INTED
Mustafa Mirza is a Computer Science and Data Science student at the University of California, Berkeley, with extensive experience in software engineering, teaching, and machine learning research. Current roles include Software Engineer Intern at Deductive AI and a stealth startup, Teaching Assistant and Reader for CS 188 (Artificial Intelligence) at UC Berkeley, and Machine Learning Researcher at the FHL Vive Center for Enhanced Reality. Previous internships include contributions to Searchful and INTED, focusing on data scraping techniques and frontend development, respectively. Additionally, Mustafa has worked as a Contract Software Engineer at MDB and served as a CS 61B Academic Intern, aiding students in understanding data structures and algorithms.
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INTED
INTED increases audio & video comprehension, memorization and engagement by introducing AI-based personalized adaptive playback speed solution (USPTO patent pending). The scientific base behind the solution has been developed by researchers from Stanford University and UC Berkeley, and our own studies. The validated benefits include a 15%increase in comprehension, 10% increase in engagement and up to 65% savings in time, which is promised to be a game changer for non-native English speakers.