Dr. Olga Russakovsky is an Assistant Professor of Computer Science at Princeton University where she is also affiliated with the Center for Statistics and Machine Learning and the Center for Information Technology Policy. She completed her PhD in Computer Science at Stanford University in August 2015 and her postdoctoral fellowship at the Robotics Institute of Carnegie Mellon University in June 2017. Her research is in computer vision, closely integrated with machine learning, human-computer interaction and fairness, accountability and transparency.
Her research focuses on three primary areas of exploration. The first is developing the fundamental building blocks of visual recognition, such as object detection, image parsing or human activity understanding. The second direction is designing human-machine interaction paradigms which enable computer vision systems to effectively learn from and collaborate with humans. The third and newest research direction is ensuring the fairness of the vision systems with respect to people of all backgrounds by improving dataset design, algorithmic methodology and model interpretability. One of her most notable contributions to date is leading the ImageNet Large Scale Visual Recognition Challenge. This research appeared in the International Journal of Computer Vision in December 2015 and amassed more than 16,000 citations as of June 2020. Her team was awarded the prestigious PAMI Everingham Prize, and the work was featured in the New York Times and MIT Technology Review.
In addition to her research, she has spearheaded a number of diversity and outreach initiatives. Most notably, she co-founded and serves on the Board of Directors of the AI4ALL nonprofit dedicated to educating diverse future Artificial Intelligence (AI) leaders. She was the co-founder and co-director of the Stanford AI4ALL summer camp for high school girls, and is the co-founder and co-director of the Princeton AI4ALL summer camp teaching AI technology and policy to diverse high school students. AI4ALL has partnered with 16 universities so far to introduce students from underrepresented groups to AI, and launched a free, project-based online AI education program Open Learning.
She has been awarded numerous honors for her research and outreach work, including the CRA-WP Anita Borg Early Career Award in 2020, the AnitaB.org’s Emerging Leader Abie Award in Honor of Denice Denton in 2020, the PAMI Everingham Prize in 2016, the MIT EECS Rising Star award in 2013, and the NSF graduate fellowship in 2007. She was named one of MIT Technology Review’s 35 Innovators Under 35 in 2017, Foreign Policy Magazine’s 100 Leading Global Thinkers in 2015 and Becominghuman.ai’s 100 Brilliant Women in AI Ethics in 2019. Within the computer vision community, she served as a Senior Program Committee member for WACV’16, CVPR’18, CVPR’19, NeurIPS’19, and CVPR’20, was the Publicity and Press chair at CVPR’16, the Doctoral Consortium Chair for CVPR’19 and will be the Workshop Chair for ICCV’21. She has organized multiple workshops and tutorials on large-scale recognition, and has given more than 50 invited talks at universities, companies, workshops and conferences.