Intelligent Robot Learning Laboratory (IRL Lab) Yang Hu

CONTACT INFORMATION:
Yang Hu
PhD Student, Computer Science
Email: yang.hu@wsu.edu
Office: Dana Hall 3


My Story

I am a PhD student, working with the Intelligent Robot Learning Laboratory (IRLL), under the guidance of professor Matthew E. Taylor. I was previously working with the Sustainable Product Life-cycle Design Lab on product disassembly design estimation.

Research

Currently I’m interested in utilizing Reinforcement learning method to build an agent to learn how to make 3D CAD models under CAD software environment.

Education

Washington State University(present) PhD of Computer Science
Washington State University(2011-2013) Master of science, Mechanical Engineering
South China University of Technology(2005– 2008) Master of science, Polymer Chemistry and Physics
Shenzhen University(2001–2005) Bachelor of science, Applied Chemistry

Current Projects

By: Yang Hu, and Matthew E. Taylor

Taking a Computer-Aided Design (CAD) class is a prerequisite for Mechanical Engineering freshmen at many universities, including ours. To make the learning process easier and more interesting, we designed and implemented a tutorial for an open source CAD program, FreeCAD, to teach students how to use Boolean operations to construct complex objects from multiple simple shapes. Instead of teaching a single method to construct a model, the program first automatically learns all possible ways to construct a model and then can teach the student multiple ways to make the 3D model. [1]

[1] [pdf] Yang Hu and Matthew E. Taylor. Work In Progress: A Computer-Aided Design Intelligent Tutoring System Teaching Strategic Flexibility. In Proceedings of the ASEE’s 123rd Annual Conference & Exposition, New Orleans, LA, USA, June 2016.
[Bibtex]
@inproceedings{2016ASEE-Hu,
author={Yang Hu and Matthew E. Taylor},
title={{Work In Progress: A Computer-Aided Design Intelligent Tutoring System Teaching Strategic Flexibility}},
booktitle={{Proceedings of the {ASEE}'s 123rd Annual Conference \& Exposition}},
month={June},
year={2016},
address={New Orleans, LA, USA},
bib2html_pubtype={Refereed Conference},
bib2html_rescat={Intelligent Tutoring System, Multiple solutions},
abstract={Taking a Computer-Aided Design (CAD) class is a prerequisite for Mechanical Engineering freshmen at many universities, including at Washington State University. The traditional way to learn CAD software is to follow examples and exercises in a textbook. However, using written instruction is not always effective because textbooks usually support single strategy to construct a model. Missing even one detail may cause the student to become stuck, potentially leading to frustration.
To make the learning process easier and more interesting, we designed and implemented an intelligent tutorial system for an open source CAD program, FreeCAD, for the sake of teaching students some basic CAD skills (such as Boolean operations) to construct complex objects from multiple simple shapes. Instead of teaching a single method to construct a model, the program first automatically learns all possible ways to construct a model and then can teach the student to draw the 3D model in multiple ways. Previous research efforts have shown that learning multiple potential solutions can encourage students to develop the tools they need to solve new problems.
This study compares textbook learning with learning from two variants of our intelligent tutoring system. The textbook approach is considered the baseline. In the first tutorial variant, subjects were given minimal guidance and were asked to construct a model in multiple ways. Subjects in the second tutorial group were given two guided solutions to constructing a model and then asked to demonstrate the third solution when constructing the same model. Rather than directly providing instructions, participants in the second tutorial group were expected to independently explore and were only provided feedback when the program determined he/she had deviated too far from a potential solution. The three groups are compared by measuring the time needed to 1) successfully construct the same model in a testing phase, 2) use multiple methods to construct the same model in a testing phase, and 3) construct a novel model.}
}

Publications

2016

  • Yang Hu and Matthew E. Taylor. Work In Progress: A Computer-Aided Design Intelligent Tutoring System Teaching Strategic Flexibility. In Proceedings of the ASEE’s 123rd Annual Conference & Exposition, New Orleans, LA, USA, June 2016.
    [BibTeX] [Abstract] [Download PDF]

