Assoc. Prof. Dr. Gözde ULUTAGAY

Assoc. Prof. Dr. Gözde ULUTAGAY Dept. of Industrial Engineering Faculty of Engineering, Tel:+90 (232) 2464949/422 Izmir University, gozde.ulutagay@ gmail.com Gursel Aksel Blv. No:14 gozde.ulutagay@ izmir.edu.tr 35350 Uckuyular, Izmir, Turkey EDUCATION Ph.D. : Dokuz Eylul University, Sept. 2006 to July 2009 Dept. of Statistics M.S.: Ege University, Dept. of Statistics Sept. 2001 to Dec. 2004 B.S.: Ege University, Dept. of Statistics Sept. 1997 to June 2001 Middle & High School: Izmir Private Turkish College Sept.1990 to June 1997 EXPERIENCE Associate Professor Dept. of Industrial Engineering, Izmir University Nov. 2013 to present Visiting Professor Dept. of Computer Science, University of Texas at El Paso, USA June 2011 to Sept. 2011 Assistant Professor Dept. of Industrial Engineering, Izmir University Sept. 2009 to Nov. 2013 Vice Dean Faculty of Engineering, Izmir University Feb. 2010 to present Vice Director Graduate School of Engineering & Science, Izmir University Sept. 2009 to present Research Assistant (TUBITAK, Project No.106T312) Dept. of Statistics, Dokuz Eylül University Jan. 2007 to Dec.2008 1

Teaching & Research Assistant Dept. of Statistics, Faculty of Science, Ege University Dec. 2001 to Aug. 2006 ACCOMPLISHMENTS Ph.D. Dissertation: Construction and Analysis of Clustering Algorithms Based on Fuzzy Relations and Their Applications to EEG Data Dokuz Eylül University, Dept. of Statistics Sept. 2006 to July 2009 M.S. Thesis: Fuzzy c-means clustering algorithm and its applications Ege University, Dept. of Statistics Sept. 2002 to Dec. 2004 B.S. Thesis: Statistical Quality Control and an Application in an Enterprise Ege University, Dept. of Statistics Sept. 2000 to June 2001 INTERESTS: o Statistics o Fuzzy Clustering Problems o Data Mining o Artificial Intelligence o Soft Computing o Decision Making and Optimization o Fuzzy Inference Systems COMPUTER SKILLS C / C++, Visual Basic, MS Access, Minitab, SPSS/Clementine, R Programming Language, DrScheme. RESEARCH PROJECTS / GRANTS 1. Design and Performance Analysis of Neighborhood Based Fuzzy Clustering Algorithms for Large Databases Funded by TUBITAK (No.111T273/COST Action COST-IC 1203) (October 2011 October 2014, PI) 2. Design and Modeling of Fuzzy Expert System for the Diagnosis and Treatment of the Thyroid Disease Funded by TWAS (No.10-183 RG/ITC/AS_C) (Sept. 2011 March 2012, PI) 2

3. Construction and Analysis of Clustering Algorithms Based on Fuzzy Neighborhood Relations Funded by TUBITAK (No.106T312) (Jan. 2007 Dec. 2008, Research Assistant) 4. "Fuzzy c-means Cluster Analysis and Its Applications Funded by Ege University Research Fund Accountancy (No.2002-FEN-043) (Dec. 2002 Dec. 2004, Research Assistant) HONORS & AWARDS PhD Honor by Administrative Board of Graduate of School of Natural and Applied Sciences, Dokuz Eylul University, 2011. Listing in Marquis Who s Who in Science& Engineering, 2010, 2012, 2014 The Best Method Approach and Application Award, The 2 nd Brain Biophysics Workshop with Young Scientists: Multidisciplinary Approach in Brain Asymmetry and Cognitive, Dokuz Eylül University, İzmir, Feb. 21-23, 2008. Ranked Second in Department of Statistics, June 2001. LANGUAGES English, reading & writing at perfect level (TOEFL CBT 253) PUBLICATIONS 1. Senvar, O; Ulutagay, G.; Turanoglu-Bekar, E., Long Term Forecasting Modeling For Oil Consumption of Turkey via Adaptive Neuro Fuzzy Inference System; Journal of Multi-Valued Logic & Soft Computing (2015), (in press) 2. Ulutagay G., Ecer F, Nasibov E.N., Performance Evaluation Of Industrial Enterprises via Fuzzy Inference System Approach: A Case Study, Soft Computing 19 (2015) 449-458. (SCI) 3. Ulutagay G., Nasibov E.N., On Fuzzy Neighborhood Based Clustering Algorithm With Low Complexity, Iranian Journal of Fuzzy Systems, 10 (2013) No.3, pp.1-20. (SCI). 4. Allahviranloo, T.; Yager, R., Abbasbandy, S., Ulutagay G., Ranking Fuzzy Numbers and Its Extensions, Mathematical Problems in Engineering, (2013) DOI: 10.1155/2013/468635 (SCI-editorial) 3

