Gregory P. Amis, Ph.D.

Machine learning expert with doctoral training in autonomous learning systems and professional experience in software engineering. Research interests include computational modeling and algorithm development for machine learning, data mining, decision support, and intelligent user interfaces.

• Resume (pdf)

  Requires Adobe Acrobat Reader.

  

• Main dissertation project

  I developed a neural network for pattern classification that learns from multiple data sources with disparate input dimensionalities, creating a unified model of the underlying class patterns. The system learns on-line, does not require parameter adjustment for robust performance, and is resilient to changing deployment contexts. In short, it is a fully autonomous learning system.

  This work was done in collaboration with my PhD adviser, Gail A. Carpenter, in the Technology Lab at Boston University's Department of Cognitive & Neural Systems. A first generation of this model has been submitted for publication to the journal Neural Networks.

  • Tech report (pdf)

    Amis, G. & Carpenter, G. A. (2009). Self-Supervised ARTMAP. Technical Report, CAS/CNS TR-2009-006, Boston, MA: Boston University.

  • Demo

    Animations illustrating the self-supervised learning paradigm and self-supervised ARTMAP performance. (Requires Adobe Flash plug-in.)

  • Code

    Zip archive of Java implementation with MATLAB scripts.

  • Data

    Zip archive of a MATLAB .mat file for Boston remote sensing benchmark.

• Other research projects
  • Default ARTMAP 2

    A successor to default ARTMAP (Carpenter, 2003) for robust pattern learning and classification across problem domains.

    • Publication (pdf)

      Amis, G. & Carpenter, G. A. (2007). Default ARTMAP 2. Proceedings of the International Joint Conference on Neural Networks (IJCNN'07), Orlando, FL, 777-782.

    • Demo

      PowerPoint show illustrating how default ARTMAP 2 differs from default ARTMAP. (Requires Microsoft PowerPoint 2000 or newer, or the free viewer.)

    • Code

      Zip archive of MATLAB implementation, including test cases, examples, and demos.

• Writing samples
  • Distributed ARTMAP

    A summary of the distributed ARTMAP model, from
    Amis, G. P., Carpenter, G. A., Ersoy, B., & Grossberg, S. (2009). Cortical learning of recognition categories: a resolution of the exemplar vs. prototype debate. Technical Report, CAS/CNS TR-2009-002, Boston, MA: Boston University.

  • "Traveling Gaussian Waves" Simulation Assignment

    One of the myriad simulation assignments I completed in my first three years in the PhD program at CNS. It is a mathematical and computational analysis of one theory of how the human visual cortex might process motion, assigned by
    Prof. Ennio Mingolla in his introductory class on neural models of vision.