    Taking a Computer-Aided Design (CAD) class is a prerequisite for Mechanical Engineering freshmen at many universities, including at Washington State University. The traditional way to learn CAD software is to follow examples and exercises in a textbook. However, using written instruction is not always effective because textbooks usually support single strategy to construct a model. Missing even one detail may cause the student to become stuck, potentially leading to frustration. To make the learning process easier and more interesting, we designed and implemented an intelligent tutorial system for an open source CAD program, FreeCAD, for the sake of teaching students some basic CAD skills (such as Boolean operations) to construct complex objects from multiple simple shapes. Instead of teaching a single method to construct a model, the program first automatically learns all possible ways to construct a model and then can teach the student to draw the 3D model in multiple ways. Previous research efforts have shown that learning multiple potential solutions can encourage students to develop the tools they need to solve new problems. This study compares textbook learning with learning from two variants of our intelligent tutoring system. The textbook approach is considered the baseline. In the first tutorial variant, subjects were given minimal guidance and were asked to construct a model in multiple ways. Subjects in the second tutorial group were given two guided solutions to constructing a model and then asked to demonstrate the third solution when constructing the same model. Rather than directly providing instructions, participants in the second tutorial group were expected to independently explore and were only provided feedback when the program determined he/she had deviated too far from a potential solution. The three groups are compared by measuring the time needed to 1) successfully construct the same model in a testing phase, 2) use multiple methods to construct the same model in a testing phase, and 3) construct a novel model.

    @inproceedings{2016ASEE-Hu,
    author={Yang Hu and Matthew E. Taylor},
    title={{Work In Progress: A Computer-Aided Design Intelligent Tutoring System Teaching Strategic Flexibility}},
    booktitle={{Proceedings of the {ASEE}'s 123rd Annual Conference \& Exposition}},
    month={June},
    year={2016},
    address={New Orleans, LA, USA},
    bib2html_pubtype={Refereed Conference},
    bib2html_rescat={Intelligent Tutoring System, Multiple solutions},
    abstract={Taking a Computer-Aided Design (CAD) class is a prerequisite for Mechanical Engineering freshmen at many universities, including at Washington State University. The traditional way to learn CAD software is to follow examples and exercises in a textbook. However, using written instruction is not always effective because textbooks usually support single strategy to construct a model. Missing even one detail may cause the student to become stuck, potentially leading to frustration.
    To make the learning process easier and more interesting, we designed and implemented an intelligent tutorial system for an open source CAD program, FreeCAD, for the sake of teaching students some basic CAD skills (such as Boolean operations) to construct complex objects from multiple simple shapes. Instead of teaching a single method to construct a model, the program first automatically learns all possible ways to construct a model and then can teach the student to draw the 3D model in multiple ways. Previous research efforts have shown that learning multiple potential solutions can encourage students to develop the tools they need to solve new problems.
    This study compares textbook learning with learning from two variants of our intelligent tutoring system. The textbook approach is considered the baseline. In the first tutorial variant, subjects were given minimal guidance and were asked to construct a model in multiple ways. Subjects in the second tutorial group were given two guided solutions to constructing a model and then asked to demonstrate the third solution when constructing the same model. Rather than directly providing instructions, participants in the second tutorial group were expected to independently explore and were only provided feedback when the program determined he/she had deviated too far from a potential solution. The three groups are compared by measuring the time needed to 1) successfully construct the same model in a testing phase, 2) use multiple methods to construct the same model in a testing phase, and 3) construct a novel model.}
    }

  • Yang Hu and Matthew E. Taylor. A Computer-Aided Design Intelligent Tutoring System Teaching Strategic Flexibility. Transactions on Techniques for STEM Education, October–December 2016.
    [BibTeX] [Abstract] [Download PDF]

