Sasha Luccioni
Alexandra Sasha Luccioni is a computer scientist specializing in the intersection of artificial intelligence and climate change. Her work focuses on quantifying the environmental impact of AI technologies and promoting sustainable practices in machine learning development.
Early life and education
Alexandra Sasha Vorobyova was born in the Ukrainian Soviet Socialist Republic in 1990. When she was four years old, her family relocated to Ontario, Canada. Her interest in science is influenced by her family's history; her mother, grandmother, and great-grandmother all pursued careers in scientific fields.Luccioni earned a B.A. in language science from University of Paris III: Sorbonne Nouvelle in 2010. Subsequently, she completed a M.S. in cognitive science, with a minor in natural language processing, at École normale supérieure in Paris in 2012. Luccioni obtained her PhD in cognitive computing from Université du Québec à Montréal in 2018.
Career
Luccioni began her professional career at Nuance Communications in 2017, where she focused on natural language processing and machine learning techniques to enhance conversational agents. She then joined Morgan Stanley’s AI/ML Center of Excellence in 2018, working on explainable artificial intelligence and decision-making systems.In 2019, she became a postdoctoral researcher at Université de Montréal and Mila, collaborating with computer scientist Yoshua Bengio on a project titled This Climate Does Not Exist. This initiative used generative adversarial networks to visualize the effects of climate change. During this time, she also contributed to integrating fairness and accountability into machine learning education at Mila.
Luccioni briefly worked with the United Nations Global Pulse in 2021, developing tools to monitor COVID-19 misinformation. Later that year, she joined Hugging Face as a research scientist. Her role includes quantifying the carbon footprint of AI systems, co-chairing the carbon working group in the Big Science project, and advancing responsible machine learning practices. She helped create "CodeCarbon," an open-source software tool that estimates the carbon emissions produced during the training and operation of machine learning models.
In addition to her research, she has developed tools to measure the environmental impact of AI models, communicated findings through media engagements, and presented at international conferences, including a TED Talk. In 2024, she was listed on BBC 100 Women and Time 100 AI.