The UW — Amazon Science Hub, established in February 2022 to focus on advancing innovation in core robotics and AI technologies and their applications, today announced the first cohort of Amazon Fellows. Fellowships are awarded annually to PhD students enrolled in the UW College of Engineering.
Students will receive funding to pursue independent research projects in robotics and adjacent areas in AI, and will have an opportunity to participate in paid summer internships at Amazon where they can work directly with Amazon researchers to gain valuable industry insight and experience.
Below is information about the four recipients and their areas of research:
- Kyle Johnson is a third-year PhD student in the computer science and engineering department where he works in the Iyer Lab advised by Vikram Iyer, assistant professor of computer science and engineering. His research interest entail leveraging combinations of low-power actuators and the structural properties in systems to create insect-scale autonomous robots optimized for resource constrained applications.
- Michael Murray is a PhD student who works on robotics and artificial intelligence research at the Human-Centered Robotics Lab, advised by Maya Cakmak, the lab’s director and assistant professor of computer science and engineering. His research interests include robot learning, embodied artificial intelligence, and human-robot interaction. Prior to graduate school, Murray was a software engineer at Amazon where he worked on computer vision projects.
- Adhyyan Narang is a third-year PhD student, advised by Maryam Fazel, the Moorthy Family Professor and Lillian Ratliff, assistant professor of electrical and computer engineering. His research includes optimization, game theory, and statistical learning theory. He is also interested in developing theory to inspire the development of principled and robust ML systems.
- Niyousha Rahimi is a PhD student and member of the Robotics, Aerospace and Information Networks Lab, advised by Mehran Mesbahi, professor of aeronautics and astronautics. Her current research draws on tools and concepts from control theory, optimization, and machine learning, where she focuses on combining the best of learning approaches with robust/optimal control for autonomous navigation and control.