Byron Boots is an Associate Professor in the Paul G. Allen School of Computer Science and Engineering (CSE) at the University of Washington where he directs the UW Robot Learning Laboratory. Byron is also a Principal Research Scientist in the Seattle Robotics Lab at NVIDIA Research, and is a co-chair of the IEEE Robotics and Automation Society Technical Committee on Robot Learning. He has received several awards including "Best Paper" Awards from ICML, AISTATS, RSS, and IJRR and is also the recipient of the RSS Early Career Award, the NSF CAREER Award, and the Outstanding Junior Faculty Research Award from the College of Computing at Georgia Tech. Byron received his PhD from the Machine Learning Department at Carnegie Mellon University.
Amirreza Shaban is a Postdoc Researcher in the Paul G. Allen School of Computer Science and Engineering (CSE) at the University of Washington where he works on perception models for off-road navigation systems that tightly integrate with planning and control algorithms. He received his Ph.D. in School of Interactive Computing within the College of Computing at Georgia Tech where he conducted research on computer vision algorithms in a low-shot learning regime advised by Prof. Byron Boots.
Sasha Lambert is a postdoctoral scholar at the University of Washington. His research focuses on machine learning and inference for perception and model predictive control. He received his Ph.D. and Master's degrees from Georgia Tech and his Bachelor's degree in Mechanical Engineering from McGill University, Canada.
Nolan Wagener is a Robotics PhD student in the School of Interactive Computing at Georgia Tech, working with Byron Boots and Panagiotis Tsiotras (Georgia Tech). His research focuses on safe reinforcement learning and model predictive control, with the goal of an agent being able to interact with and learn from an environment with little to no risk of damaging itself. He was an NSF Graduate Fellow from 2015 to 2018 and recipient of the Best Student Paper Award at RSS 2019.
Jake Sacks is a PhD student in the Paul G. Allen School of Computer Science and Engineering at the University of Washington (UW), working with Dr. Byron Boots. His research centers around machine learning for time series, dynamical systems, and control. He moved to UW from the Georgia Institute of Technology (Georgia Tech), where he was an Electrical and Computer Engineering (ECE) PhD student. He received his Masters degree in ECE from Georgia Tech and his Bachelors degree in Biomedical Engineering at the University of Texas at Austin. He was a National Defense Science and Engineering Graduate (NDSEG) fellow from 2015 to 2017. When not coding, he can be found playing guitar, biking, or playing an old Final Fantasy game from the golden era of video games.
Siddarth Srinivasan is PhD student in Prof. Byron Boots' Robot Learning Lab, at the Paul G. Allen School of Computer Science and Engineering. His current research explores connections between machine learning and quantum information, including ideas from quantum tensor networks, quantum tomography, spectral learning, dynamical systems, and kernel methods. He previously received his MS in Mathematics at Georgia Tech, and a BS in Physics from Harvey Mudd College.
Nathan Hatch joined the University of Washington CS PhD program in Winter 2020, after two and a half years in the Georgia Tech ML PhD program. Prior to that, he worked for three years as a software engineer at eSpark Learning, an education technology company that adaptively curates educational resources for grade school students based on their test scores. He completed his Bachelor of Science degree at the University of Chicago in 2014 with a double major in mathematics and computer science.
Anqi Li is a PhD student in the Paul G. Allen School of Computer Science and Engineering at the University of Washington, working with professor Byron Boots. Her research aims to make robot learning safe and sample efficient. She moved to the University of Washington from the Georgia Institute of Technology, where she was a Robotics PhD student. She received her Master's degree in Robotics from Carnegie Mellon University and her Bachelor's degree in Automation from Zhejiang University, China. Her research is supported by the NVIDIA Graduate Fellowship.
Mohak Bhardwaj is a PhD student in the Robot Learning Lab at the Paul G. Allen School of Computer Science and Engineering advised by Prof. Byron Boots. His research focuses on enabling scalable and efficient real-world robot learning with a specific focus on the intersection of reinforcement learning, model-predictive control and motion planning. Before moving to University of Washington, Mohak was a PhD Robotics student at Georgia Tech. Mohak received his MS in Robotic Systems Development from Carnegie Mellon University and Bachelor’s of Technology in Mechanical Engineering from IIT(BHU), Varanasi.
Sandesh Adhikary is a PhD student in the Paul G. Allen School of Computer Science and Engineering. His research has been focused on quantum-inspired probabilistic models for sequential data. In particular, he has worked on understanding how these models relate to models from classical machine learning in terms of expressiveness and learnability. Additionally, he has also been working with kernel-based sampling methods, particularly when applied to problems that require sampling over non-Euclidean Riemannian manifolds. He obtained his Bachelor's degree in Physics from Reed college, Portland, Oregon.
Adam Fishman is a fourth-year Computer Science PhD student in The Allen School at the University of Washington, where he is co-advised by Dieter Fox and Byron Boots. Currently, his research interests lie in end-to-end learning for closed-loop motion control in partially observable environments. Previously, he worked as a Computer Vision Engineer at Oculus VR. While there, he helped build the SLAM system for Oculus Quest. He likes to ride bikes, hike with his dog, and make pizza.
Yuxiang Yang is a PhD student in the CSE department, working with professor Byron Boots. His research aims to make robots actively perceive and interact with the external world, with a current focus on legged locomotion. Before UW, he received his Bachelor's degree in EECS at UC Berkeley and worked as a resident researcher in Robotics at Google.
Boling Yang is a Ph.D. student in the Paul G. Allen School of Computer Science and Engineering co-advised by Prof. Joshua Smith and Prof. Byron Boots. His current research focuses on making robots strategically and agilely interact with human users in certain competitive-HRI scenarios. Previously, Boling received his B.S. and M.S. degrees in Electrical Engineering from the University of Washington.
Carolina Higuera is a new Ph.D. student in the Paul G. Allen School of Computer Science and Engineering advised by Prof. Byron Boots. Her research interests are imitation learning and inverse reinforcement learning applied to robotics. She received her Master's degree in Electrical Engineering and Computers from Universidad de los Andes, Colombia, and her Bachelor's degree in Electrical Engineering from UPTC, Colombia.
Rosario is a PhD student in the Robot Learning Lab. He is interested in dynamic, robust, & resilient robots that adapt to the world around them. The goal of his research is to achieve these characteristics using tools from machine learning, motion planning, and adaptive control. Previously, he received BS degrees in EE/CompE from UConn and an MS from the Robotics Institute at CMU.
Brian (JoonHo) Lee is a Masters student in the Paul G. Allen School of Computer Science & Engineering at the University of Washington, joined Spring 2021. His research focuses on Robotic Vision and Deep Learning. He recently received his BS degree also at the University of Washington.
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