5. Ulutagay G., Nasibov E.N., Fuzzy and Crisp Clustering Methods Based on The Neighborhood Concept: A Comprehensive Review, Journal of Intelligent & Fuzzy Systems, 10 (2012), No.3, pp.1-20 (SCI). 6. Ulutagay G., Nasibov E.N., Improving FJP Algorithm for Fuzzy Neighborhood Based Clustering, Iranian Journal of Fuzzy Systems (in review) (SCI). 7. Ecer F., Ulutagay G., Nasibov E.N., Does Foreign Ownership Affect Financial Performance? An Industrial Approach, Middle Eastern Finance and Economics, 14 (2011), pp.152-166. 8. Ulutagay G., Nasibov E.N., Influence of Transitive Closure Complexity in FJP-Based Clustering Algorithms, Turkish Journal of Fuzzy Systems, 1 (2010), No:1, pp.3-20. 9. Nasibov, E.N., Özgören, M., Ulutagay, G., Öniz, A., & Kocaaslan S., On the Analysis of BIS Stage Epochs via Fuzzy Clustering, Biomedizinische Technik/Biomedical Engineering, 55 (2010) No.3, pp. 147-153 (SCI). 10. Nasibov E.N, Ulutagay G., Comparative Clustering Analysis of Bispectral Index Series of Brain Activity, Expert Systems with Applications 37 (2010) No.3, pp. 2495-2504 (SCI). 11. Nasibov E.N, Ulutagay G., Robustness of Density-Based Clustering Methods with Various Neighborhood Relations, Fuzzy Sets and Systems, 160 (2009) 3601-3615 (SCI). 12. Ulutagay G., Nasibov E.N., Detection of BIS stage levels via fuzzy clustering approach, 14th National Biomedical Engineering Meeting (BIYOMUT) doi: 10.1109/BIYOMUT.2009.5130356, pp. 419-422 (SCI). 13. Nasibov, E.N., Özgören, M., Ulutagay, G., Öniz, A., & Kocaaslan, S., Comparison of FCM and FN-DBSCAN clustering methods in the analysis of BIS. The Applied Brain Biophysics. (2009) 233-250, ISBN 978-975-441-259-8 (book chapter) (in Turkish). 14. Nasibov E.N., Ulutagay G., A New Unsupervised Approach for Fuzzy Clustering, Fuzzy Sets and Systems, 158 (2007) 2118-2133 (SCI). 15. Nasibov E.N., Ulutagay G., On the Fuzzy Joint Points Method for Fuzzy Clustering Problem, Automatic Control and Computer Sciences, 40 (2006), No:5, pp.23-31 (SCI). 16. Nasibov E.N., Ulutagay G., O metode nechetkix svyazannix tochek dlya nechetkoi klasterizatsii, Avtomatika i Vychislitel'naya Tekhnika, 40 (2006), No:5, pp.33-44 (in Russian). 4

