machinery industry. She left the industry after 4 years to pursue a master’s in research engineering at UWE and afterwards a PhD in Robotics & Autonomous Systems at the University of Bristol.

Description

A social event celebrating women researchers at CoRL 2021, featuring a short panel discussion on career trajectories for women in robotics and machine learning. Space is limited, so please sign up if you plan to attend.

Bios

Dorsa Sadigh is an assistant professor in Computer Science and Electrical Engineering at Stanford University. Her research interests lie in the intersection of robotics, learning, and control theory. Specifically, she is interested in developing algorithms for safe and adaptive human-robot interaction. Dorsa has received her doctoral degree in Electrical Engineering and Computer Sciences (EECS) from UC Berkeley in 2017, and has received her bachelor’s degree in EECS from UC Berkeley in 2012. She is awarded the NSF CAREER award, the AFOSR Young Investigator Program Award, the IEEE TCCPS early career award, the Google Faculty Award, and the Amazon Faculty Research Award.

Chelsea Finn is an Assistant Professor in Computer Science and Electrical Engineering at Stanford University, and the William George and Ida Mary Hoover Faculty Fellow. Professor Finn's research interests lie in the ability to enable robots and other agents to develop broadly intelligent behavior through learning and interaction. Her work lies at the intersection of machine learning and robotic control, including topics such as end-to-end learning of visual perception and robotic manipulation skills, deep reinforcement learning of general skills from autonomously collected experience, and meta-learning algorithms that can enable fast learning of new concepts and behaviors. Professor Finn received her Bachelors degree in Electrical Engineering and Computer Science at MIT and her PhD in Computer Science at UC Berkeley.