School of Engineering
Showing 351-400 of 2,309 Results
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Steve Cousins
SRC Executive Director, Computer Science
Current Role at StanfordExecutive Director of the Stanford Robotics Center
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Róbert Csordás
Postdoctoral Scholar, Computer Science
BioI am a postdoctoral researcher in the Stanford NLP Group, supervised by Prof. Christopher Manning and Prof. Christopher Potts. Previously, I did my PhD in IDSIA, supervised by Prof. Jürgen Schmidhuber. I work on systematic generalization, mainly in the context of algorithmic reasoning. This drives my research interest in network architectures (Transformers, DNC, graph networks) with inductive biases like information routing (attention, memory) and learning modular structures. My goal is to create a system that can learn generally applicable rules instead of pure pattern matching but with minimal hardcoded structure. I consider the lack of systematic generation to be the main obstacle to a more generally applicable artificial intelligence.
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Andrea Cuadra
Postdoctoral Scholar, Computer Science
BioI am a postdoc working with James Landay. My field is Human-Computer Interaction, and my work lies at the intersection of interaction design, inclusivity, and artificial intelligence. I study the needs of marginalized groups who may particularly benefit from or be harmed by the outcomes of technology design decisions that affect us all. In addition, I employ my design skills to generate and advocate for more-inclusive design alternatives.
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David Dai
Masters Student in Computer Science, admitted Autumn 2022
BioI am a masters student at Stanford University majoring in Computer Science. I am currently in Stanford SVL and Partnership in AI-Assisted Care (PAC) Lab supervised by Dr. Fei-Fei Li and Dr. Ehsan Adeli.
Before joining Stanford, I graduated with the highest honor in Computer Science and Math from Emory University. I was in the Emory Brain Network Lab under the supervision of Dr. Carl Yang working on graph mining in the area of healthcare.
My research interests lie in computer vision, graph learning, bioinformatics, AI in healthcare, interpretation, and explainability.
