Applied Computer Science

Shane Torbert
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Applied Computer Science

Shane Torbert
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Found in: Reference, COMPUTERS GENERAL

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Overview

202 PAGESENGLISH

Promotional Details
  • Published date: Apr 08, 2024
  • Language: English
  • No. of Pages: 202
  • Publisher: Springer/Sci-Tech/Trade
  • ISBN: 9781489990334
  • Dimensions: 6.1" W x 1.0" L x 9.25" H
From the reviews: "There are many graphs and pseudocode listings in C++, Python, Fortran, Java, and other programming languages. . Teachers could use these to teach students the basics only, or they could add methodology to show students how to address a specific problem. Readers will find many numerical analysis examples that make the book friendlier to tactile learners who absorb knowledge by exploring the physical world around them. . high school students studying engineering, future graphic designers, and students . will benefit from reading this book." (Jolanta Mizera-Pietraszko, ACM Computing Reviews, June, 2012)
Dr. Shane Torbert holds a B.A. in Mathematics from the University of Virginia, and an M.Ed., M.S., and Ph.D. from George Mason University where he conducted research in the Center for Computational Fluid Dynamics.  He has been at Thomas Jefferson High School for Science and Technology since the summer of 1999 and full-time since 2001, having taught all levels of Math and Computer Science. Since 2004 he has been lab director of TJ's Computer Systems Lab.  He was a consultant for the College Board in Computer Science, served as a grant review panelist for the National Science Foundation, and has given presentations at the local, regional, state, and national levels including JOSTI, NCTM, NCSSS, and CSTA.  He has run workshops for Computer Science teachers sponsored by both Google and ACM.  Introductory materials developed by Dr. Torbert are used continually by beginning students each year.  


At the advanced level, his post-AP elective courses attract talented high school Computer Science students with a research interest in algorithms, optimization, agent-based models, search, parallel programming, computer vision, and machine learning.  Students from the lab have consistently placed well in Science Fair and contests including Intel, Siemens, and ISEF.  In addition, each fall Dr. Torbert coordinates the research efforts of TJ students working at external sites for a substantial portion of their school day, and directly alongside professional mentors from academia and industry.

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