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Mike Dereviankin

Mike Dereviankin


Mike Dereviankin brings a solid foundation in forensic geochemistry and comprehensive experience in data validation to the Chemistry Matters team. Mike Dereviankin has a BSc in Biological & Pharmaceutical Chemistry from the University of Guelph and is a candidate for a MSc in Analytical Biochemistry from McMaster University. As an auditor for Labstat International, Mike gained familiarity with ASTM analytical protocols, data validation and ensuring compliance to ISO 17025 and GLP/GMP regulations. He is experienced in univariate and multivariant statistical analysis gained from graduate work developing comprehensive two-dimensional gas chromatography methods to monitor oil sands tailing ponds.
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Importance of Data Normalization in Complex Environmental Data Sets

Prior to making any statistical interference, the distribution of the metal and TSS data is required to be assessed if outlier concentrations are present due to variability in the measurement or experimental error. This pre-processing procedure is referred to as:

Data Normalization

The goal of normalization is to...

t-SNE is so last week, all the cool kids are using UMAP now!

Importance of staying on top of trends as a subject matter expert.

I wrote an article discussing the applications of t-distributed stochastic neighbor embedding (t-SNE) as an improved technique for dimensionality reduction and cluster association comparable to the overused Principal Component Analysis (PCA). Although...

What does the Human Genome, every image on Google and your chemical data set all have in common?

High-dimensional data reduction using Machine Learning can help find the commonalities hidden in big data.

The ability to collect data is constantly exponentially evolving and there has a been a surge in exploring the world of ‘Big Data Analytics’ in environmental forensics. This coupled with the high-throughput and...


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