17. Şenol, S., Ulutagay, G., Logistic Regression Analysis to Determine The Factors That Affect Green Card Usage For Health Services, Journal of Faculty of Science, 29 (2006), pp. 18-26. 18. Nasibov E.N., Ulutagay G., A New Approach to Clustering Problem Using the Fuzzy Joint Points Method, Automatic Control and Computer Sciences, 39 (2005), No:6, pp.8-17 (SCI). 19. Nasibov E.N., Ulutagay G., Novii podxok k probleme klasterizatsii c ispolzovaniem metoda nechetkix svyazannix tochek, Avtomatika i Vychislitel'naya Tekhnika, 39 (2005), No:6, pp.11-21 (in Russian). 20. Nasibov E.N., Şenol Ş., Ulutagay G., A Visual Processing System for Fuzzy Clustering, IJSIT Lecture Notes of 1 st Int. Conf. On Informatics, 2004 (1), No:2, pp.123-128. 21. Şenol, S., Ulutagay, G., Endüstri İşletmelerinin Toplam Kalite Yönetimi Çalışmalarında İstatistik Bilimi ve İstatistikçinin Yeri ve Öneminin Sorgulanmasi Üzerine Bir Çalışma, İstatistik Araştırma Dergisi (özel sayı), 2003 (2), No:2, pp.37-45 (in Turkish). BOOKS 1. Ulutagay G., Nasibov E.N., Fuzzy Neighborhood-Based Clustering: with Recent Theory and Applications, Lap Lambert Academic Publishing, Germany, 2011, 144 pages, ISBN: 978-3-8465-4025-1. 2. Ulutagay G., Kreinovich V., Density-Based Fuzzy Clustering as a First Step to Learning Rules: Challenges and Solutions, Proceedings of WCSC 2013, December 16-18, San Antonio, Texas, USA, (Advance Trends in Soft Computing, Volume 312, 2014, pp 357-372, Springer, DOI: 10.1007/978-3-319-03674-8_34) (book chapter) 3. Nasibov, E.N., Özgören, M., Ulutagay, G., Öniz, A., & Kocaaslan, S., Uygulamalı Beyin Biyofiziği ve Multidisipliner Yaklaşım. BIS verilerinin analizinde FCM ve FN- DBSCAN kümeleme yöntemlerinin karşılaştırılması, (2009) 233-250, ISBN 978-975- 441-259-8, (book chapter) PRESENTATIONS 1. Ulutagay G., Kreinovich V., Density-Based Fuzzy Clustering as a First Step to Learning Rules: Challenges and Solutions, Proceedings of WCSC 2013, December 16-18, San Antonio, Texas, USA, (Advance Trends in Soft Computing, Volume 312, 2014, pp 357-372, Springer, DOI: 10.1007/978-3-319-03674-8_34) 5

2. Ulutagay G., Kantarcı S., Classification of LR Fuzzy Data Using OWA Distance, 3rd Fuzzy Systems Symposium 2013, 174-180, October 24-26, İstanbul. 3. Ulutagay G., Nasibov E.N., CxK-Nearest Neighbor Linkage Approach via OWA Distance, 7th Int. Conference on Soft Computing, Computing with Words and Perceptions in System Analysis, Decision and Control, pp. 203-211, September, 2-3 2013, Izmir, Turkey. 4. Kantarcı S., Turanoğlu-Bekar E., Ulutagay G., A Comparison of Decision Tree Algorithms for the Classification of Thyroid Disease, 7th Int. Conference on Soft Computing, Computing with Words and Perceptions in System Analysis, Decision and Control, pp. 141-148, September 2-3, 2013, Izmir, Turkey. 5. Şenvar Ö., Ulutagay G., Turanoğlu-Bekar E., Forecasting oil consumption of Turkey using Adaptive Neuro-Fuzzy Inference System (ANFIS), RACR 2013, Intelligent Systems and Decision Making for Risk Analysis and Crisis Response- Huang & Kahraman (eds), 27-29 August 2013, pp. 375-381, Istanbul, Turkey (Compendex Database) 6. Ulutagay G., Theoretical Examination of Clustering Structure in Fuzzy Joint Points Method, 15th IFSA World Congress and 32nd Annual Meeting of NAFIPS, 24-28 June 2013, pp.496-501, Edmonton, Canada. Doi: 10.1109/IFSA-NAFIPS.2013.6608450 7. Ulutagay G., Nasibov E.N., OWA Aggregation Based CxK-Nearest Neighbor Classification Algorithm, Proceedings of 2012 IEEE 6th International Conference Intelligent Systems (Yager, R.R., V. Sgurev and M. Hadjiski, Eds.), Vol. I, pp. 219-224, September 6-8, 2012, Sofia, Bulgaria, ISBN 978-1-4673-2782-4. 8. Ulutagay G., Nasibov E.N., A New CxK-Nearest Neighbor Linkage Approach to The Classification Problem, Proceedings of the 10th International FLINS Conference (C. Kahraman, E.K. Kerre, and F.K. Bozbura, Eds.), World Scientific Proceedings on Computer Engineering and Information Science, Vol. I, pp. 471-476, August 26-29, 2012, Istanbul, Turkey, ISBN 978-981-4417-73-0. 9. Ulutagay G., Nasibov E.N., DBSCAN-Based Clustering Methods: A Short Survey, 2 nd International Fuzzy Systems Symposium, (C. Gökçeoğlu, H.C. Aladağ, A. Akgün, Eds.), pp. 176-181, November 17-18, 2011, Ankara, Turkey. 10. Ulutagay G., Nasibov E.N., An Overview of Neighborhood-Based Clustering Methods with Fuzzy Logic, 6 th Int. Conference on Soft Computing, Computing with Words and Perceptions in System Analysis, Decision and Control, pp. 121-131, September 1-2, 2011, Antalya, Turkey. 11. Ulutagay G., Ecer F., Nasibov E.N., Performance Analysis of Industrial Enterprises via Data Mining Approach, Proceedings of the 2 nd International Symposium on Computing 6

