School of Engineering
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Arjun Desai
Ph.D. Student in Electrical Engineering, admitted Autumn 2019
BioArjun Desai is a 4th year PhD candidate working with Akshay Chaudhari and Chris Ré. He is broadly interested in how we can accelerate the pace at which artificial intelligence can be used robustly, safely and at scale in practice. His research focuses on the intersection of signal processing and machine learning and how we can build scalable deployment and validation systems for applications in heathcare and the sciences.
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Yiwen Dong
Ph.D. Student in Civil and Environmental Engineering, admitted Autumn 2020
Ph.D. Minor, Electrical EngineeringBioYiwen Dong is a Ph.D. student in the Department of Civil and Environmental Engineering at Stanford University, advised by Prof. Hae Young Noh. Her research interest is human behavior characterization and health monitoring through their interactions with the physical structures. Her current work focuses on human and animal health monitoring through footstep/activity-induced structural vibrations.
While structures are traditionally considered as passive and indifferent, her works allow the structures to be both self-aware and user-aware. Yiwen developed systems that utilize the ambient structural vibrations to infer human behaviors and health states, which enables many smart building applications such as in-home patient monitoring and elder care, intruder prevention and occupant management, animal health monitoring and welfare. She strives for the next-generation intelligent infrastructures by exploring the potential of structural monitoring for human-centered purposes.
Yiwen has an interdisciplinary background in structural engineering, electrical engineering, and machine learning. Yiwen received her Master’s degree in Structural Engineering at Stanford University and her Bachelor’s degree in civil engineering at Nanyang Technological University. She won various awards (Best Paper Award, runner-ups in competitions) in ubiquitous computing and cyber-physical system conferences. She is passionate about combining the physical knowledge from structural dynamics, sensing approaches from cyber-physical systems, and data-driven models from machine learning to infer people’s characteristics, behavior patterns and health states.