Dr. Umair Azfar Khan

Assistant Professor,
Computer Science,
School of Science & Engineering
Email: umair.azfar@sse.habib.edu.pk

Dr. Khan has always been passionate about computer games from the early days of Commodore 64 when a game was considered to be a good game with graphics if its size was bigger than 256 Kilobytes. His interest brought him into the realm of Computer Science where he found out that there is much more to games than fancy graphics. His research took him through the fields of Software Engineering and Design, and applying graph theory techniques for Artificial Intelligent Decision Making through Planning.

With the development of countless game engines and his own experience with making games and teaching at various universities, Dr. Khan aims to make game development easy enough so that anyone can make the game they want. This will include art development, artificially intelligent programming and multiplatform deployment. With Habib University’s emphasis on social sciences, he aims to make games that are not only fun to play, but also cover many social issues that are present in our current society, to spread awareness and provide help by disseminating information.

Education

  • Ph.D. in Information Science, Kyushu University, Fukuoka, Japan
  • M.S. in Software Development, University of Tampere, Tampere, Finland
  • B.S. in Computer Systems Engineering, Ghulam Ishaq Khan Institute, Topi, Pakistan

Research Interests

Dr. Khan’s research interests lie in the field of Artificial Intelligence and Planning Graphs. With the help of planning graphs, all the possible outcomes in a contained environment can be mapped. When a decision is required, the computer acquires the least costing outcome based on a series of actions and the current state of the environment. These actions can range from telling an artificially intelligent agent to follow an alternate route, tell the fire prevention system in a chemical factory to use the appropriate fire extinguisher or tell a Mars probe to fire jets in a certain order and duration to rectify its path.

Dr. Khan specifically used planning graphs to help agents take decision in a self-contained environment of a Role Playing Game. On top of that, the agents decided which actions to do based on their mental attributes which decided if the agent was morally good or bad. He aims to further this research to create agents that respond more naturally to the available choices, based on their emotional makeup and then follow a sound plan to achieve their goals.

Courses Taught at HU

Selected Publications

  • Umair Azfar Khan and Yoshihiro Okada: Genetic Algorithm (GA)-Based NPC Making, Encyclopedia of Computer Graphics and Games, Springer International Publishing, pp. 1-7. 2015
  • A Framework for Defining Intelligent Agents with Different Orientations that take Decisions based on a Planning Graph in a Game Environment (PhD Thesis)
  • Umair Azfar Khan and Yoshihiro Okada: Multi-step Decision Making Process for Non-Playable Characters in an RPG, 13th International Conference on e-Society (ES 2015).
  • Umair Azfar Khan and Yoshihiro Okada: Emotional Decision Making Response of Non-Playable Characters in a Role-Playing Game, IADIS International Journal On Computer Science and Information Systems, ISSN: 1646-3692, pp. 53-66 Vol.9 Number 2, 2014. http://www.iadisportal.org/ijcsis/
  • Umair Azfar Khan and Yoshihiro Okada : Planning Graph with Character Orientation for Decision Making of Non-Playable Characters in a Role-Playing Game, Proc. of the 7th Int. Conf. on Game and Entertainment Technologies (GET2014), pp. 165-172, July 15-17, 2014.
  • Umair Azfar Khan and Yoshihiro Okada: Character Generation using Interactive Genetic Algorithm, Proc. of the GameOn 2013, pp. 31-35, November 25-27, 2013.
  • Umair Azfar Khan, Yoshihiro Okada: Evolving story and character generation for role-playing games, Proc. of the workshop at SIGGRAPH ASIA 2012, pp. 59-64, Nov., 26-27, 2012.
  • Umair Azfar Khan and Yoshihiro Okada: 3D Terrain Generation and Texture Manipulation by Voice Input, Proc. of GameOn-Asia 2012, pp. 71-75, Feb., 24-26, 2012.
  • Azfar. U, Qureshi. H., Comparative Analysis of the Computational Methods used in Protein Structure Prediction. BIOCOMP’10, July, 2010.
  • Azfar, U., Improved Iterative Software Development Method for Game Design, Masters Thesis, in Department of Computer Sciences. 2008, University of Tampere, Tampere, Finland.

 

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