Data Science Summer 2021 Capstone Project Showcase for 5th Year MIDS Students
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 5th Year MIDS Capstone Award.
As the head of data and analytics engineering at Eventbrite, Archana drives actionable insights for product strategy, go-to-market, and customer value from data. She has built cross-functional teams of top caliber data science, engineering, and product analytics talent and partners and aligns with executives and stakeholders to enable and evangelize data-driven decisions. Before coming to Eventbrite, Archana worked at Splunk for eleven years, starting as a research engineer and progressed up to the senior director of data and insights. Archana has a B.A. in computer science, an M.S. in computer science, and a Ph.D. in computer science, all from UC Berkeley.
Amitabha Karmakar, MIDS ’17
Amit is a vice president at American Express where he works on AI initiatives and strategies. Prior to that, he was a vice president at Peloton and an executive director at J.P. Morgan where he was head of engineering and architecture for data. Amit has a Master of Information and Data Science degree from the UC Berkeley School of Information.
Charles Kekeh, MIDS ’16
Charles Kekeh has over twenty years of experience in the development of computer systems. He started my career as a software development engineer working on multiple client and server platforms. He spent eight of those years at Microsoft working initially on client and server platforms in Windows and in the Windows Server and Tools business as a software development lead. After those years, he was fortunate to get exposure to science work, working as an individual contributor in the Bing organization on the initial release of the Cortana personal assistant as an engineer, and supporting science teams working on statistical models for natural language understanding. That experience convinced him to enroll in the MIDS program starting in the summer of 2015 as a full-time student. After completing the program in 12 months, he transitioned into a career as a professional data scientist, working at a startup in Boston on medical risk prediction using deep longitudinal patient cohort data. That experience opened the doors for him to rejoin the world of personal voice assistants with Amazon Alexa where he has been working since 2017 as an applied scientist with a current focus on neural language model development for automated speech recognition (ASR).
Charles holds a bachelor’s degree in industrial engineering from Montréal Polytechnic Engineering, an M.Sc. in computer science from McGill University and a Master of Information Data Science from the UC Berkeley School of Information.
David Steier co-instructs the data science capstone class in the MIDS program. He is also a distinguished service professor in Carnegie Mellon University’s Heinz College School of Information Systems and Management, where he teaches courses on data science for product management, managing analytics projects, data management, designing smart systems, and artificial intelligence.
Prior to joining CMU, David was managing director in Deloitte Consulting’s data science practice. At Deloitte, David helped clients use advanced data analytics and visualization in a variety of industries including health care, banking, retail, manufacturing, telecommunications, media and the public sector. Prior to Deloitte, David was director in the Center for Advanced Research at PwC, senior director of technology and business development at Kanisa, and managing director at Scient. Beyond the general topics of data science and artificial intelligence, David’s research interests are in data-driven approaches to behavioral change, particularly in health and wellness.