School of Engineering
Showing 161-170 of 360 Results
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Renesmee Kuo
Ph.D. Student in Electrical Engineering, admitted Autumn 2022
Masters Student in Electrical Engineering, admitted Autumn 2023BioRenesmee Kuo is an Electrical Engineering PhD candidate at Stanford University supported by NSF GRFP. She focuses on preclinical PET imaging for neuroinflammatory diseases and cancer in Prof. Michelle James' lab. She graduated from UC Berkeley with a BS in Bioengineering. Her research interests lie at the intersection of engineering and medicine. At UC Berkeley, she worked in Prof. Steve Conolly's lab on Magnetic Particle Imaging (MPI). She focused on tracking CAR-T cells in immunotherapy using high-resolution MPI tracers. She also focused on using commercially available high-resolution MPI tracers for early diagnosis of Pulmonary Embolisms and Cardiovascular disease in preclinical settings.
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Anand Vikas Lalwani
Ph.D. Student in Electrical Engineering, admitted Autumn 2018
BioAnand is a Graduate Student researcher in XLab (advisor: Debbie Senesky).
Anand's research work includes developing and deploying sensors for environmental and energy industries. Sensors developed include techniques for Hall Effect sensors to measure AC magnetic fields, deployable and low cost ammonia sensor for rivers and lakes, CO2 sensors for down-hole applications.
Anand's interests outside of research include startups and solving problems. Anand is committed to developing technologies that tackle pressing issues and translating work form lab into a startup. -
Axel Levy
Ph.D. Student in Electrical Engineering, admitted Autumn 2020
BioAxel is a PhD candidate in Electrical Engineering at Stanford University. He is jointly supervised by Pr. Mike Dunne (LCLS, SLAC) and Pr. Gordon Wetzstein. His research focuses on solving inverse problems that arise in scientific imaging, that is to say getting as much information as possible about hidden physical quantities from noisy or sparsely sampled measurements.
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Meijin Li
Masters Student in Electrical Engineering, admitted Autumn 2023
BioI'm Meijin Li, a software engineering and machine learning enthusiast, deeply engrossed in the real-world applications of AI+. I am presently pursuing a Master's degree in Electrical Engineering at Stanford University, specializing in the software system track.
I work at the intersection of machine learning, software, and cloud engineering in recent internship at Alibaba and project at Stanford, all about building AI traning or powered platform. I have a strong passion for real-world applications of AI+. I'm actively seeking software engineer opportunities.
During my undergraduate years, I was fortunate to work under the guidance of Prof. Zhiyang F. on multiple Reinforcement Learning and Computer Systems research projects. Additionally, I had the opportunity to further enhance my skills during my recent internship at Alibaba, with the expert mentorship of Mr. Qingnan Y. Here I was involved in developing an enterprise-level CI/CD/CT Web platform for Large Language Model training, deployment, and testing.
I am excited to leverage my skills and knowledge to drive advancements in this ever-evolving field and contribute to AI+ practical applications.
