The RAI Rockstar series aims to improve the representation of women and members of historically under-represented groups in AI careers. We do this by bringing role models who work on RAI topics and contribute to the diversity of voices in this area of research, education, and practice. Our first RAI Rockstar, Dr. Sihem Amer-Yahia, will visit NYU R/AI in November 2022. She will give talks and participate in a fireside chat with NYU students.

Sihem Amer-Yahia is a Silver Medal CNRS Research Director and Deputy Director of the Lab of Informatics of Grenoble. She works on exploratory data analysis and fairness in job marketplaces. Before joining CNRS, she was Principal Scientist at QCRI, Senior Scientist at Yahoo! Research and Member of Technical Staff at AT&T Labs. Sihem is PC chair for SIGMOD 2023 and vice president of the VLDB Endowment. She currently leads the Diversity, Equity and Inclusion initiative for the database community.


All events are open to the broader NYU community.

Talk: Towards AI-Powered Data-Informed Educational Platforms

The Covid-19 health crisis has seen an increase in the use of digital work platforms, from videoconferencing systems to MOOC-type educational platforms and crowdsourcing and freelancing marketplaces. These levers for sharing knowledge and learning constitute the premises of the future of work. Educational technologies coupled with AI hold the promise of helping learners and teachers. However, they are still limited in terms of social interactions, user experience, and learning opportunities as they must address a tension between learner-centered and platform-centered approaches. I will describe research at the intersection of data-informed recommendations and education theory and conclude with ethical considerations in building educational platforms. The talk will be followed by a reception with the CDS Women in Data Science group

Date & Time: November 8th, 2022 (Tue), 2-4 pm
Venue: NYU Center for Data Science, 60 5th Avenue, 7th Floor open space, New York, NY 10011

Talk: Commodifying Data Exploration

Exploratory Data Analysis (EDA) is an iterative and tedious process. Several strategies have been proposed to ease the burden on users in EDA, ranging from stepwise to full-guidance approaches. Stepwise approaches rely on computing utility functions that determine the best action to take at each step. Full-guidance approaches rely on learning end-to-end exploration policies. Today’s big question is how to commodify EDA and make it easily deployable for all but for that, we need to know what users are looking for: are they looking for a needle in a haystack, taking a tour of the data, or are they feeling lucky? This talk will investigate those questions and discuss the challenges of storing learned pathways through data or regenerating them when needed.

Date & Time: November 9th, 2022 (Wed) 1-2 pm
Venue: NYU Tandon School of Engineering, 370 Jay Street, Room #1201, Brooklyn, NY, 11201

Fireside Chat with Dr. Sihem Amer-Yahia

Join us in a fireside chat with Dr. Sihem Amer-Yahia, hosted by Dr. Julia Stoyanovich, Associate Professor of Computer Science & Engineering and of Data Science and Director of the Center for Responsible AI at NYU. Dr. Sihem will share with you her experience as a woman, a scientist, an engineer, an African, an American, and a French. She will discuss her research experience in industry and academia, in five countries across four continents, and will exchange ideas and opinions with you about how universal research environments can be and what it means to be a woman in the world of computer science and data science research.

This event will consist of a 30-minute dialogue between Sihem and Julia, followed by questions from the audience and an informal discussion. Refreshments will be served.

Date & Time: November 14th, 2022 (Mon), 12:30-2 pm
Venue: NYU Tandon School of Engineering, 370 Jay Street, Room #1201, Brooklyn, NY, 11201