Applied Research Lab:: Projects

I am currently accepting new undergraduate / graduate research assistant. If you are interested in doing research with me, please contact me for more information!

[I] Active Projects

1) Human Activity Recognition

In this project, we are trying to build computational tools to help the artist to create human movement that has aesthetics value and meaning. Through creating of these movements, we can understand the mechanism of the human figure movement and also to understand the meaning behind these movements. There are many facet of this projects, for examples:

  • idanceForms2 – a creative choreography sketchbook on iPad. Download idanceForms here.
  • Computational Conductor – using machine learning techniques to understand and recognize conducting gesture.

Publications (selected)

  • J. Pettigrew, G. Woo and H. H. Tsang, "Computational Intelligence in Human Feature Analysis and Pose Selection", in 2020 IEEE Symposium Series on Computational Intelligence (SSCI), Dec 1-4, 2020, Canberra Australia.
  • F. Tan, G. Woo, and H. H. Tsang, "CGLER: Laban Effort Framework Analysis with Conducting Gestures Using Neural Networks", in 2020 IEEE Symposium Series on Computational Intelligence (SSCI), Dec 1-4, 2020, Canberra Australia.
  • K. Carlson, P. Pasquier, H.H. Tsang, J. Phillips, T. Schiphorst and T. Calvert. “CoChoreo: A Generative Feature in iDanceForms for Creating Novel Keyframe Animation for Choreography”, in Proceedings of the Seventh International Conference on Computational Creativity, Paris, France, June 27 – July 1, 2016.
  • K. Carlson, H.H. Tsang, J. Phillips, T. Schiphorst, and T. Calvert. “Sketching Movement: Designing Creativity Tools for In-Situ, Whole-Body Authorship,” in Proceedings of the 2nd International Workshop on Movement and Computing, Vancouver, August 14-15, 2015, pp. 68-75. [Acceptance rate: 26/56, 46%]
  • K. Carlson, T. Schiphorst, K. Cochrane, J. Phillips, H.H. Tsang, and T. Calvert. “Moment by Moment: Creating Movement Sketches with Camera Stillframes,” in Proceedings of the ACM SIGCHI Conference on Creativity and Cognition, Glasgow, United Kingdom, June 22-25, 2015, pp. 131-140. [Acceptance rate: 23/88, 26%]

2) RNA Prediction and Design

RNA design algorithm takes an RNA secondary structure description as input and then try to identify an RNA strand that folds into this function-specific target structure. With new advances in biotechnology and synthetic biology, a reliable RNA design algorithm can be crucial steps to create new biochemical components. Our lab is interested in employing various computational intelligence techniques to propose the new paradigm to help with the RNA design problem. Recently, we have designed an algorithm SIMARD, which is based on the simulated annealing paradigm.

Publications (selected)


3) Computational Crime Analysis

With the advance of big data and machine learning techniques, law enforcement agencies are keen to use computational techniques to help them to prevent criminal activities or even to solve crime. Our lab's work in this area has two main paradigms

  • Using a virtual environment to help with emergency preparedness
  • Employing computational techniques and crime data, to help law enforcement agencies visualize and resource management

Publications (selected)

  • A.J. Park, R.N. Quadari, and H.H. Tsang. “Phishing Website Detection Framework Through Web Scraping and Data Mining”, the 8th IEEE Annual Information Technology, Electronics and Mobile Communication Conference, Vancouver, Canada, Oct 3-5, 2017. Received the best paper award
  • A.J. Park, B. Beck, D. Fletche, P. Lam, and H.H. Tsang. "Temporal Analysis of Radical Dark Web Forum Users", in Proceedings of the International Symposium on Foundations of Open Source Intelligence and Security Informatics, San Francisco, CA, USA, August 18-21, 2016, pp. 880-883.
  • B. Chersinoff, H.H. Tsang, and V. Spicer. "iPatrol+: Patterns of Public Disorder from a Community Volunteer Perspective," in Proceedings of the 43rd Annual Conference of the Western Society of Criminology, Vancouver, BC, Canada, February 4 -6, 2016, pp. 6.
  • A.J. Park and H.H. Tsang, “A Systematic Approach to Develop a Computational Framework for Counter-terrorism and Public Safety” Martin Bouchard, editor, Social Networks, Terrorism and Counter-terrorism: Radical and Connected, Routledge, 2015, 196-217.
  • A.J. Park, H.H. Tsang, M.Sun, and U. Glässer, “An Agent-Based Model and Computational Framework for Counter-Terrorism and Public Safety Based on Swarm Intelligence.” Journal of Security Informatics, 2012, 1:23.

4) Mobile Applications Development

In my classroom and lab, I have overseas the development of over 150 mobile applications. See here for some examples.

[II] Past Projects

Computational approach to predict species-specific type III secretion system (T3SS) effectors

We are using machine learning techniques to seek out the Type III secretion system (T3SS) effectors which are harmful to human.


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