Our quickly growing team of scientists, engineers and innovators are the pioneers of future AI. Distributed around the world, we’re transforming cutting-edge deep learing research into impactful AI soltions in computer vision, natural language processing and self-learning AI. Together, we’re building a great company.
London, UK
Dr. Yichuan Zhang has been passionate about AI since the beginning of his research career in 2010. As a PhD student at University of Edinburgh, he had published several papers on Boltzmann machines and approximate inference at top AI conference “NeurIPS”. His research contributes to the core of Boltzbit AI.
Prior to found Boltzbit, Dr. Zhang was a postdoctoral researcher at the University of Cambridge. Before that, he worked as software engineer at Google and a research scientist at Zalando DE.
He has been invited to speak at industrial AI conferences in UK, Germany and China. He was also the winner of 2nd place of Trinity Bradfield Prize for entrepreneurs at Cambridge in 2019.
London, UK
Dr. Yichuan Zhang has been passionate about AI since the beginning of his research career in 2010. As a PhD student at University of Edinburgh, he had published several papers on Boltzmann machines and approximate inference at top AI conference “NeurIPS”. His research contributes to the core of Boltzbit AI.
Prior to found Boltzbit, Dr. Zhang was a postdoctoral researcher at the University of Cambridge. Before that, he worked as software engineer at Google and a research scientist at Zalando DE.
He has been invited to speak at industrial AI conferences in UK, Germany and China. He was also the winner of 2nd place of Trinity Bradfield Prize for entrepreneurs at Cambridge in 2019.
London, UK
Dr. Jinli Hu started his machine learning research journey in 2011, with a background in Theoretical Physics. During his PhD at The University of Edinburgh, Jinli's research focuses on training and applying energy-based models. His work has been published at top conferences including “ICML” and “ECML”.
From 2017 to 2020, Jinli worked at Gambit Research, London's top sports-betting company, as a senior quantitative researcher and data scientist. He led development of Gambit’s first deep learning based betting systems.
Jinli’s expertise in both machine learning and physics contributes to Boltzbit’s core AI technology. Our research team led by Jinli backs the success of our products and solutions.
Cambridge, UK
Dr. José Miguel Hernández-Lobato is a well-established AI researcher in the world. He is a University Lecturer (equivalent to US Assistant Professor) in Machine Learning at the Department of Engineering in the University of Cambridge, UK.
Dr. Hernández-Lobato's research interests are in Bayesian deep learning, deep generative models, Bayesian optimization, approximate inference, and other areas. He has co-authored more than 50 papers in top conferences and journals in machine learning: JMLR, ICML, NeurIPS, AIStats and ICLR.
Dr. Hernández-Lobato organised the NeurIPS Workshop on Machine Learning for Molecules and Materials in 2017, 2018 and 2020, the NeurIPS Workshop on Bayesian Deep Learning in 2017, 2018 and 2019, the NeurIPS Workshop on Bayesian Optimization in 2017 and the machine learning summer school in Madrid in 2018.
