Short (100 words)

Rosanne Liu is a research scientist at Google Brain, and co-founder and executive director of ML Collective, a non-profit organization providing research training for all. She was also a founding member of Uber AI. She obtained her PhD in Computer Science at Northwestern University, published research at NeurIPS, ICLR, ICML, Science and other top venues, and had her work featured by WIRED, MIT Tech Review and Fortune. She builds communities for underrepresented and unprivileged researchers, organizes symposiums, workshops, and a weekly reading group “Deep Learning: Classics and Trends” since 2018. She serves as the Diversity, Equity & Inclusion chair of ICLR 2022 and 2023.



Long (200 words)

Rosanne Liu is a research scientist at Google Brain, and co-founder and executive director of ML Collective, a non-profit organization providing research training for all, through open collaboration and accessible mentorship. Before that she was a founding member of Uber AI. She has published research at NeurIPS, ICLR, ICML, Science 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 weekly reading group “Deep Learning: Classics and Trends” since 2018. She serves as the Diversity, Equity & Inclusion chair of ICLR 2022 and 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:



Visual

I also 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):