Koc University Intelligent User Interfaces Lab

MS and PhD applicants: Apply now for three new projects. See details below.

Postdoc positions also available.

We are interested in enabling natural human-computer interaction by combining techniques from computer vision, machine learning, computer graphics, human-computer interaction and psychology. Specific areas that we focus on include:

  • multimodal human-computer interfaces,
  • affective computing,
  • pen-based interfaces, 
  • sketch-based applications, 
  • intelligent user interfaces
  • applications of computer vision and machine learning to solving real world problems.
  • Browse through the publications and research pages to get a flavor of IUI@KU


    New: SVM-based Sketch Recognition: Which Hyper-parameter Interval to Try by Kemal Tugrul Yesilbek, Cansu Sen, Serike Cakmak and T. Metin Sezgin has been accepted for publication in Expressive 2015.

    New: Recognition of Haptic Interaction Patterns in Dyadic Joint Object Manipulation by Cigil Ece Madan, Ayse Kucukyilmaz, Tevfik Metin Sezgin, and Cagatay Basdogan has been accepted for publication in IEEE Transactions on Haptics.

    New: Open Postdoctoral and Doctoral Positions in Automatic Emotion Recognition and Machine Learning. Check out the open positions page.

    New: Dr. Sezgin has received the Outstanding Young Scientist Award from the Turkish Academy of Sciences (TÜBA-GEBİP). 

    New: Dr. Sezgin presented the Lab's work on formative assessment at the The ASC-Inclusion final project review meeting in Luxembourg.

    Dr. Sezgin has been awarded a TUBITAK 1003 Grant. The grant will support research in development and evaluation of pen-based intelligent user interfaces for eLearning in the context of the FATIH initiative. Of hundreds of initial proposals submitted to the 1003 call, only 67 made it past the first round, and only nine were eventually funded at the end of the second round reviews. 

     Sezgin&Sezgin's article on finding portable congruential random number generators has been accepted for publication in the Computer Physics Communications journal. 

    DPFrag: A Trainable  Stroke Fragmentation Framework based on Dynamic Programming by R.Sinan Tümen and Tevfik Metin Sezgin has been accepted for publication in IEEE Computer Graphics and Applications.