in Science & Engineering (ISCSE-2011), pp. 985-991, June 1-4, 2011, Kuşadası, Turkey. 12. Ecer F., Ulutagay G., Nasibov E.N., Foreign Ownership and Financial Performance Relationship: Evidence from Turkey, Anadolu International Conference in Economics, Congress, pp.1-15, June 15-17, 2011, Eskişehir, Turkey. 13. Ecer F., Ulutagay G., Nasibov E.N., Realistic Modeling of 500 Major Industrial Organizations in Turkey, 12 th Econometrics, Operations Research and Statistics Congress, pp.198-202, May 26-29, 2011, Pamukkale, Turkey. 14. Ulutagay G., Nasibov E.N., A Fuzzy Inference System for Thyroid Disease Diagnosis, Proceedings of the 1st International Symposium on Computing in Science& Engineering (ISCSE-2010), pp. 1159-1165, June 1-3, 2010, Kuşadası, Turkey. 15. Nasibov E.N., Ulutagay G., MFJP: A New Modified FJP Algorithm with Low Complexity, Proceedings of the 1st International Fuzzy Systems Symposium (T. Dereli, A. Baykasoglu, I.B. Turksen, Eds.), pp. 444-450, November 1-2, 2009, Ankara, Turkey 16. Ulutagay G., Nasibov E.N., Detection of BIS stage levels via fuzzy clustering approach, IEEE Biomedical Engineering Meeting (BIYOMUT), 2009, IEEE Xplore Digital Library, doi: 10.1109/BIYOMUT.2009.5130356, pp. 1-4. 17. Nasibov E., Ulutagay G., FN-DBSCAN: A Novel Density-Based Clustering Method with Fuzzy Neighborhood Relations, Proceedings of the 8 th International Conference on Application of Fuzzy Systems and Soft Computing (ICAFS-2008), pp.101-110, September 1-3, 2008, Helsinki, Finland. 18. Ulutagay G., Nasibov E., A New Clustering Approach to EEG Data for BIS Measurements, Proceedings of the 8 th International Conference on Application of Fuzzy Systems and Soft Computing (ICAFS-2008), pp.111-118, September 1-3, 2008, Helsinki, Finland. 19. Ulutagay G., Nasibov E., Density-Based Clustering Methods with EEG Data, 2 nd Brain Biophysics Workshop with Young Scientists: Brain Asymmetry and Multidisicplinary Approach in Cognitive Measures, p.55, February 21-23, 2008 (in Turkish). 20. Nasibov E., Özgören M., Ulutagay G., Öniz A., Kocaaslan S., BIS Monitoring Analysis of Sleep Data via Clustering, 2 nd Brain Biophysics Workshop with Young Scientists: Brain Asymmetry and Multidisicplinary Approach in Cognitive Measures, p.56, February 21-23, 2008 (in Turkish). 21. Nasibov E.N., Ulutagay G., On Cluster Analysis Based on Fuzzy Relations Between Spatial Data, Proc. of the 5 th EUSFLAT Conference, pp.59-62, September 11-14, 2007, Ostrava, Czech Republic. 7

