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Chad Scherrer

from Seattle, WA
Age ~52
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Also known as:
Chad Scherre
Phone and address:
1924 E John St, Seattle, WA 98112
Related to:
Patricia R Fleck, 78Jan ScherrerFrancisco Cavazos, 49Deanna Freeman, 84Thomas G Birrell, 61Pamela L Kreider, 57Alexander BirrellJeanne M Freeman, 47Tracy Collins, 60Laurel J Collins, 67Sarah E Freeman, 52Morgan P Collins, 42Alba L Hernandez, 42Deanna K Freeman, 44Heather Scherrer, 46Heidi D Birrell, 63Ian L Stewart, 48Tracy L Lykins, 55Yvonne M CollinsRobert L Ebberts, 53
Connected to:
Betty J Scherrer, 98Jay R Scherrer, 35Jeffrey M Scherrer, 57Josh R Scherrer, 30Justin D Scherrer, 45Maura J Scherrer, 60Megan Scherrer, 36Raymond W Scherrer, 49Robert W Scherreik, 70Rose Scherrer, 81

Chad Scherrer Phones & Addresses

  • 1924 E John St, Seattle, WA 98112
  • Mercer Island, WA
  • Portland, OR
  • Yakima, WA
  • 8304 Quatsino Dr, Pasco, WA 99301 (509) 543-9791 (509) 544-6543
  • Indianapolis, IN
  • Jasper, IN
  • Terre Haute, IN
  • Bloomington, IN
  • Martinsville, IN

Work

Company: Pacific northwest national laboratory - Richland, WA 2000 Position: Research scientist

Education

School / High School: Indiana University- Bloomington, IN 1994 Specialities: PhD in Mathematics

Public records

Vehicle Records

Chad Scherrer

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Address:
3412 Gregory Ave, Yakima, WA 98902
VIN:
WBAVC535X8A246879
Make:
BMW
Model:
3 SERIES
Year:
2008

Resumes

Resumes

Chad Scherrer Photo 1

Senior Research Scientist

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Location:
1924 east John St, Seattle, WA 98112
Industry:
Higher Education
Work:
Relationalai
Senior Research Scientist
Metis Jan 2018 - Jan 2020
Senior Data Scientist
Galois, Inc. Sep 2014 - Jan 2017
Technical Lead
Melinae Feb 2014 - Aug 2014
Lead Data Scientist
Insight Results Jun 2013 - Feb 2014
Statistics Consultant
Education:
Indiana University 2003
Indiana University Bloomington 1994 - 2000
Doctorates, Doctor of Philosophy, Mathematics Rose - Hulman Institute of Technology 1990 - 1994
Bachelors, Bachelor of Science, Mathematics Jasper High School
Skills:
Algorithms
Machine Learning
Mathematical Modeling
Statistical Modeling
High Performance Computing
Computer Science
Statistics
Python
Numerical Analysis
R
Bayesian Statistics
Data Analysis
Parallel Computing
Haskell
Scientific Computing
Programming
Computational Biology
Distributed Systems
Statistical Computing
Data Mining
Latex
Research
Parallel Algorithms
Parallel Programming
Linear Algebra
C
Monte Carlo Simulation
Natural Language Processing
Science
Matlab
Dimensionality Reduction
Simulations
Linux
Teaching
Applied Mathematics
Bayesian Inference
Julia
Statistical Consulting
Openmp
Technical Writing
Bayesian Networks
Feature Selection
Stochastic Simulation
Data Science
Artificial Intelligence
Apache Spark
High Performance Computing
Ocaml
Stochastic Optimization
Stan
Interests:
Mathematics
Functional Programming
Computer Programming
Facebook
Jokes
Humor
Algorithms
Music
Survival Techniques
Programming Languages
Haskell
Startups
Food
Google
Movies
Bayesian Inference
Software Engineering
Statistics (Academic Discipline)
Chad Scherrer Photo 2

