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Dr. Diane Litman and collaborators from the LRDC win Future Forums on Learning's Learning Engineering Tools Competition
The Future Forums on Learning awarded Dr. Diane Litman and collaborators from the Learning Research and Development Center, Lindsay Clare Matsumura and Richard Correnti, a Catalyst Prize as part of their 2021-2022 Learning Tools Competition.
Dr. Xulong Tang (Assistant Professor, Computer Science) received a new three-year grant from the National Science Foundation.
Cameras are popping up throughout the 5th and 6th floors of Sennott Square to investigate how public spaces are used as part of a new research project from Department of Computer Science students and faculty.
Ms. Victoria Chuah graduated with a BS+MS degree in Computer Science in May 2022 and was crowned Miss Virginia in June 2022. Read the interview to find out about her experience at Pitt and her plans for the future.
The CS 50 Fellowship was created in 2021 to celebrate the Department’s 50th Anniversary. In 2022, the competition had two winners, Meiqi Guo and Bingyao Li.
Pranut Jain received an honorable mention award at Designing Interactive Systems (DIS) 2022 for his paper Laila is in a Meeting: Design and Evaluation of a Contextual Auto-Response Messaging Agent.
Combining the decision power or AI with the ability of the user to guide and control it brings together the strong sides of artificial and human intelligence and could lead to better results. In this talk, I will review the work of our team and the broader research community focused on adding various kinds of user control to adaptive information access systems and discuss lessons learned, prospects, and challenges of this direction of research.
I present three of our recent works: 1) Discourse-aware generation models for automatic social media moderation and mediation, 2) Sign language processing, and 3) Equitable and human-like dialogue generation models based on learning theory. Finally, I describe my research vision: Building inclusive and collaborative communicative systems and grounded artificial intelligence models by leveraging the cognitive science of language use alongside formal methods of machine learning.
While current research has mostly focused on reducing the energy footprint, in this talk, we will discuss how improving energy efficiency does not translate to the goal of zero emissions. More importantly, carbon efficiency can be optimized independently of energy efficiency. Toward this end, I will present some examples of mitigating emissions and some directions toward designing carbon-efficient infrastructures.