About

Jessica Yung is an AI Resident at Google Brain in Zurich, where she focuses on research in transfer learning and representation learning. She is currently working on BigTransfer, a big model trained on a big dataset that is cheap to transfer from and only requires a few examples per new class to do reasonably well on a new dataset. As of today, it is state-of-the-art on standard computer vision benchmarks like ImageNet, CIFAR-10, CIFAR-100, and the low-data transfer learning benchmark VTAB. Jessica has also worked as a Venture Scout at Backed VC, a community-driven seed stage VC fund based in London, where she helped source great founders and talent, diversified the landscape of venture, and learned and grew together toward individual ambitions while supporting each other in surviving the journey. She has also worked as an AI Engineering Consultant at Wintermute Systems, where she researched augmenting models with external memory, contributed to the open-source implementation of Relational RNNs, and researched methods for time series prediction and unsupervised learning. Jessica holds a Research Masters in Computational Statistics and Machine Learning from UCL, a Bachelor of Arts in Engineering, Economics, and Mathematics from the University of Cambridge, and has completed a Self-Driving Car Engineer Nanodegree and a Machine Learning Engineer Nanodegree from Udacity. She also has a background in Mathematics, Physics, and Economics from Westminster School and Mathematics, Physics, English Language and Literature, Chinese, and Liberal Studies from Diocesan Girls' School. Jessica's tech stack includes AI, Computer Vision, Research Scientist, AWS, Python, ML, and Pytorch. With 4.71 years of relevant experience, Jessica is a highly skilled and knowledgeable professional in the field of artificial intelligence and machine learning.