Marc Borowczak
  • Male
  • Newark, OH
  • United States
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Short Bio:
Accomplished Innovation Leader and Research Scientist skilled in polymers, rubber, composites, coatings materials characterizations. Expert in mechanical properties characterization, adhesion, durability, life prediction, quality and data analysis. In 2015, completed Data Science Specialization Track, and all modules of Executive Data Science and Genomics Data Science with distinction at Johns Hopkins University. Consult on composites, polymers, rubber compounds, plastics, and engineered products, mapping performance and value definition. Fluent French, German, and English. US citizen, born and educated in EU.

Innovation: Known as an creative problem solver, product developer, and prolific inventor, credited with more than 10 US Patents and numerous Trade Secrets. Passionately engaged in Data Analysis, Material Science, R&D, Sustainability, Value Innovation and Sustainability.

Leadership: Builds, recruits and develop highly effective teams that solve “impossible” problems.

Teaching and Mentoring: Adjunct Professor, Chemistry & Physics Departments, Kent State and Walsh Universities. Rebuilt curriculum for Goodyear Institute of Technology, a University of Akron accredited program.

Special Interests: Machine Learning, Natural Language Processing, Data Analytics, R, Bioconductor, Value Innovation, FEI, Testing and Data Analysis.
PRC Consulting, LLC
Job Title:
Founder & Chief strategist
LinkedIn Profile:
Finding a new position, Networking, Other

Marc Borowczak's Blog

Migrating an Excel Spreadsheet Directly to HDFS and Spark 2.0.1 (Part 2)

Posted on October 23, 2016 at 5:30am 0 Comments

Recently, in a previous post, we reviewed a path to leverage legacy Excel data and import CSV files thru MySQL into Spark 2.0.1. This may apply frequently in businesses where data retention did not always take the database route……


Expand Machine Learning Tools (Part2): Toree Scala and Python in Jupyter Notebook

Posted on June 9, 2016 at 10:30am 0 Comments

Data Analytics favorite Apache Spark,  is progressing as a reference standard for Big Data, and a “fast and general engine for large-scale data processing”. In our previous post, we detailed how to expand ML tools using a PySpark kernel and leverage the …


Expand Machine Learning tools: Configure Jupyter/IPython notebook for PySpark 1.6.1

Posted on May 26, 2016 at 6:43am 0 Comments

Data Analytics favorites include Apache Spark, which is becoming a reference standard for Big Data, as a “fast and general engine for large-scale data processing”. Its built-in PySpark interface can run as a Jupyter notebook, but recent posts didn’t quite allow me to do…


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