Dr. Yichuan ZhangChief Executive Officer
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.
Dr. Jinli HuChief Research Scientist
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.
Dr. Hanchen XiongChief Technology Officer
Hanchen has been a machine learning researcher and engineer for over 10 years. He is fascinated with applying math and computer science to solve real-world challenges. He won several prizes at worldwide machine learning conferences and China national mathematical contests.
Hanchen leads Boltzbit's engineering team, overseeing the company's product development and a culture of tech excellence. Before co-founding Boltzbit, he was a Senior ML Engineer and Data Scientist at Twitter. Prior to that, he also worked as a key research staff on a EU-FP7 project and research engineer at Zalando. He has deep experience in ML-driven product development, Big Data tech stack and MLOps infrastructure.
Hanchen received a PhD in Computer Science at University of Innsbruck and a MSc in Machine Learning at University College London.
Dr. José Miguel Hernández-LobatoSenior Scientific Advisor
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.
Brian TylerCommercial AI Advisor
Experienced, strategic C-Suite director with record in international, early-stage, high-tech software and hardware companies, supporting teams, securing funding, developing markets and collaborative partnerships, delivering world-class products, services and networks to generate value.
Experience with state-of-the-art AI models, platforms and markets in applications across finance, genomics, speech, text, NLP, automotive and space.
Recently as Commercial Director with Myrtle.AI 2021 developing low-latency datacentre AI hardware accelerators for text, speech and recommendation models collaborating with Intel & Xilinx.
Joss PetersBackend Developer
After earning his masters degree specialising in Machine learning from Edinburgh University, Joss Peters spent 4 years as a software engineer developing large scale banking applications before joining Boltzbit. Joss loves problem solving and enjoys digging into technical details and creating robust solutions to complex problems. In his spare time he likes to play sport, socialise and play chess.