Koçhan, Necla
Kayaalp, Necla
applied statistics
biostatistics
machine learning
Doktora eğitimini Uygulamalı Matematik ve İstatistik alanında tamamlamış olup, Prof. Dr. G.Y. Tütüncü danışmanlığında “A new RNA-Seq data classifier based on quantile transformation” başlıklı tez çalışmasını gerçekleştirmiştir. Doktora sürecinde, TÜBİTAK’tan aldığı burs ile Avustralya’daki Smyth Lab’e 8 ay süreyle misafir araştırmacı olarak katılmıştır. 2020 yılında 8 ay süreyle bir COVID-19 projesinde doktora sonrası araştırmacı olarak çalışmıştır.
2024 yılından itibaren İzmir Ekonomi Üniversitesi Fen-Edebiyat Fakültesi Matematik Bölümü'nde Dr. Öğr. Üyesi olarak görev yapmaktadır. Akademik ilgi alanları arasında hesaplamalı biyoloji, istatistiksel veri analizi, bulanık mantık, sınıflandırma yöntemleri, Bayes sınıflandırıcıları, veriden öğrenme ve biyostatistik yer almaktadır.
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Dr. Necla Kayaalp Koçhan graduated from the Department of Mathematics at Izmir University of Economics in 2010, and also successfully completed a Double Major Program in Economics. In the same year, she began her master’s studies in Applied Statistics at the same university. Between 2010 and 2017, she worked as a Research Assistant in the Department of Mathematics, Faculty of Arts and Sciences at Izmir University of Economics.
She completed her Ph.D. in Applied Mathematics and Statistics under the supervision of Prof. Dr. G.Y. Tütüncü with a dissertation titled “A new RNA-Seq data classifier based on quantile transformation.” During her doctoral studies, she was awarded a scholarship by The Scientific and Technological Research Council of Turkey (TÜBİTAK) and joined the Smyth Lab in Australia for 8 months as a visiting scientist. In 2020, she worked as a postdoctoral researcher for 8 months on a COVID-19 related project.
Since 2024, she has been serving as an Assistant Professor (Dr. Öğr. Üyesi) in the Department of Mathematics, Faculty of Arts and Sciences at Izmir University of Economics. Her research interests include computational biology, statistical data analysis, fuzzy logic, classification methods, Bayesian classifiers, machine learning, and biostatistics.
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