    Taking a Computer-Aided Design (CAD) class is a prerequisite for Mechanical Engineering freshmen at many universities, including at Washington State University. The traditional way to learn CAD software is to follow examples and exercises in a textbook. However, using written instruction is not always effective because textbooks usually support a single strategy to construct a model. Missing even one detail may cause the student to become stuck, potentially leading to frustration. To make the learning process easier and more interesting, we designed and implemented an intelligent tutorial system for an open source CAD program, FreeCAD, for the sake of teaching students some basic CAD skills (such as Boolean operations) to construct complex objects from multiple simple shapes. Instead of teaching a single method to construct a model, the program first automatically learns all possible ways to construct a model and then can teach the student to draw the 3D model in multiple ways. Previous research efforts have shown that learning multiple potential solutions can encourage students to develop the tools they need to solve new problems. This study compares textbook learning with learning from two variants of our intelligent tutoring system. The textbook approach is considered the baseline. In the first tutorial variant, subjects were given minimal guidance and were asked to construct a model in multiple ways. Subjects in the second tutorial group were given two guided solutions to constructing a model and then asked to demonstrate the third solution when constructing the same model. Rather than directly providing instructions, participants in the first tutorial group were expected to independently explore and were only provided feedback when the program determined he/she had deviated too far from a potential solution. The three groups are compared by measuring the time needed to 1) successfully construct the same model in a testing phase, 2) use multiple methods to construct the same model in a testing phase, and 3) construct a novel model.

    @article{2016STEMTransactions-Yang,
    author={Hu, Yang and Taylor, Matthew E.},
    title={{A Computer-Aided Design Intelligent Tutoring System Teaching Strategic Flexibility}},
    journal={{Transactions on Techniques for {STEM} Education}},
    month={October--December},
    year={2016},,
    abstract={Taking a Computer-Aided Design (CAD) class is a prerequisite for Mechanical Engineering freshmen at many universities, including at Washington State University. The traditional way to learn CAD software is to follow examples and exercises in a textbook. However, using written instruction is not always effective because textbooks usually support a single strategy to construct a model. Missing even one detail may cause the student to become stuck, potentially leading to frustration.
    To make the learning process easier and more interesting, we designed and implemented an intelligent tutorial system for an open source CAD program, FreeCAD, for the sake of teaching students some basic CAD skills (such as Boolean operations) to construct complex objects from multiple simple shapes. Instead of teaching a single method to construct a model, the program first automatically learns all possible ways to construct a model and then can teach the student to draw the 3D model in multiple ways. Previous research efforts have shown that learning multiple potential solutions can encourage students to develop the tools they need to solve new problems.
    This study compares textbook learning with learning from two variants of our intelligent tutoring system. The textbook approach is considered the baseline. In the first tutorial variant, subjects were given minimal guidance and were asked to construct a model in multiple ways. Subjects in the second tutorial group were given two guided solutions to constructing a model and then asked to demonstrate the third solution when constructing the same model. Rather than directly providing instructions, participants in the first tutorial group were expected to independently explore and were only provided feedback when the program determined he/she had deviated too far from a potential solution. The three groups are compared by measuring the time needed to 1) successfully construct the same model in a testing phase, 2) use multiple methods to construct the same model in a testing phase, and 3) construct a novel model.}
    }

  • Yang Hu, Dominique Tilke, Taylor Adams, Aaron S. Crandall, Diane J. Cook, and Maureen Schmitter-Edgecombe. Smart home in a box: Usability study for a large scale self-installation of smart home technologies.. Journal of Reliable Intelligent Environments, 2(2):93-106, June 2016.
    [BibTeX] [Abstract] [DOI]

    This study evaluates the ability of users to self-install a smart home in a box (SHiB) intended for use by a senior population. SHiB is a ubiquitous system, developed by the Washington State University Center for Advanced Studies in Adaptive Systems (CASAS). Participants involved in this study are from the greater Palouse region of Washington State, and there are 13 participants in the study with an average age of 69.23. The SHiB package, which included several different types of components to collect and transmit sensor data, was given to participants to self-install. After installation of the SHiB, the participants were visited by researchers for a check of the installation. The researchers evaluated how well the sensors were installed and asked the resident questions about the installation process to help improve the SHiB design. The results indicate strengths and weaknesses of the SHiB design. Indoor motion tracking sensors are installed with high success rate, low installation success rate was found for door sensors and setting up the Internet server.

