Joseph Mahoney

 JosephM. Mahoney

Joseph M. Mahoney

  • Courses6
  • Reviews11
Jan 2, 2020
N/A
Textbook used: No
Would take again: Yes
For Credit: Yes

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Mandatory



Difficulty
Clarity
Helpfulness

Good

Prof. Joseph is one of the best engineering profs at Berks. You can see that he really wants you to learn the basic concepts and be creative with more complex solutions. He gets a bad rep for pushing students to think, but it really helps us learn the material better. He's an amazing prof!

Biography

Pennsylvania State University Berks - Engineering

Associate Professor at Penn State Berks
Mechanical or Industrial Engineering
Joseph
Mahoney
Allentown, Pennsylvania
Research in Human Motion, Low Cost Biomechanic Measurement Devices, Nonlinear Dynamics, Virtual Reality, Video Game Design


Experience

  • Penn State University

    Research Assistant

    Joseph worked at Penn State University as a Research Assistant

  • Penn State University

    Lecturer

    Lecturer in Mathematics

  • Penn State Berks

    Assistant Professor

    Joseph worked at Penn State Berks as a Assistant Professor

  • Penn State Berks

    Associate Professor

    Joseph worked at Penn State Berks as a Associate Professor

  • Penn State Erie, The Behrend Campus

    Faculty Lecturer

    Teaching Statics, System Dynamics and Material Mechanics

  • Johns Hopkins' CTY

    Instructor

    Instructor of "Principles of Engineering Design"

    Summers

Education

  • Penn State University

    Bachelor of Science (B.S.)

    Mechanical Engineering
    Schreyer Honors College Minors in both Mathematics and Engineering Mechanics

  • Penn State University

    Master of Science (M.S.)

    Mechanical Engineering
    Thesis: A Bimetallic Valve Solution for a Hydrogen-Powered Micro-Generator

  • Penn State University

    Doctor of Philosophy (Ph.D.)

    Engineering Science and Mechanics

  • Penn State University

    Research Assistant



  • Penn State University

    Lecturer


    Lecturer in Mathematics



Publications

  • Inter-trial Dynamics in Goal-oriented Tasks with Asymmetric Error and Reduced Precision

    Penn State University

  • Inter-trial Dynamics in Goal-oriented Tasks with Asymmetric Error and Reduced Precision

    Penn State University

  • Inter-trial Dynamics in Goal-oriented Tasks with Asymmetric Error and Reduced Precision

    Penn State University

  • Inter-trial Dynamics in Goal-oriented Tasks with Asymmetric Error and Reduced Precision

    Penn State University

  • Inter-trial Dynamics in Goal-oriented Tasks with Asymmetric Error and Reduced Precision

    Penn State University

  • Inter-trial Dynamics in Goal-oriented Tasks with Asymmetric Error and Reduced Precision

    Penn State University

  • Design method for multi-user workstations utilizing anthropometry and preference data

    Applied Ergonomics

  • Inter-trial Dynamics in Goal-oriented Tasks with Asymmetric Error and Reduced Precision

    Penn State University

  • Design method for multi-user workstations utilizing anthropometry and preference data

    Applied Ergonomics

  • The Dynamical Analysis of Inter-Trial Fluctuations Near Goal Equivalent Manifolds

    Springer New York

    Using the concept of task manifolds, a number of data analysis methods have been used to explain how redundancy influences the structure of variability observed during repeated motor performance. Here we describe investigations that integrate the task manifold perspective with the analysis of Inter-Trial task dynamics. Goal equivalent manifolds (GEMs), together with optimal control ideas, are used to formulate simple models that serve as experimentally testable hypotheses on how Inter-Trial fluctuations are generated and regulated. In an experimental context, these phenomenological models allow us to show how error-correcting control is spatiotemporally organized around a given GEM. To illustrate our approach, we apply it to study the variability observed in a virtual shuffleboard task. The geometric stability properties of the Inter-Trial dynamics near the GEM are extracted from fluctuation time series data. We find that subjects exhibit strong control of fluctuations in an eigendirection transverse to the GEM, whereas they only weakly control fluctuations in an eigendirection nearly, but not exactly, tangent to it. We demonstrate that our dynamical analysis is robust under coordinate transformations, and discuss how our results support a generalized interpretation of the minimum intervention principle that suggests the involvement of competing costs in addition to goal-level error minimization.

  • Inter-trial Dynamics in Goal-oriented Tasks with Asymmetric Error and Reduced Precision

    Penn State University

  • Design method for multi-user workstations utilizing anthropometry and preference data

    Applied Ergonomics

  • The Dynamical Analysis of Inter-Trial Fluctuations Near Goal Equivalent Manifolds

    Springer New York

    Using the concept of task manifolds, a number of data analysis methods have been used to explain how redundancy influences the structure of variability observed during repeated motor performance. Here we describe investigations that integrate the task manifold perspective with the analysis of Inter-Trial task dynamics. Goal equivalent manifolds (GEMs), together with optimal control ideas, are used to formulate simple models that serve as experimentally testable hypotheses on how Inter-Trial fluctuations are generated and regulated. In an experimental context, these phenomenological models allow us to show how error-correcting control is spatiotemporally organized around a given GEM. To illustrate our approach, we apply it to study the variability observed in a virtual shuffleboard task. The geometric stability properties of the Inter-Trial dynamics near the GEM are extracted from fluctuation time series data. We find that subjects exhibit strong control of fluctuations in an eigendirection transverse to the GEM, whereas they only weakly control fluctuations in an eigendirection nearly, but not exactly, tangent to it. We demonstrate that our dynamical analysis is robust under coordinate transformations, and discuss how our results support a generalized interpretation of the minimum intervention principle that suggests the involvement of competing costs in addition to goal-level error minimization.

  • Both coordination and symmetry of arm swing are reduced in Parkinson's disease

    Gait & Posture

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