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Sabrina M. Neuman
Sabrina M. Neuman
Assistant Professor
Boston University
Sabrina M. Neuman is an Assistant Professor at Boston University. Her research interests are in computer architecture design informed by explicit application-level and domain-specific insights. She is particularly focused on robotics applications because of their heavy computational demands and potential to improve the well-being of individuals in society. She received her S.B., M.Eng., and Ph.D. from MIT. She is a 2021 EECS Rising Star, and her work on robotics acceleration has received Honorable Mention in IEEE Micro Top Picks 2022 and IEEE Micro Top Picks 2023.
Brian Plancher
Brian Plancher
Assistant Professor
Barnard College, Columbia University
Brian Plancher is an Assistant Professor at Barnard College. His research is focused on developing and implementing open-source algorithms for dynamic motion planning and control of robots by exploiting both the mathematical structure of algorithms and the design of computational platforms. As such, his research is at the intersection of robotics and computer architecture / embedded systems, numerical optimization, and machine learning. He is passionate about improving accessibility of STEM education.
Wil Thomason
Research Scientist
The AI Institute
I am research scientist at The AI Institute.
Previously I was a postdoctoral researcher in the Kavraki Lab at Rice University. I worked with Professor Lydia Kavraki on combining symbolic and geometric planning.
I’m interested in improving the efficiency, robustness, and utility of robot task and motion planning (TMP), with a particular focus on making TMP under uncertainty practically useful.
Though I primarily research robot planning, I’m also interested in ML and formal methods for robotics, robotics research broadly, and programming languages. I was graciously funded by the CRA CIFellows 2021 postdoctoral fellowship.
Zak Kingston
Assistant Professor
Purdue University
I am an Assistant Professor in the Department of Computer Science at Purdue University, leading the Computational Motion, Manipulation, and Autonomy (CoMMA) Lab.
Previously, I was a postdoctoral research associate and lab manager for the Kavraki Lab at Rice University under the direction of Dr. Lydia Kavraki. During my Ph.D., I was funded by a NASA Space Technology Research Fellowship and worked with the Robonaut 2 team at NASA JSC. My research interests are in robot motion planning and long-horizon robot autonomy, with focus on manipulation planning, planning with constraints, and hardware and software for planning.
Radhika Ghosal
Radhika Ghosal
PhD Candidate
Harvard University
I’m a fifth-year PhD student in Computer Science at Harvard University, where I work in the Edge Computing Lab, advised by Profs. Vijay Janapa Reddi, David Brooks, and Gu-Yeon Wei.
I am interested in designing high-performance systems for robotics across multiple levels of the application stack: be it language design, runtime systems, or hardware accelerators. My research is supported by the NSF Graduate Research Fellowship (NSF GRFP).
I graduated with a Bachelor’s in Computer Science and Engineering from IIIT-Delhi in 2019, and have interned at Amazon Robotics (2023), Intel (2021), Microsoft Research (2018), and EPFL (2017) in the past.
For my notes on programming and electronics, head over to my blog; I used to run a series of graphic guides to algorithms on Algosaurus.
You can find me on GitHub.
Thomas Bourgeat
Thomas Bourgeat
Assistant Professor
École Polytechnique Fédérale de Lausanne (EPFL)
My research is between computer architecture and programming languages.
I work on leveraging high-level hardware programming languages to design hardware. I am especially interested in leveraging those hardware programming languages to ease verification, which is typically a significant part of the development effort.
Especially, I often try to use theorem proving to state and prove the properties of different architectures.
In the past, I worked on domain-specific hardware accelerators and I studied various unintended security consequences of modern microarchitectural features in our out-of-order processor (see our riscy-OOO project).
Vijay Janapa Reddi
Vijay Janapa Reddi
Associate Professor
Harvard University
Prof. Janapa Reddi is an Associate Professor in John A. Paulson School of Engineering and Applied Sciences at Harvard University. Prior to joining Harvard, he was an Associate Professor at The University of Texas at Austin. He is a founding member of MLCommons, serves on the MLCommons Board of Directors, and is a Co-Chair of MLPerf Inference. His primary research interests include computer architecture and system-software design to enable mobile computing and autonomous machines. His secondary research interests include building high-performance, energy-efficient and resilient computer systems.
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