Carolyn Rose

Keynote Talk: An Analytic Lens for Neural Model Transparency

Dr. Carolyn Rosé is a Professor of Language Technologies and Human-Computer Interaction in the School of Computer Science at Carnegie Mellon University and Interim Director of the Language Technologies Institute. Her research program focuses on computational modeling of discourse to enable scientific understanding the social and pragmatic nature of conversational interaction of all forms, and using this understanding to build intelligent computational systems for improving collaborative interactions. She is best known for her work on dynamic support of collaborative learning using intelligent conversational agents in online, face-to-face, and hybrid settings, triggered through real time analysis of conversational interactions. Her research group’s highly interdisciplinary work, published in over 280 peer reviewed publications, is represented in the top venues of 5 fields: namely, Language Technologies, Learning Sciences, Cognitive Science, Educational Technology, and Human-Computer Interaction, with awards in 4 of these fields. She is a Past President and Inaugural Fellow of the International Society of the Learning Sciences, Senior member of IEEE, Founding Chair of the International Alliance to Advance Learning in the Digital Era, and Co-Editor-in-Chief of the International Journal of Computer-Supported Collaborative Learning. She also serves as a 2020-2021 AAAS Leshner Leadership Institute Fellow for Public Engagement with Science, with a focus on public engagement with Artificial Intelligence.

Antigoni Polychroniadou

Invited Talk: Efficient Privacy-Preserving Federated Learning with Reusable Secure Aggregation

Dr. Antigoni Polychroniadou is the head of the AlgoCRYPT Center of Excellence at J.P. Morgan Chase and the cryptography research lead (Vice President) at J.P. Morgan AI Research. From 2017 to 2019, she was a postdoctoral researcher in Cryptography at Cornell University and Cornell Tech. Dr. Polychroniadou received her PhD from Århus University in Denmark under Prof. Ivan

Damgård. She received several awards including the junior Simons fellowship, awarded by the Simons Foundation. Dr. Polychroniadou is working on a number of tools which enable secure computation on private data. Beginning in J.P. Morgan Markets, the inaugural tools are enabling new business methods to leverage data while proving that privacy of the data is maintained.

Julia Stoyanovich

Invited Talk: Nutritional Labels for Automated Decision Systems: Strengthening Accountability Through Public Disclosure

Dr. Julia Stoyanovich is Institute Associate Professor of Computer Science and Engineering, Associate Professor of Data Science, and Director of the Center for Responsible AI at New York University. Her goal is to make “Responsible AI” synonymous with “AI”. She works towards this goal by engaging in academic research, education and technology regulation, and by speaking about the benefits and harms of AI to practitioners and members of the public. Julia’s research interests include AI ethics and legal compliance, data management and AI systems, and computational social choice. She has co-authored over 100 academic publications, and has written for the New York Times, the Wall Street Journal, and Le Monde. Julia has been teaching courses on responsible data science and AI to students, practitioners and the general public. She is a co-author of the “Data, Responsibly” and “We are AI” comic book series. She received her M.S. and Ph.D. degrees in Computer Science from Columbia University, and a B.S. in Computer Science and in Mathematics & Statistics from UMass Amherst. Julia’s work has been generously supported by the US National Science Foundation, Pivotal Ventures, JP Morgan Chase, and Meta Responsible AI, among others.