Our Team

reask brings a broad range of expertise from the fields of numerical modelling, data science, high-performance computing and insurance

Thomas Loridan Risk Modelling Solutions

Thomas Loridan

Contact Thomas for guidance and advice on our range of catastrophe risk products and services

Thomas leads the development of our global risk models, with a slight obsession for all things machine learning. Having built several tropical cyclone risk models for the cat modelling industry, Thomas has a strong understanding of the strength and limitations of current model solutions. His job at reask is to make sure we get rid of these limitations.

Nick Hassam Insurance Risk and Partnerships

Nick Hassam

Contact Nick to discuss operational arrangements, commercial partnerships and implementing our solutions in your business

Nick is an expert in the application of technology to the global re/insurance industry to better understand the impact of natural catastrophes, and has over 20 years’ professional experience. In close collaboration with our team, partners and clients, Nick is helping define the future of catastrophe modelling.

Nic Hannah

Nic Hannah

Contact Nic for learning more about our technology platform

High-performance computing lies at the heart of our proposition. As Chief Technology Officer and founder of reask natural hazard repository HazDat, Nic brings a wealth of expertise in the use of distributed and super-computing capability from his experience in environmental modelling as a software engineer and scientific programmer.

Eugene Dubossarsky AI and Innovation

Eugene Dubossarsky

Contact Eugene to understand how data science can better service your organisation

When it comes to leveraging the latest advances in machine learning, we understand there is no faking it. That’s why we turned to the best for advice and mentoring. Eugene has over 20 years of experience playing with neural nets and the likes, and we are proud to have him as reask’s in house AI guru.

Nico Bruneau

Nico Bruneau

Contact Nico for deep understanding of the underlying components of our models

Our models are only as good as the data they are built on. Nico’s job is to ensure we make best use of the constant increase in both quality and availability of global earth system data. Beyond management of the raw data Nico’s key contribution is the development of our automated knowledge discovery engine, using state-of-the-art methods from the field of image processing and pattern recognition.

Close Menu