22. Nasibov E.N., Ulutagay G., DBSCAN and FJP based neighborhood relations in clustering: a comparative analysis, 4 th Int. Conference on Soft Computing, Computing with Words and Perceptions in System Analysis, Decision and Control, pp.209-218, August 27-28, 2007, Antalya, Turkey. 23. Nasibov E.N., Ulutagay G., Fuzzy Logic Approach in Spatial Data Analysis (Uzaysal Veri Analizinde Bulanık Mantık Yaklaşımı), Operations Research and Industrial Engineering Congress (YA/EM'07), pp.1225-1230, July 02-04, 2007, İzmir, Turkey (in Turkish). 24. Nasibov E.N., Ulutagay G., Cluster Analysis Based on Fuzzy Relations (Noktalar Arası Bulanık İlişkilere Dayalı Kümeleme Analizi)i, 5 th Statistics Congress, pp.557-562, May 20-24, 2007, Antalya, Turkey (in Turkish). 25. Ulutagay G., Clustering Methods and Using Variable Length Segments in EEG Analysis (Kümeleme yöntemleri ve EEG analizinde değişken uzunluklu segmentlerin kullanımı), 1 st Brain Biophysics Workshop with Young Scientists, pp. 17, May 9-11, 2007, İzmir, Turkey (in Turkish). 26. Nasibov E.N., Ulutagay G., Optimal Adjustment of The Parameters of Noise-Resistant Fuzzy Joint Points Clustering Method, 7 th Int. Conf. On Application of Fuzzy Systems and Soft Computing (ICAFS'06), pp.80-86, September 13-14, 2006, Siegen, Germany. 27. Nasibov E.N., Ulutagay G., A New Fuzzy Joint Points Criteria for Cluster Validity, Int. Conf. on Modelling and Simulation (AMSE'06), pp. 625-629, August 28-39, 2006, Konya, Turkey. 28. Nasibov E.N., Ulutagay G., A Novel Fuzzy Joint Points Algorithm to Clusteirng Apporach, (Kümeleme Analizinde Sapanlara Dayanıklı Yeni Bir Bulanık Birleşik Noktalar Algoritması), Operations Research and Industrial Engineering Congress (YA/EM'06), pp. 429-432, July 1-3, 2006, Kocaeli, Turkey (in Turkish). 29. Nasibov E.N., Ulutagay G., Program Tools for Fuzzy Clustering Analysis, Inf. Tech. and Telecomm. in Education and Science, pp.195-197. May 20-26, 2006, Antalya, Turkey. 30. Nasibov E.N., Ulutagay G., FJP: A New Hierarchical Method For Fuzzy Clustering, 3 rd Int. Conference on Soft Computing, Computing with Words and Perceptions in System Analysis, Decision and Control, pp.212-220, September 1-2, 2005, Antalya, Turkey. 31. Nasibov E.N., Ulutagay G., Evaluation of Fuzzy Joint Points Algorithm for Unsupervised Clustering, 3 rd Int. Conference on Soft Computing, Computing with Words and Perceptions in System Analysis, Decision and Control, pp.203-211, September 1-2, 2005, Antalya, Turkey. 8

32. Nasibov E.N., Şenol Ş., Ulutagay G., A Visual Interactive System With Several Fuzzy Clustering Techniques, (Çeşitli bulanık kümeleme teknikleriyle bir visual işlem sistemi), 4 th İstatistik Kongresi, pp.305-310, May 8-12, 2005, Antalya, Turkey (in Turkish). 33. Nasibov E.N., Şenol Ş., Ulutagay G., A visual processing system for fuzzy clustering, Int. Conf. on Informatics, September 1-4, 2004, Çeşme, Turkey. 34. Şenol, Ş., Ulutagay, G., A Study to Determine Work and Family Interactions of Working Women (Çalışan kadınların iş ve aile içi etkileşimlerinin belirlenmesi üzerine bir araştırma), Statistics Ressearch Symposium, December 10-12, 2003, Ankara, Turkey (in Turkish). 35. Şenol, Ş., Ulutagay, G., A Study to Determine The Place of Statistics as a Science and Statistician in Total Quality Management Studies of Industry (Endüstri işletmelerinin Toplam Kalite Yönetimi çalışmalarında İstatistik bilimi ve İstatistikçinin yeri ve öneminin sorgulanması üzerine bir çalışma), Statistics Ressearch Symposium, December 9-11, 2002, Ankara, Turkey (in Turkish). Seminars An Overview of Fuzzy and Crisp Clustering Algorithms, July 8, 2011, University of Texas at El Paso. Fuzzy and Crisp Clustering Algorithms, May 20, 2010, Izmir University, Seminar Days, Mathematics and Computer Science. Modified FJP Algorithm and Its Worst Time Complexity, Dokuz Eylül University Statistics Department, İzmir, (2009). FJP: A New Approach to Fuzzy Clustering Problem, Dokuz Eylül University Statistics Department, İzmir, (2007). Çeşitli Bulanık Kümeleme Teknikleri ile Bir Visual Işlem Sistemi, Ege Üniversitesi İstatistik Bölümü, İzmir (2005). On Fuzzy c-means Clustering Algorithm, Ege University Statistics Department, İzmir (2004). Logistic Regression Analysis to Determine the Factors that Affect Green Card Usage for Health Services, Ege University Statistics Department, İzmir (2004). LIST OF JOURNALS SERVED AS A REFEREE - Soft Computing (SCI) - Applied Soft Computing (SCI) 9

- Turkish Journal of Electrical Engineering & Computer Sciences (SCI) - Fuzzy Sets and Systems (SCI) - Computational Intelligence in Decision Making (SCI) - Computer Standards & Interfaces (SCI) - Information Sciences (SCI) - Textile Research Journal (SCI) - Turkish Journal of Fuzzy Systems LIST OF JOURNALS SERVED AS AN EDITOR - Mathematical Problems in Engineering (SCI) (Guest Editor) - International Journal of Industrial Mathematics 10