Developer Relations Manager At Fp Complete

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Position:
Developer Relations Manager at FP Complete
Location:
Yakima, Washington
Industry:
Computer Software
Work:
FP Complete since Feb 2013
Developer Relations Manager
Yakima Valley Community College - Yakima, WA Sep 2012 - Mar 2013
Adjunct Professor of Mathematics
Self-employed - Yakima, Washington Jul 2012 - Feb 2013
Independent Consultant
Pacific Northwest National Laboratory - Richland, WA Dec 2000 - Jul 2012
Research Scientist
Columbia Basin College - Pasco, WA 2005 - 2008
Adjunct Professor of Mathematics
Education:
Indiana University Bloomington 1994 - 2000
PhD, Mathematics Rose-Hulman Institute of Technology 1990 - 1994
BS, Math Jasper High School
Skills:
Haskell
Statistical Modeling
Statistical Computing
R
Machine Learning
Parallel Computing
Parallel Programming
Parallel Algorithms
Statistics
Python
Dimensionality Reduction
Feature Selection
High Performance Computing
LaTeX
Mathematical Modeling
Data Analysis
Computer Science
Statistical Consulting
Statistical Learning
OpenMP
OCaml
Bayesian inference
Stochastic Simulation
Stochastic Optimization
Information Theory
Data Science
Scientific Computing
Algorithms
Science
Simulations
Matlab
Teaching
C
Research
Programming
Bayesian statistics
Monte Carlo Simulation
Linux
Pattern Recognition
Technical Writing
Linear Algebra
Natural Language Processing
Bayesian networks
Martial Arts
Kung Fu
Tai Chi Chuan
Tai Chi
Predictive Analytics
Chad Scherrer Photo 3

Chad Scherrer Yakima, WA

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Work:
Pacific Northwest National Laboratory
Richland, WA
2000 to 2012
Research Scientist
Columbia Basin College
Pasco, WA
2005 to 2008
Adjunct Professor
Indiana University
Bloomington, IN
1994 to 2000
Associate Instructor
Education:
Indiana University
Bloomington, IN
1994 to 2003
PhD in Mathematics
Rose-Hulman Institute of Technology
Terre Haute, IN
1990 to 1994
BS in Mathematics

Publications

Us Patents

System And Method For Anomaly Detection

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US Patent:
20030236652, Dec 25, 2003
Filed:
May 29, 2003
Appl. No.:
10/449755
Inventors:
Chad Scherrer - Pasco WA, US
Bradley Woodworth - Richland WA, US
Assignee:
Battelle - Richland WA
International Classification:
G06F017/10
US Classification:
703/002000
Abstract:
A system and method for detecting one or more anomalies in a plurality of observations. In one illustrative embodiment, the observations are real-time network observations collected from a plurality of network traffic. The method includes selecting a perspective for analysis of the observations. The perspective is configured to distinguish between a local data set and a remote data set. The method applies the perspective to select a plurality of extracted data from the observations. A first mathematical model is generated with the extracted data. The extracted data and the first mathematical model is then used to generate scored data. The scored data is then analyzed to detect anomalies.

System And Method For Anomaly Detection

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US Patent:
20070294187, Dec 20, 2007
Filed:
Jun 8, 2006
Appl. No.:
11/423046
Inventors:
Chad Scherrer - Pasco WA, US
International Classification:
H04L 9/00
US Classification:
705 75
Abstract:
A system and method for detecting one or more anomalies in a plurality of observations is provided. In one illustrative embodiment, the observations are real-time network observations collected from a stream of network traffic. The method includes performing a discrete decomposition of the observations, and introducing derived variables to increase storage and query efficiencies. A mathematical model, such as a conditional independence model, is then generated from the formatted data. The formatted data is also used to construct frequency tables which maintain an accurate count of specific variable occurrence as indicated by the model generation process. The formatted data is then applied to the mathematical model to generate scored data. The scored data is then analyzed to detect anomalies.
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Chad Scherrer from Seattle, WA, age ~52 Get Report