Valery Manokhin🇬🇧

About Valery Manokhin

Head of Data Science at UCL

Valeriy Manokhin, PhD, MBA, CQF Forecasting | Machine Learning | Data Science | Conformal Prediction

I’m a machine learning and data science practitioner specializing in data science, forecasting, uncertainty quantification, and applied conformal prediction. I completed my PhD in Conformal Prediction under Professor Vladimir Vovk, the creator of conformal prediction itself. My academic work has been published in top ML journals, including JMLR, Neurocomputing, and the Journal of Machine Learning Research.

I teach two hands-on courses on Maven — Modern Forecasting Mastery and Applied Conformal Prediction — where I help practitioners build uncertainty-aware ML systems that work in real-world settings. I’m also the author of "Practical Guide to Applied Conformal Prediction in Python", focused on helping industry teams implement the most effective uncertainty frameworks in practice.

I maintain the widely used "Awesome Conformal Prediction" repository and actively contribute to advancing the practical adoption of CP methods across industries.

In mentorship, I help data scientists, ML engineers, and analysts:

Apply modern forecasting and machine learning techniques effectively Implement conformal prediction for real-world uncertainty estimation Build robust, interpretable, production-ready ML systems Connect academic rigor with practical business-driven decision-making

If you want to strengthen your forecasting, ML, or uncertainty modeling skills — or need guidance implementing conformal prediction in your workflows — I’m here to support you.

Expertise

Sessions with Valery Manokhin

• Mentorship Session (30 min): Mentorship session