School of Engineering
Showing 1-73 of 73 Results
-
Joseph Alan McCoy
Masters Student in Computer Science, admitted Autumn 2022
Stanford Student Employee, Undergrad Housing Front DesksBioBorn and raised in Central IL. I enjoy soccer, tennis, and cross-country and I can always have a good time playing board games or video games. I may be shy at first, but it doesn't take me long to break out of my shell. Now, I am an aspiring surgeon, pursuing that path as a Cardinal, Class of 2025. I yearn to learn, to enhance myself as a person and the knowledge that I hold, helping whoever I can along the way.
-
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. -
Robert Moss
Ph.D. Student in Computer Science, admitted Autumn 2021
BioRobert Moss is a computer science Ph.D. student at Stanford University studying algorithms to validate safety-critical autonomous systems. He holds an M.S. in computer science from Stanford where his research received the best computer science master’s thesis award and he also received the Centennial TA award for his teaching efforts. He earned his B.S. in computer science with a minor in physics from the Wentworth Institute of Technology in Boston, MA. Robert was an associate research staff member at MIT Lincoln Laboratory where he was on the team that designed, developed, and validated the next-generation aircraft collision avoidance system for commercial aircraft, unmanned vehicles, and rotorcraft. Robert was also a research engineer at the NASA Ames Research Center, developing decision support tools for the VIPER autonomous Lunar rover mission searching for water deposits on the Moon. Robert is a member of the Stanford Intelligent Systems Laboratory, the Stanford Center for Earth Resources Forecasting, and part of the Stanford Center for AI Safety conducting research on methods for high-dimensional planning under uncertainty using low-dimensional surrogate models, autonomous vehicle risk assessment, and efficient algorithms for safety validation.
