AI and Society Community Mixer
Wednesday, April 16 | 5:30 – 7:00 p.m. (PT) | Soda Hall 510
We will aim to begin the talks by Gireeja Ranade (Assistant Teaching Professor of EECS) and Zachary A. Pardos (Associate Professor of Education) around 6pm with socializing before and after. There will be food and drinks.
Dr. Pardos is an Associate Professor of Education at UC Berkeley studying adaptive learning and AI. His current research focuses on knowledge representation and recommender systems approaches to increasing upward mobility in postsecondary education using behavioral and semantic data. He earned his PhD in Computer Science at Worcester Polytechnic Institute with a dissertation on computational models of cognitive mastery. Funded by a National Science Foundation Fellowship (GK-12), he spent extensive time with K-12 educators and students working to integrate educational technology into the curriculum as a formative assessment tool. After completing his PhD in 2012, he spent one year as a Postdoctoral Associate at the Massachusetts Institute of Technology. At Cal, he directs the Computational Approaches to Human Learning research lab, teaches in the data science undergraduate program, and is an affiliated faculty in Cognitive Science.
Prof. Ranade was a Researcher at Microsoft Research AI in the Adaptive Systems and Interaction Group before joining the faculty at UC Berkeley. She also designed and taught the first offering for the new course sequence EECS16A and EECS16B in the EECS department at UC Berkeley and received the 2017 UC Berkeley Electrical Engineering Award for Outstanding Teaching. She was also awarded the 2020 UC Berkeley award for Extraordinary Teaching in Extraordinary Times. Prof. Ranade received her PhD in Electrical Engineering and Computer Science from the University of California, Berkeley, and her undergraduate degree from MIT in Cambridge, MA.
If you require an accommodation for effective communication (ASL interpreting/CART captioning, alternative media formats, etc.) to fully participate in an event, please contact Justin Do at jtrido@berkeley.edu with as much advance notice as possible and at least 7 business days in advance of the event.