Topics
Large Language Models, Deep Learning, Natural Language ProcessingBiography
Vivek Natarajan is a Research Scientist at Google leading research at the intersection of large language models (LLMs) and biomedicine. In particular, Vivek is the lead researcher behind Med-PaLM and Med-PaLM 2, which were the first AI systems to obtain passing and expert level scores on US Medical License exam questions respectively. Med-PaLM was recently published in Nature and has been featured in The Scientific American, Wall Street Journal, The Economist, STAT News, CNBC, Forbes, New Scientist among others. More recently, Vivek also led the development of Med-PaLM M, the first demonstration of a generalist biomedical AI system.
Over the years, Vivek’s research has been published in well-regarded journals and conferences like Nature, Nature Medicine, Nature Biomedical Engineering, JMLR, CVPR, ICCV and NeurIPS. It also forms the basis for several regulated medical device products under clinical trials at Google, including the NHS AI award winning breast cancer detection system Mammo Reader and the skin condition classification system DermAssist.
Prior to Google, Vivek worked on multimodal assistant systems at Facebook AI Research and published award winning research, was granted multiple patents and deployed AI models to products at scale with hundreds of millions of users.
Topics
Mathematics of Artificial Neural Networks, Biological Neural Networks, Deep LearningBiography
Johannes Schmidt-Hieber was born in Freiburg im Breisgau, Germany, in 1984. He received the master’s degree from the University of Göttingen, Germany, in 2007, and the joint Ph.D. degree from the University of Göttingen and the University of Bern, Switzerland, in 2010.,His Ph.D. degree was followed by two one-year post-doctoral visits at Vrije Universiteit Amsterdam, The Netherlands, and ENSAE, Paris, France. From 2014 to 2018, he was an Assistant Professor at the University of Leiden. Since 2018, he has been a Full Professor at the University of Twente, The Netherlands. His research interests include mathematical statistics, including nonparametric Bayes and statistical theory for deep neural networks. He serves as an Associate Editor for the Annals of Statistics, Bernoulli, and Information and Inference.
The Prof. Schmidt-Hieber’s ERC CoG grant has been selected by the ERC as one of four highlighted projects.
