Speakers

Y-Lan Boureau , Facebook Artificial Intelligence Research

Y-Lan Boureau is a research scientist at Facebook Artificial Intelligence Research. She received her PhD from New York University and École Normale Supérieure (within the INRIA Willow project team), working in machine learning and computer vision. Before joining Facebook AI Research, she did postdoctoral research in experimental psychology and neuroscience at New York University, investigating self-control and meta decision making. She was one of the 2014 junior fellows of the Simons Society of Fellows. At FAIR, her work has focused on building more helpful conversations and understanding dialogue.

Hal Daumé III , University of Maryland, College Park | Microsoft Research

Hal Daumé III is a professor in Computer Science at the University of Maryland, College Park and Principal Researcher at Microsoft Research, New York City. His primary research interest is in developing new learning algorithms for prototypical problems that arise in the context of natural language processing, with a focus on interactive systems and fairness. He has received several ``best of' awards, including at ACL 2018, NAACL 2016, NeurIPS 2015 (demo), CEAS 2011 and ECML 2009. He has been program chair for NAACL 2013 (and chair of its executive board), is program co-chair for ICML 2020, and was an inaugural diversity and inclusion co-chair at NeurIPS 2018.

Julia Hirschberg , Columbia University

Julia Hirschberg is Percy K. and Vida L. W. Hudson Professor of Computer Science at Columbia University. She was department chair from 2012-2018. She previously worked at Bell Laboratories and AT&T Labs where she created the HCI Research Department. She served on the Association for Computational Linguistics executive board (1993-2003), the International Speech Communication Association board (1999-2007; 2005-7 as president), the International Conference on Spoken Language Processing board (1996--), the NAACL executive board (2012-15), the CRA Executive Board (2013-14), the AAAI Council (2012-15), and the IEEE SLTC 2015--. She has been editor of Computational Linguistics and Speech Communication, is a fellow of AAAI, ISCA, ACL, ACM, and IEEE, and a member of the National Academy of Engineering, the American Academy of Arts and Sciences, and the American Philosophical Society. She received the IEEE James L. Flanagan Speech and Audio Processing Award and the ISCA Medal for Scientific Achievement in 2011. She is co-chair of the CRA-W Board, and has worked for diversity for many years at AT&T and Columbia. She works on spoken language processing and NLP, studying text-to-speech synthesis, spoken dialogue systems, entrainment in conversation, detection of deceptive and emotional speech, hedging behavior, and linguistic code-switching (language mixing).

Varoon Mathur , AI Now Institute

Varoon Mathur is a researcher and data scientists, conducting interdisciplinary research on the social implications of machine learning and related technologies on public domains. He currently serves as a Technology Fellow at the AI Now Institute in New York.
Previously, Varoon served as one of Microsoft's Data Science for Social Good Fellows, and earned his software engineering degree from UBC with a focus in machine learning. He is also a global health activist, and is a Co-ordinating Committee Fellow with Universities Allied for Essential Medicines, a student-driven NGO focused on access to medicines issues for vulnerable and marginalized population. He has advised on global health policy and research at the World Health Organization, and is a former TEDx Speaker.

Alfredo Canziani , New York University

Alfredo Canziani is a Post-Doctoral Deep Learning Research Scientist and Lecturer at NYU Courant Institute of Mathematical Sciences, under the supervision of professors KyungHyun Cho and Yann LeCun. His research mainly focusses on Machine Learning for Autonomous Driving. He has been exploring deep policy networks actions uncertainty estimation and failure detection, and long term planning based on latent forward models, which nicely deal with the stochasticity and multimodality of the surrounding environment. Alfredo obtained both his Bachelor (2009) and Master (2011) degrees in Electrical Engineering cum laude at Trieste University, his MSc (2012) at Cranfield University, and his PhD (2017) at Purdue University. In his spare time, Alfredo is a professional musician, dancer, and cook, and keeps expanding his free online video course on Deep Learning and PyTorch.

Brian McFee , New York University

Brian McFee is Assistant Professor of Music Tech-nology and Data Science New York University. He received the B.S. degree (2003) in Computer Science from the University of California, Santa Cruz, and M.S. (2008) and Ph.D. (2012) degrees in Computer Science and Engineering from the University of California, San Diego. His work lies at the intersection of machine learning and audio analysis. He is an active open source software developer, and the principal maintainer of the librosa package for audio analysis.

Arthur Spirling , New York University

Arthur Spirling is Professor of Politics and Data Science at New York University. He received a bachelor's and master's degree from the London School of Economics, and a master's degree and PhD from the University of Rochester. Spirling's research centers on quantitative methods for social science, especially those that use text as data and more recently, deep learning and embedding representations. His work on these subjects has appeared in outlets such as the American Political Science Review, the American Journal of Political Science, the Journal of the American Statistical Association and conference proceedings in computer science. His work have been supported by the National Science Foundation. Substantively, he is interested in the political development of institutions, especially for the United Kingdom.

Joel Tetreault , Dataminr

Joel Tetreault is Director of Research at Dataminr, a company that provides updates on breaking events across the world in near real-time. His background is in AI, specifically Natural Language Processing and Machine Learning, and using techniques from those fields to solve real-world problems such as automatic essay scoring, grammatical error correction, hate speech detection, ranking user comments and dialogue systems, among others. Prior to joining Dataminr, he led research groups at Grammarly, Nuance and Educational Testing Service, and was a Senior Research Scientist at Yahoo Labs. Joel recently finished a six-year stint as NAACL Treasurer and was a long-time organizer of the Building Educational Application workshop series. He is a program chair for ACL 2020.