Anthony D. Rhodes Office: NH M324 |

Machine Learning, Artificial Intelligence, Numerical Analysis, Computational Mathematics, Data Science, Intellectual History, Fin de Siecle Studies.

__Education__

**Ph.D.** Mathematical Sciences, Portland State University. (in progress)

<>Allied Field: Computer Science; Focus: Machine Learning

<>Dissertation: "Efficient Object Localizaton for Situation Recognition in Computer Vision."

<>Advisors: Melanie Mitchell, Computer Science, Portland State University;Bruno Jedynak, Statistics, Portland State University.

**M.S.** Mathematics, Portland State University.

<>Foci: Algebra, Topology, Discrete Mathematics, Analysis.

<>Thesis: "The Algebraic Structure of Cellular Automata."

**G.C.C.I.** Graduate Certificate in Computational Intelligence, Portland State University.

**G.C.A.S.** Graduate Certificate in Applied Statistics, Portland State University.

**M.A.** History, Philosophy and German Studies, Portland State University.

<>Focus: Modern European Intellectual History

<>Thesis: "Jacob Burckhardt: History and the Greeks in the Modern Context."

**B.A.** Mathematics, with distinction, UC San Diego.

**B.A.** History, Minor: Classical Studies, with distinction, UC San Diego.

__Publications__

Rhodes, A. D., Witte, J., Mitchell, M., and Jedynak, B (2017). Bayesian optimization for refining object proposals. Submitted.

Rhodes, A. D., Quinn, M. H., and Mitchell, M. (2016). Fast on-line kernel density estimation for active object localization. To appear in Proceedings of the International Joint Conference on Neural Networks (IJCNN), 2017.

Quinn, M. H., Rhodes, A. D., and Mitchell, M. (2016). Active object localization in visual situations. arXiv 1607.00548.

__Recent Work__

**Research Assistantship in Machine Learning and Visual Situation Recognition (Winter 2015-Present):** Abstract

<> This project investigates a novel approach to building computer systems that can recognize visual situations;

the approach explored integrates two previously-studied approaches: brain-inspired neural networks for lower-lever

vision and cognitive-level models of concepts and analogy-making.

<> Project is funded by the National Science Foundation (NSF).

<> Advisor: Melanie Mitchell , Computer Science, Portland State University.

**Lectures in Mathematics for Complex Systems Science (2014):**

<> Content/curriculum creation for large-scale courses for http://www.complexityexplorer.org,

a web-based repository of educational materials related to complex systems science.

<>Advisor: Melanie Mitchell, Computer Science, Portland State University.

*Click image to view my lecture series for 'complexity explorer' MOOC*

**Statistics Consultation for University Mathematics Placement Scores (Spring 2014):**

<> Directed a study to determine the overall efficacy of the undergraduate placement examination process at Portland State University.

<> Advisor: Mara Tableman (Statistics/Mathematics), Portland State University.

__Some Papers and Lecture Materials__

<>"Graphical Models for Machine Learning", lecture notes

<>"Gaussian Process Regression for Visual Situation Recognition", slides

<>"Lectures in Graph Theory and Complex Systems," Part 1 Part 2
Part 3 Part 4 Part 5
Part 6 Part 7 Part 8
Part 9

<>"Lectures in Numerical Analysis," Part 1 Part 2 Part 3
Part 4 Part 5 Part 6 Part7
Part 8 Part 9 Part 10 Part 11
Part 12 Part 13 Part 14 Part 15

<>"The Algebraic Structure of Cellular Automata," pp. 28. PDF

<>"Jacob Burckhardt: History and the Greeks in the Modern Context," pp. 119. PDF

<>"A Statistical Analysis of Undergraduate Mathematics Placement Scores at Portland State University," pp. 19. PDF

<>"The Case Against Computational Theory of Mind: A Refutation of Mathematically-Contigent Weak A.I.," pp. 27.

Listen to my music here: AMAZON SPOTIFY

__Courses I Have Taught Previously__

Math 30: Pre-Algebra

Math 60: Algebra/Geometry I

Math 65: Algebra/Geometry II

Math 95: Intermediate Algebra/Geometry

Math 105: Exploring Mathematics

Math 107: Math & Society

Math 111: Pre-Calculus I

Math 112: Pre-Calculus II/Trigonometry

Math 171: Computational Calculus I

Math 172: Computational Calculus II

Math 221: Finite Mathematics

Math 241: Calculus for Business/Economics

Math 243: Statistics/Probability I

Math 244: Statistics II

Math 251: Calculus I

Math 252: Calculus II

Math 253: Calculus III

Math 254: Calculus IV

Math 256: Intro to Differential Equations

Math 261: Intro to Linear Algebra

Math 273: Vector Calculus

*Math 300: Computational Mathematics & Numerical Analysis

Math 321: Ordinary Differential Equations

*Math 398: History of Mathematics

*[MOOC]: Matrix Algebra & Applications to Complex Systems

*[MOOC]: Graph Theory/Network Theory & Applications to Complex Systems

*Designed (and taught) curriculum

*Calculus Lecture: Day One