School of Engineering
Showing 1,501-1,600 of 2,782 Results
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Jade Marcus
Ph.D. Student in Chemical Engineering, admitted Autumn 2023
Current Research and Scholarly InterestsActivating mg-silicates for fertilizer applications to remove CO2 and reduce N2O emissions while increasing crop yields, plant resiliency, and soil health
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Megan Martin
Ph.D. Student in Bioengineering, admitted Autumn 2024
Current Research and Scholarly InterestsCharacterization of brain waste clearance with motion-encoding MRI
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Russell Martin
Ph.D. Student in Mechanical Engineering, admitted Autumn 2020
BioPhD student with the Stanford Biomechatronics Lab (biomechatronics.stanford.edu).
LinkedIn: linkedin.com/in/russell-m-martin/
Scholar: scholar.google.com/citations?user=h1vmmG0AAAAJ&hl=en
Website: russellmmartin.github.io -
Ryosuke Mashiko
Ph.D. Student in Electrical Engineering, admitted Autumn 2025
BioRyosuke Mashiko is a Ph.D. student in the Department of Electrical Engineering at Stanford University. He graduated from the University of Tokyo with a B.E. (2022) and an M.E. (2024), where he worked on computational imaging based on unsupervised learning and large-scale optical computing. Currently, he works on integrated photonics for sensing and computing applications.
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Emilin Maria Mathew
Masters Student in Computer Science, admitted Autumn 2023
Stanford Student Employee, Emergency MedicineBioScientist-technologist passionate about designing accessible healthcare solutions
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Matthew McCready
Ph.D. Student in Electrical Engineering, admitted Autumn 2021
BioI am a 1st year PhD Student in Electrical Engineering at Stanford, with a M.Sc in Physics from The University of Western Ontario. I have over 4 years of research experience across various projects in medical and condensed matter physics. My interests focus on the design and development of tools that improve quality of life through the application of physics.
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Yuchen Mei
Ph.D. Student in Electrical Engineering, admitted Autumn 2023
BioYuchen Mei is an EE Ph.D. student at Stanford University in Prof. Priyanka Raina's group. He received a B.S. degree in Electronic Information Science and Technology from Nanjing University (China) in 2021 and a M.S. degree in Electrical Engineering from Stanford in 2023. He is interested in digital VLSI design, domain-specific accelerators, and design automation.
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Brando Miranda
Ph.D. Student in Computer Science, admitted Autumn 2022
BioBio
Brando Miranda is a current Ph.D. Student at Stanford University under the supervision of Professor Sanmi Koyejo in the department of Computer Science. Previously he has been a graduate student at University of Illinois Urbana-Champaign, Research Assistant at MIT’s Center for Brain Minds and Machines (CBMM), and graduate student at the Massachusetts Institute of Technology (MIT). Miranda’s research interests lie in the field of meta-learning, foundation models for theorem proving, and human & brain inspired Artificial Intelligence (AI). Miranda completed his Master of Engineering in Electrical Engineering and Computer Science under the supervision of Professor Tomaso Poggio – where he did research on Deep Learning Theory. Miranda has been the recipient of several awards, including Most Cited Paper Certificate awarded by International Journal of Automation & Computing (IJAC), two Honorable Mention with the Ford Foundation Fellowship, Computer Science Excellence Saburo Muroga Endowed Fellow, Stanford School of Engineering fellowship, and is currently an EDGE Scholar at Stanford University.
About me (Informal)
I am a scientist and an engineer that is interested in moving forward the powerful and beautiful field of A.I. closer to true Artificial General Intelligence (AGI). I believe an important direction is understanding how to combine cognitive and neuro-inspired models, specially investigating how reasoning and learning work together. In addition, I also believe being able to adapt to new tasks using prior experience and knowledge is crucial for AGI to occur. Consequently, I decided to pursue a Ph.D in AI and machine learning. I currently work on meta-learning and machine learning (ML) for Theorem Proving (TP) at Stanford University.
