School of Engineering
Showing 1,251-1,300 of 2,227 Results
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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. -
Aadhityaa Mohanavelu
Ph.D. Student in Civil and Environmental Engineering, admitted Autumn 2023
BioAadhityaa Mohanavelu is a Ph.D. candidate in the Osman Lab at Stanford University, where he works on quantifying water and infrastructure challenges and developing more equitable and resilient infrastructure systems. His research uses tools and techniques from diverse disciplines, including computational modeling, artificial intelligence, qualitative methodology, spatial analysis, and sensor-based experiments, to better understand infrastructure and environmental problems and develop innovative solutions.
He has a strong background in modeling hydro-climatic systems, studying infrastructure resilience, and assessing environmental hazards. Aadhityaa is a 2023 Quad Fellow in the inaugural cohort. Outside research, he loves to hike, read books and travel.
