Learning Brain Dynamics With Coupled Low-Dimensional Nonlinear Oscillators and Deep Recurrent Networks
- Germán Abrevaya
- Guillaume Dumas
- et al.
- Neural Computation
David Cox is the VP for AI models at IBM Research, responsible for the development and training of IBM's large language models. He is also the IBM Director of the MIT-IBM Watson AI Lab, a first of its kind industry-academic collaboration between IBM and MIT, focused on fundamental research in artificial intelligence. The Lab was founded with a $240m, 10 year commitment from IBM and brings together researchers at IBM with faculty at MIT to tackle hard problems at the vanguard of AI.
Prior to joining IBM, Cox was the John L. Loeb Associate Professor of the Natural Sciences and of Engineering and Applied Sciences at Harvard University, where he held appointments in Computer Science, the Department of Molecular and Cellular Biology and the Center for Brain Science. Cox has been a speaker and agenda contributor at the World Economic Forum, and he was a Faculty Associate at the Berkman-Klein Center for Internet and Society at Harvard Law School. He has received a variety of honors, including the Richard and Susan Smith Foundation Award for Excellence in Biomedical Research, the Google Faculty Research Award in Computer Science, and the Roslyn Abramson Award for Excellence in Undergraduate Teaching. He has published over 100 peer-reviewed academic articles in the fields of neuroscience and AI.
His lab at Harvard started several widely-used open source projects, including Hyperopt, one of the first frameworks for hyperparameter optimization of AI models, and Triton (now OpenAI Triton) a framework for accelerated compute on GPUs. While at Harvard, he also co-founded several AI startups, including DeepHealth (acquired by RadNet, Inc.) which developed multiple FDA-cleared AI-based medical imaging solutions which have been deployed at scale.
Cox earned an undergraduate degree at Harvard University and a Ph.D. at the Massachusetts Institute of Technology.