    @article{2016RIE-Yang,
    author={Hu, Yang and Tilke, Dominique and Adams, Taylor and Crandall, Aaron S. and Cook, Diane J. and Schmitter-Edgecombe, Maureen},
    title={{Smart home in a box: Usability study for a large scale self-installation of smart home technologies.}},
    journal={{Journal of Reliable Intelligent Environments}},
    volume={2},
    number={2},
    pages={93--106},
    month={June},
    year={2016},
    doi={10.1007/s40860-016-0021-y},
    abstract={This study evaluates the ability of users to self-install a smart home in a box (SHiB) intended for use by a senior population. SHiB is a ubiquitous system, developed by the Washington State University Center for Advanced Studies in Adaptive Systems (CASAS). Participants involved in this study are from the greater Palouse region of Washington State, and there are 13 participants in the study with an average age of 69.23. The SHiB package, which included several different types of components to collect and transmit sensor data, was given to participants to self-install. After installation of the SHiB, the participants were visited by researchers for a check of the installation. The researchers evaluated how well the sensors were installed and asked the resident questions about the installation process to help improve the SHiB design. The results indicate strengths and weaknesses of the SHiB design. Indoor motion tracking sensors are installed with high success rate, low installation success rate was found for door sensors and setting up the Internet server.}
    }

2015

  • Yang Hu, Raghunathan Srinivasan, Jessica Spoll, and Gaurav Ameta. Graph Based Method and Tool for Complete and Selective Disassembly Time Estimation in Early Design. Journal of Computing and Information Science in Engineering, 2015.
    [BibTeX]
    @article{hu2015graph,
    author={Yang Hu and Raghunathan Srinivasan and Jessica Spoll and Gaurav Ameta},
    title={{Graph Based Method and Tool for Complete and Selective Disassembly Time Estimation in Early Design}},
    journal={{Journal of Computing and Information Science in Engineering}},
    year={2015}
    }

2013

  • Yang Hu and Gaurav Ameta. Life Cycle Assessment and Eco-Design of a Wireless TV/VCR Remote. In ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, page V02AT02A049–V02AT02A049. American Society of Mechanical Engineers,, 2013.
    [BibTeX] [DOI]
    @inproceedings{hu2013life,
    author={Yang Hu and Gaurav Ameta},
    title={{Life Cycle Assessment and Eco-Design of a Wireless {TV/VCR} Remote}},
    booktitle={{{ASME} 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference}},
    pages={V02AT02A049--V02AT02A049},
    year={2013},
    doi={10.1115/DETC2013-12484},
    organization={American Society of Mechanical Engineers}
    }

2008

  • Yan Pang, Bo Liu, Shuang-gui Qing, Lin-na Sun, Wei-zong Lv, and Yang Hu. Influence of methylic Modification on the Forming Membrane Performance of 8-Hydroxylquinoline Aluminum [J]. Journal of Materials Science and Engineering, 6:15, 2008.
    [BibTeX]
    @article{pang2008influence,
    author={Yan Pang and Bo Liu and Shuang-gui Qing and Lin-na Sun and Wei-zong Lv and Yang Hu},
    title={{Influence of methylic Modification on the Forming Membrane Performance of 8-Hydroxylquinoline Aluminum [{J}]}},
    journal={{Journal of Materials Science and Engineering}},
    volume={6},
    pages={015},
    year={2008},
    url={http://en.cnki.com.cn/Article_en/CJFDTOTAL-CLKX200806015.htm}
    }

  • Fang Liu, Yang Hu, Zhengmei Lin, Junqi Ling, Yuanfang Luo, and Demin Jia. Preparation and properties of new resin root canal filling materials. Acta Materiae Compositae Sinica, 6:10, 2008.
    [BibTeX]
    @article{liu2008preparation,
    author={Fang Liu and Yang Hu and Zhengmei Lin and Junqi Ling and Yuanfang Luo and Demin Jia},
    title={{Preparation and properties of new resin root canal filling materials}},
    journal={{Acta Materiae Compositae Sinica}},
    volume={6},
    pages={010},
    year={2008},
    url={http://en.cnki.com.cn/Article_en/CJFDTOTAL-FUHE200806010.htm}
    }