Faculty Mentor: Tomaso Poggio
Direct Supervisor: Joel Z. Leibo
Home University: University of California, Santa Cruz
Major: Robotics Engineering
I was born and raised in the San Francisco Bay Area. Currently, I’m a fifth-year at the University of California in Santa Cruz (UC Santa Cruz) majoring in Robotics Engineering. My research interests are in Assistive and Biomedical Robotics, particularly focusing on biologically inspired robotics; in an effort to not only learn more about autonomous systems and the human body, but to also aid those who suffer from mental and/or physical ailments. My career goals are to procure a PhD in Robotic Engineering and a faculty position at a research-based university. I wish to manage my own research laboratory and teach the bright minds of tomorrow, in hopes of making the realm of biologically inspired robotics and its benefits to our society better known. Aside from academics, I love writing poetry, playing my Fender Telecaster, lounging on the beach, and spending time with my family. I am a firm believer that higher education and academics can lead to a brighter future for all of society.
A Model of Invariant Text Recognition in the Ventral Stream
The brain contains specialized modules involved in the visual processing of some object classes but not others. The object classes with specialized modules include—at least—faces, scenes, human bodies, and written words. The underlying computational reason for the brain to employ this modular architecture is unknown and all hypotheses remain controversial. A recent computational theory of the ventral stream implies modularity, however, its predictions have, so far, only been tested in the context of face recognition. By building a biologically-plausible model of the invariant recognition of text, in accord with the theory of modularity1, we may make more specific predictions about the modular architecture of the brain’s ventral stream and (maybe) how children learn to read.