Joshua Horacsek


Originally from Vancouver B.C. and now located in the South-west quadrant of Calgary, I'm a PhD student at the University of Calgary studying computer science. My main area of research is computer graphics, but my interests extend much further into computer science and math (and maker space stuff, and AI, and makerspace stuff, and blockchain stuff, and whatever else captivates me).


  • 2019: CPSC TA Excellence Award
  • 2018: CPSC TA Excellence Award, Sudent Union TA Excellence Award
  • 2017: NSERC PGSD, Alberta Innovates Technology Futures
  • 2016: CPSC TA Excellence Award, Department Research Award
  • 2015: NSERC CGSM, Department Research Award
  • 2014: NSERC USRA, Undergrad Research Award
  • 2012: NSERC USRA

Projects and Publications

  • Compactly Supported Biorthogonal Wavelet Bases on the Body Centered Cubic Lattice

    Joshua Horacsek, Usman Alim

    In this work, we present a family of compact, biorthogonal wavelet filter banks that are applicable to the Body Centered Cubic (BCC) lattice. While the BCC lattice has been shown to have superior approximation properties for volumetric data when compared to the Cartesian Cubic (CC) lattice, there has been little work in the way of designing wavelet filter banks that respect the geometry of the BCC lattice. Since wavelets have applications in signal de-noising, compression, and sparse signal reconstruction, these filter banks are an important tool that addresses some of the scalability concerns presented by the BCC lattice. We use these filters in the context of volumetric data compression and reconstruction and qualitatively evaluate our results by rendering images of isosurfaces from compressed data.

    Google Scholar: Link
    Github: Link
  • A closed PP form of box splines via Green’s function decomposition

    Joshua Horacsek, Usman Alim

    For the class of non-degenerate box splines, we prove that these box splines are piecewise polynomial. This is not a new result, it is in fact a well known and useful property of box splines. However, our proof is constructive, and the main result of this work is a corollary that follows from this proof, namely one that gives an explicit construction scheme for the polynomial pieces in the interior regions of any non-degenerate box spline.

    ScienceDirect: Link
  • Demo Hour: RIPT

    Claire Mikalauskas, Tiffany Wun, Kevin Ta, Joshua Horacsek, Lora Oehlberg Abstract:

    Robot Improv Puppet Theatre (RIPT) is an improvised theater experience centered around an Arduino Braccio robot, Pokey. Pokey performs gestures and dialogue in short-form improv scenes based on audience input from a mobile device. The robot’s performance is based entirely on audience participation, providing audience members an opportunity to see and hear their.

    ACM DL: Link
  • Improvising with an Audience-Controlled Robot Performer

    Claire Mikalauskas, Tiffany Wun, Kevin Ta, Joshua Horacsek, Lora Oehlberg Abstract:

    In improvisational theatre (improv), actors perform unscripted scenes together, collectively creating a narrative. Audience suggestions introduce randomness and build audience engagement, but can be challenging to mediate at scale. We present Robot Improv Puppet Theatre (RIPT), which includes a performance robot (Pokey) who performs gestures and dialogue in short-form improv scenes based on audience input from a mobile interface. We evaluated RIPT in several initial informal performances, and in a rehearsal with seven professional improvisers. The improvisers noted how audience prompts can have a big impact on the scene - highlighting the delicate balance between ambiguity and constraints in improv. The open structure of RIPT performances allows for multiple interpretations of how to perform with Pokey, including one-on-one conversations or multi-performer scenes. While Pokey lacks key qualities of a good improviser, improvisers found his serendipitous dialogue and gestures particularly rewarding.

    ACM DL: Link

Research Interests

Graphics, Functional and Numerical Analysis, Wavelets, Combinatorics, Machine Learning, Bioinformatics