Christopher Bonnett Ph.D

Dr. Christopher Bonnett is a highly accomplished Machine Learning Engineer with a Ph.D. in Astronomy and Astrophysics. With a stellar academic background, including studying for a Ph.D. with Cum Laude distinction in Astronomy and Astrophysics at Université Pierre et Marie Curie, Paris VI, and a B.A., M.S. in Astronomy from Leiden University, Dr. Bonnett has a strong foundation in scientific research.

Dr. Bonnett has made significant contributions in various roles, including as a Senior Machine Learning Researcher at Alpha-I, where his work focused on Bayesian Deep Learning for dynamical systems. He also served as a Fellow at Insight Data Science, NYC, developing advanced classification and object recognition pipelines using machine learning techniques such as Convolutional Neural Networks (CNNs), Deep Learning, and Natural Language Processing (NLP). His achievements include attaining 94% accuracy through transfer learning and fine-tuning with Neural Networks for e-commerce product recognition.

Prior to his industry roles, Dr. Bonnett held prestigious post-doctoral positions. At the Institute for High Energy Physics in Barcelona, he played a key role in producing and validating galaxy distance measurements using Neural Networks and Bayesian modeling for millions of galaxies in the Dark Energy Survey. His contributions to the understanding of the accelerated expansion of the universe were noteworthy, and he led a key science group within the project. Dr. Bonnett was also involved in the translation of the book 'First contact with TensorFlow' from Spanish to English as part of his scientific endeavors.

During his Marie Curie Post-doc at the Institute for Space Sciences in Barcelona, Dr. Bonnett excelled in conducting systematic tests on galaxy shapes, introducing novel approaches using Neural Networks for estimating galaxy distance distributions. His innovative methods led to him winning the prestigious Euclid galaxy distance data challenge. Additionally, he organized and led international workshops on cosmology, showcasing his leadership and collaborative skills.

Currently, Dr. Bonnett serves as a Machine Learning Engineer at Zoe, bringing his expertise in machine learning, deep learning, and data science to his role. With a rich background in academia and research, coupled with his practical experience in industry, Dr. Christopher Bonnett is a seasoned professional with a passion for leveraging cutting-edge technologies to solve complex problems in the fields of astronomy, cosmology, and machine learning.