[Short] [Long] [Audio] [Video]



Short (100 words)

Rosanne Liu is the Co-founder and Executive Director of ML Collective, a non-profit organization providing research training for all, and is concurrently doing science and being a manager at Google DeepMind (previously Brain). She was a founding member of Uber AI. Rosanne obtained her PhD in Computer Science at Northwestern University, and has published well-cited research at NeurIPS, ICLR, ICML, Nature and other top venues. She builds communities for researchers around the world, organizes symposiums, workshops, and a long-running weekly reading group “Deep Learning: Classics and Trends.” She serves as the Diversity, Equity & Inclusion chair of ICLR 2022-2024, and NeurIPS 2023.



Long (200 words)

Rosanne Liu is the Co-founder and Executive Director of ML Collective, a non-profit organization providing research training for all, through open collaboration and accessible mentorship; and she is concurrently doing science and being a manager at Google DeepMind. Before that she was one of the 15 founding members (and the only woman) of Uber AI Labs. She has published research at NeurIPS, ICLR, ICML, Nature and other top venues, and her work has been covered by WIRED, MIT Tech Review, and Fortune. She obtained her PhD in Computer Science at Northwestern University; while at school she used neural networks to help discover novel materials, and to optimize fuel efficiency in hybrid vehicles. She builds and supports communities for underrepresented and unprivileged researchers, organizes symposiums, workshops, and a long-running weekly reading group “Deep Learning: Classics and Trends.” She serves as the Diversity, Equity & Inclusion chair of ICLR 2022-2024, and NeurIPS 2023. She is currently thinking deeply about how to democratize AI research even further, and improve the diversity and fairness of the field, while working on multiple fronts of machine learning research including understanding training dynamics, rethinking model capacity and scaling. Through all these efforts she wants to make neural networks a better place—both to understand the science better, and to make it a more fulfilling field to work in.



Audio

If you prefer to know me through a few rambly audio conversations, I was on these podcasts:

Video

I gave a talk on my personal path into co-founding and leading MLC that went kinda viral (10k views in 3 days; 20k views in 6 months):