Stanford University
Showing 821-830 of 1,216 Results
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Michael P. Minitti
Senior Scientist, SLAC National Accelerator Laboratory
BioA native of Arizona, I studied chemistry at Mesa Community College and Arizona State University, receiving my bachelor’s degree in 2000. I then did graduate work in chemistry at SUNY Stony Brook and Brown University, eventually specializing in time-resolved studies of the dynamics of chemical reactions. Following my interest in combining chemistry with ultrafast lasers, I did postdoctoral research at Princeton and Brown before joining SLAC as a staff scientist in 2011.
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Kevin Mintz
Instructor, Pediatrics - Center for Biomedical Ethics
Current Role at StanfordSocial Science Research Scholar (Stanford Center for Biomedical Ethics)
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Brando Miranda
Research Asst - Graduate, Program-Koyejo, O.
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.
