I am an Assistant Professor in Yale’s Computer Science Department, where I lead the Yale Interactive Machines Group (IMG). My main area of research is Human-Robot Interaction (HRI). An updated list of my publications can be found here and in Google Scholar.
Before Yale, I was a Post-Doctoral Scholar at the Stanford Vision and Learning Lab working on the JackRabbot project. I closely collaborated with Disney Research while I was a Ph.D. student in the Robotics Institute (RI) at Carnegie Mellon University, and worked on assisted photography while pursuing my M.S. degree at the RI as well. Even before then, I built and learned how to fly a remote controlled helicopter! This allowed me to work on video stabilization for my bachelor’s degree in Computer Engineering at Universidad Simón Bolívar.
I study fundamental problems to enable group human-robot interactions. For instance, my work investigates social group phenomena in HRI, including spatial patterns of behavior typical of group conversations and group social influence. Further, I work on advancing autonomous, social robot behavior, both in terms of perception and decision making. An example is our work on learning social navigation policies, which has led us to create interactive online surveys to scale data collection in HRI. A key idea that has driven our recent work in group HRI is abstracting interactions as graphs. This allows robots to reason about individual, relationship and group factors in unison (e.g., see our work on group detection and pose generation). I also enjoy building robotic systems to demonstrate ideas in practice (Chester, Shutter). More details about my research can be found in my lab’s website.
My group’s research has been recognized by best paper award nominations (HRI’21, IROS’18, and RO-MAN’16), two Amazon Research Awards, and more.
If you are interested in joining my lab, please read this note about open positions at Yale IMG before contacting me.
NewsBelow are a few recent news from my research group and events that I have participated in:
Building Interactive Machines, Yale University
This project-based course brings together methods from Machine Learning, Computer Vision, Robotics, and Human-Computer Interaction to enable interactive machines to perceive and act in dynamic environments. Part of the course examines approaches for perception with a variety of devices and algorithms; the other part focuses on methods for decision making. The course is a combination of lectures, reviews of state-of-the-art papers, discussions, coding assignments, and a final team project.
Introduction to Human-Computer Interaction, Yale University
This course introduces students to the interdisciplinary field of Human-Computer Interaction (HCI). It covers principles and techniques in the design, development, and evaluation of interactive systems, and provides students with an introduction to UX Design and User-Centered Research. Additionally, some classes will focus on emergent areas within HCI, like Human-Robot Interaction, AR/VR, and Fabrication. The course is organized as a series of lectures, presentations, a mid-term exam, and group projects on designing new interactive systems.