The purpose of this event is to unite women in AI and to foster, encourage and support greater diversity in the field of AI in the Latin American community, while highlighting diverse career paths: from academia, to industrial research, to applied machine learning. Our eminent panellists will each discuss their personal career journey and their experiences in machine learning. Participants will also have the opportunity for Q&A with the panelists as well as a chance to network. At the end of the event we will enjoy a dinner and a show of one of the most famous Uruguayan rock bands.
All participants must appear on the guest list and be registered to attend the event. Participation is non-transferable.
Get to know our panelists:
Paula Martínez
Paula Martínez cofounded Marvik, a machine learning consulting and development company that specializes in Computer Vision, Predictive Analytics and Natural Language Processing. Paula is an Electrical Engineer and holds a Master in technological business management. She was selected as a Google Developer Expert in machine learning and co-organizes machine learning meetups. She has also completed programs at MIT and Berkeley among others.
Aiala Rosá
Aiala Rosá is a full time Associate Professor at the Instituto de Computación – Facultad de Ingeniería – UdelaR, she is currently the head of the NLP research group. Her main research lines include subjectivity analysis in social media, question & answering, and applications of language technologies for language teaching. She holds a Ph.D. in Computer Sciences from PEDECIBA – UdelaR (Uruguay) and Université Paris-Ouest Nanterre La Défense (France), and a B.Sc. in Computer Engineering from Facultad de Ingeniería, UdelaR.
Magdalena Fuentes
Magdalena Fuentes is Assistant Professor at New York University. She works in machine listening, a field of study that combines signal processing and machine learning for machines to make sense of natural and everyday sounds, and music. She is interested in methods at the intersection of sound, vision and natural language, which can be easily adapted to different users and contexts. Magdalena holds a Ph.D. from Université Paris Saclay in France, and a B.Eng. in Electrical Engineering at Universidad de la República, Uruguay.
Sara Hooker
Sara is a Director at Cohere and she leads Cohere For AI, a non-profit research lab that seeks to solve complex machine learning problems while being focused on creating more points of entry into machine learning research. She is one of the co-founders of the Trustworthy ML Initiative, a forum and seminar series related to Trustworthy Machine Learning. She is also on the advisory board of Patterns and on Kaggle’s ML Advisory Research Board.