Christopher Tegho

Christopher Tegho is a highly skilled professional currently working as a Machine Learning Engineer at Calipsa in London. His expertise lies in computer vision, machine learning, Bayesian neural networks, reinforcement learning, meta reinforcement learning, variational inference, and video analytics.

With a strong academic background, Christopher completed his MPhil in Machine Learning at the University of Cambridge, where he focused on enhancing uncertainty estimates in deep reinforcement learning using Bayes By Backprop for dialogue systems. He also holds a Bachelor's degree in Electrical Engineering from McGill University.

Christopher's professional journey includes roles such as a Cloud Developer & Consultant at GURUS Solutions, a Software Developer at GERAD - Groupe d'études et de recherche en analyse des décisions, and a Back-end Developer at McGill University. His diverse experience spans across machine learning, software engineering, and cloud development.

His notable achievements include developing a few shot detector for identifying tear gas canisters to support investigations on human rights violations at Forensic Architecture. Additionally, he has worked on projects involving image and video generation, language modeling for art installations, and research on support vector graphic generation.

Christopher's strengths lie in effectively applying machine learning solutions to real-world problems, regardless of the scale of data available. He excels in working with both 'small' and 'big' data, showcasing his versatility and adaptability in handling varied challenges.

His interests and skills cover a broad spectrum of topics within the realm of technology, including video recognition, few shot learning, object and movement detection. Christopher Tegho's passion for innovation and problem-solving is evident in his contributions to diverse projects and organizations throughout his career.