Data Science Summer 2022 Capstone Project Showcase
Capstone projects are the culmination of the MIDS students’ work in the School of Information’s Master of Information and Data Science program.
Over the course of their final semester, teams of students propose and select project ideas, conduct and communicate their work, receive and provide feedback, and deliver compelling presentations along with a web-based final deliverable.
Join us for an online presentation of these capstone projects. Each team will present for twenty minutes, including Q&A.
A panel of judges will select an outstanding project for the Hal R. Varian MIDS Capstone Award.
Kyle Hamilton, MIDS ’17, taught Machine Learning at Scale for four years after graduating the MIDS program. She also served as course coordinator and acting course lead during that time. She is a three-time recipient of the Distinguished Faculty Award for this work. She is currently pursuing a Ph.D. in machine learning at Technological University Dublin in Ireland, specializing in neurosymbolic AI and natural language processing. Her research cuts across multiple disciplines at the intersection of sociolinguistics and AI, focusing on the detection and interpretation of rhetoric and propaganda in news articles. In addition to research, Kyle is also the chief innovation and data officer at iQ4, a digital talent cloud infrastructure platform that enables a skills marketplace for learning and hiring. Prior to pursuing a career in data, Kyle studied and worked as a fine artist and designer. She holds a B.F.A. from Cooper Union in NYC.
Dr. Marti Hearst is Head of School and professor at the UC Berkeley School of Information and a professor in the Computer Science Division. Her research encompasses user interfaces with a focus on search, information visualization with a focus on text, computational linguistics, and educational technology. She is the author of Search User Interfaces, the first academic book on that topic. She co-founded the ACM Learning@Scale conference, is a former president of the Association for Computational Linguistics, a member of the CHI Academy and the SIGIR Academy, an ACM fellow, and has received four Excellence in Teaching Awards from the students of UC Berkeley. She received her Ph.D., M.S., and B.A. degrees in computer science from UC Berkeley and was a member of the research staff at Xerox PARC.
Daniel Kent, MIDS ’19, is the director of product management for personalization at Dow Jones, which brings together world-leading data, media, membership, and intelligence solutions to power the most ambitious companies and professionals. Previously he was the lead product manager for machine learning at Glassdoor, one of the world’s largest job and recruiting sites, leading all machine learning product teams that are developing solutions to power the company’s next generation business and consumer products. He’s the co-founder of Jobwell.co, a patent-pending AI-enabled platform to help jobseekers manage all of their job applications and networking. Jobwell was recently named as one of 18 services with transformative potential to serve both sides of the labor market and boost the career prospects for millions of American workers.
Dan also founded Net Literacy.org/AI Literacy.org, a tech-oriented nonprofit focused on increasing digital and AI literacy that has donated over 44,000 computers and $14M in services. Net Literacy’s services were highlighted by the FCC in the national broadband plan presented to Congress; they received Computerworld’s 21st Century Award for creating “the most innovative application of IT to extend the distribution of digital information and access to web-based programs and services to previously underserved populations” and have been honored by two US presidents, including one in a private White House ceremony.
He has served as a judge and mentor to venture teams at UC Berkeley's LAUNCH Accelerator, The Yale School of Management Program on Entrepreneurship, and Tsai CITY Summer Fellowship and Accelerator at Yale University. Dan has a MIDS degree from the School of Information at UC Berkeley and an MBA from the Yale School of Management.
Andrew Kiruluta, MIDS ’21, leads a machine learning research group for drug discovery at Pfizer consisting of a team of data scientists developing the next generation of drugs using AI. He was previously at Novartis and Microsoft Research working on large NLP models for drug discovery pipelines. He got his Ph.D. from the University of Toronto in the field of condensed matter physics, a postdoc fellow at Cavendish Lab, Cambridge University, followed by another post-doctorate position at JILA national optics lab in Boulder, Colorado. He subsequently took a faculty position at Harvard University where he taught and conducted physics research for 15 years before joining industry in the emerging AI research space. He is also a graduate of the MIDS program at UC Berkeley.