Kaya Oğuz has a BSc degree in Software Engineering from Izmir University of Economics (2007), a MSc degree in Computer Games Technology from University of Abertay Dundee (2009) and a PhD in Information Techologies from Ege University (2016). Currently, he is appointed as an assistant professor at Izmir University of Economics.
Kaya Oğuz gives undergraduate courses on computer games, software engineering and computer science. You can visit the university directory for a complete list.
His research interests cover artificial and computational intelligence in computer games, machine learning, image processing, medical imaging and fMRI.
A. P. Akay et al., “Genetic imaging study with [Tc-99m] TRODAT-1 SPECT in adolescents with ADHD using OROS-methylphenidate,” Progress in Neuro-Psychopharmacology and Biological Psychiatry, vol. 86, pp. 294–300, Aug. 2018.
K. Oğuz, B. Canlıtürk, C. Kabar, O. Durukan, and B. Özceylan, “Digital Recognition and Evaluation of the Clock Drawing Test,” in 2018 26th Signal Processing and Communications Applications Conference (SIU), 2018.
İ. Korkmaz and K. Oğuz, “Application of Neural Gas Networks to Object Detection,” in 4th International Conference on Engineering and Natural Sciences, 2018.
C. Candemir, K. Oğuz, S. Korukoğlu, and A. S. Gönül, “Detection and Evalution of Activation Instances as Change Points in Functional MR Images,” in 2018 26th Signal Processing and Communications Applications Conference (SIU), 2018.
M. B. Temuçin and K. Oğuz, “Procedural City Generation Using Cellular Automata,” presented at the Eurasia Graphics 2017 Conference, Nov-2017.
C. Candemir and K. Oğuz, “A Comparative Study on Parameter Selection and Outlier Removal for Change Point Detection in Time Series,” in European Conference on Electrical Engineering and Computer Science (EECS 2017), 2017.
F. Simsek, K. Oguz, O. Kitis, S. T. Akan, M. J. Kempton, and A. S. Gonul, “Neural activation during cognitive reappraisal in girls at high risk for depression,” Progress in Neuro-Psychopharmacology and Biological Psychiatry, vol. 77, pp. 49–56, 2017.
K. Oguz, M. G. Cinsdikici, and A. S. Gonul, “Robust activation detection methods for real-time and offline fMRI analysis,” Computer Methods and Programs in Biomedicine, vol. 144, pp. 1–11, 2017.
K. Oguz and S. Gül, “Managing and evaluating team projects in software engineering education [Yazilim Mühendisligi Egitiminde Takim Projelerinin Yonetimi ve Degerlendirilmesi],” in CEUR Workshop Proceedings, 2017, vol. 1980, pp. 184–195.
M. M. Bilgi, S. Taspinar, B. Aksoy, K. Oguz, K. Coburn, and A. S. Gonul, “The relationship between childhood trauma, emotion recognition, and irritability in schizophrenia patients,” Psychiatry Research, vol. 251, pp. 90–96, 2017.
Z. A. Dağdeviren, K. Oğuz, and M. Cinsdikici, “Automatic registration of structural brain MR images to MNI image space,” in 2015 23nd Signal Processing and Communications Applications Conference (SIU), 2015, pp. 359–362.
U. Biyik, D. Keskin, K. Oguz, F. Akdeniz, and A. S. Gonul, “Facial emotion recognition in remitted depressed women,” Asian Journal of Psychiatry, vol. 17, pp. 111–113, 2015.
Z. A. Dagdeviren, K. Oguz, and M. G. Cinsdikici, “Three techniques for automatic extraction of corpus callosum in structural midsagittal brain MR images: Valley Matching, Evolutionary Corpus Callosum Detection and Hybrid method,” Engineering Applications of Artificial Intelligence, vol. 31, pp. 101–115, 2014.
F. Simsek et al., “P.2.b.032 Neural correlates of emotion regulation response to negative stimuli in young women at high risk for depression,” European Neuropsychopharmacology, vol. 23, pp. S337–S338, 2013.
O. Kitis et al., “Reduced left uncinate fasciculus fractional anisotropy in deficit schizophrenia but not in non‐deficit schizophrenia,” Psychiatry and Clinical Neurosciences, vol. 66, no. 1, pp. 34–43, 2012.
K. Oğuz, “Bilgisayar Oyunlarında Kalabalıkların Hızlı Çizimi,” Anadolu Üniversitesi Bilim ve Teknoloji Dergisi A - Uygulamalı Bilimler ve Mühendislik, vol. 11, no. 1, pp. 23–33, 2010.
M. S. Unluturk, K. Oguz, and C. Atay, “A Comparison of Neural Networks for Real-time Emotionrecognition from Speech Signals A Comparison of Neural Networks for Real-time Emotionrecognition from Speech Signals,” WSEAS Trans. Sig. Proc., vol. 5, no. 3, pp. 116–125, Mar. 2009.
M. S. Unluturk, K. Oguz, and C. Atay, “Emotion Recognition Using Neural Networks,” in Proceedings of the 10th WSEAS International Conference on Neural Networks, Prague, Czech Republic, 2009, pp. 82–85.