School of Engineering
Showing 101-200 of 357 Results
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Zengxiao He
Masters Student in Electrical Engineering, admitted Autumn 2024
Grader ENGR 108, Electrical Engineering - Student ServicesBioHi! I’m Zengxiao(Xander) He, a graduate student in Electrical Engineering at Stanford University, where I focus on artificial intelligence, deep learning, and computer vision. I completed my undergraduate degree in Software Engineering in China, where I developed a passion for creating real-world applications that improve people's lives.
I’m constantly curious about the latest advancements in technology, and I enjoy exploring innovative solutions to complex problems. I also have experience as a co-founder of HealX AI, a Chinese startup focused on using AI for medical diagnostics and healthcare improvement.
I am highly intrigued by the vibrant startup ecosystem in Silicon Valley and would love to connect with anyone who shares similar interests in AI, entrepreneurship, and technology. Let’s connect and explore how we can create impactful technologies together! -
Manchen Hu
Ph.D. Student in Electrical Engineering, admitted Autumn 2020
Student Trainer, Stanford Nano Shared Facilities Service CenterBioManchen Hu is an expert in optoelectronic engineering, with a specialization in the development of perovskite optoelectronic devices. He earned his bachelor's degree from Huazhong University of Science and Technology in Optoelectronic Engineering and a Master of Science degree from Stanford University in Electrical Engineering. Manchen possesses a deep passion for exploring light-matter interactions and light-emitting devices. His expertise uniquely positions him at the intersection of optics, electronics, and materials, equipping him with the skills necessary to optimize device performance and functionality. As an innovator in his field, Manchen is keen on collaborative endeavors that push the boundaries of optoelectronic research and applications.
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Mahnaz Islam
Ph.D. Student in Electrical Engineering, admitted Autumn 2019
Current Research and Scholarly InterestsMy current research focuses on understanding the physics of insulator-metal-transition (IMT) oxides such as niobium oxide and lanthanum cobalt oxide for applications in memory selectors and spike generators in brain-like computing.
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Andrei Kanavalau
Ph.D. Student in Electrical Engineering, admitted Autumn 2020
Masters Student in Electrical Engineering, admitted Winter 2023BioAndrei is a PhD candidate in the Electrical Engineering department at Stanford. His research focuses on augmenting control algorithms with machine learning while preserving safety and stability guarantees.
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Taeyoung Kong
Ph.D. Student in Electrical Engineering, admitted Autumn 2017
BioTaeyoung is a Ph.D. student at Stanford University working with prof. Mark Horowitz in VLSI group and he is currently working within the AHA Agile Hardware Project. He is interested in hardware accelerator for deep learning / image processing and hardware design methodology. Taeyoung received a B.S. in Electrical and Computer Engineering from Seoul National University in 2017, and M.S. in Electrical Engineering from Stanford University in 2020.
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Kalhan Koul
Ph.D. Student in Electrical Engineering, admitted Autumn 2019
BioKalhan Koul is an EE Ph.D. student at Stanford University supervised by Prof. Priyanka Raina. Previously, he was a Digital Design Intern at Micron and Silicon Labs. He received a B.S. in Electrical Engineering Honors and a B.A. in Plan II Honors (Liberal Arts) from The University of Texas in 2018 and his M.S. in Electrical Engineering from Stanford University in 2021. During his PhD he has worked on three chip tapeouts. The first was Chimera, a DNN accelerator utilizing RRAM for low energy inference. The next was Amber, a coarse grained reconfigurable array (CGRA) optimized for image processing and machine learning applications. Finally, Kalhan led the tapeout of Onyx, a CGRA accelerating both dense and sparse kernels on the same fabric. His current research focuses on further improving the efficiency of the CGRA and extending its acceleration to end-to-end machine learning workloads.
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Renesmee Kuo
Ph.D. Student in Electrical Engineering, admitted Autumn 2022
BioRenesmee Kuo is an Electrical Engineering PhD candidate at Stanford University supported by NSF GRFP. Her research interests lie at the intersection of engineering and medicine. She focuses on validation of preclinical PET imaging tracers and their translation into the clinic for applications in neuroinflammatory diseases (e.g., MS, AD) and cancer (e.g., brain metastasis) in Prof. Michelle James' lab. She graduated from UC Berkeley with a BS in Bioengineering. At Berkeley, she worked in Prof. Steve Conolly's lab on Magnetic Particle Imaging (MPI), focusing on tracking CAR-T cells in immunotherapy using high-resolution MPI tracers. She also explored 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. -
Matthew McCready
Ph.D. Student in Electrical Engineering, admitted Autumn 2021
Grader EE 261, Electrical Engineering - Student ServicesBioI 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.
