Molecular characterization takes time

Companies cannot waste valuable time on expensive techniques to determine properties of molecules.

We are using artificial intelligence to predict the activity of molecules such as pesticides. Our proprietary algorithms can sift through terabytes of data to pinpoint specific structures and properties that give rise to optimal properties.

Meet the team

Scott Hopkins

Co-Founder & CEO

Scott Hopkins is an Associate Professor of Chemistry at the University of Waterloo. His expertise in is experimental, computational, and theoretical physical chemistry, including machine learning techniques. Dr. Hopkins has received numerous awards for his research, including the Ramsay Memorial Fellowship (held at Oxford University), and the Early Researcher Award from the Province of Ontario. Dr. Hopkins has published more than 50 peer-reviewed articles in top-tier journals, including 9 cover articles, and he has been granted 3 patents.

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Larry Campbell, Ph.D.


Larry Campbell, Ph.D. has been using mass spectrometry and other analytical instrumentation to solve complex and downright bizarre molecular puzzles for over 25 years. Many of these stories have been published in more than 65 peer-reviewed articles in scientific journals and in over 20 patents. Larry's continuing desire to help other scientists solve similar molecular puzzles brought him to join the Watermine team as Chief Technology Officer (CTO).

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Jeff Crouse

VP, Research and Development
PhD, Queens - PDF, Waterloo

Jeff is an expert is in computational and theoretical physical chemistry, with a focus on machine learning. His PhD work focused on processing and interpreting large data arrays from molecular dynamics simulations.

Josh Featherstone

Data Scientist
PhD, Waterloo & PDF, Oxford

Josh has expertise in computational and theoretical physical chemistry. Josh has a passion for designing pythonic solutions to computational problems that arise in the analysis of data.

Our Mission

We are a technology company that aims to use artificial intelligence to predict characteristics of molecules.

Differential Mobility Spectroscopy

Differential mobility spectrometry (DMS) is a relatively new technique in ion chromatography, which enables the separation and characterization of compounds in complex mixtures. For example, we can use DMS to quickly determine the properties of pesticides, and we can separate and quantify species of interest in environmental contamination. Our methodology requires very little sample and it is much faster and environmentally friendly than traditional liquid chromatography-based methods.

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