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Mehmet S. Aktas
Also published under:M. S. Aktas, Mehmet S. Aktaş, Mehmet Aktas, Mehmet Sıddık Aktaş
Affiliation
Computer Engineering Department, Yildiz Technical University, İstanbul, Türkiye
Topic
Deep Learning,F1 Score,Long Short-term Memory,Machine Learning Models,Software Architecture,Bidirectional Long Short-term Memory,Customer Behavior,Deep Learning Techniques,Internet Of Things,Internet Of Things Devices,Internet Of Things Systems,Language Model,Learning Algorithms,Machine Learning,Mean Absolute Percentage Error,Precision Values,Predictive Maintenance,Prototype Implementation,Question Answering,Real-time Data,Recurrent Neural Network,Remaining Useful Life,Root Mean Square Error,Sensor Data,Short-term Memory,Tokenized,Training Data,Transformer Model,Accuracy And Precision,Accuracy Metrics,Active Users,Anomaly Detection,Artificial Neural Network,Attention Mechanism,Attention Model,Autoencoder,Automatic Evaluation,Autoregressive Integrated Moving Average,BERT Model,Balanced Data,Betweenness Centrality,Bottom Of Page,Business Processes,CNN Model,Cache Hit,Cache Misses,Centrality Measures,Centrality Metrics,Cloze Test,Community Detection,
Biography
Prof. Mehmet S. Aktas is a Full Professor of Computer Engineering Department at Yildiz Technical University. Professor Aktas received his PhD and Master's degrees in Computer Science from the School of Informatics and Computing at Indiana University and Electrical Engineering and Computer Science Department at Syracuse University, respectively. Aktas completed his post-doc in the Data to Insight Center (D2I) at Indiana University. Prof. Aktas has edited a book, published a number of book chapters, sci-indexed journals and peer-reviewed conference papers. Prof. Aktas has research interests in long-term preservation and access to scientific data, large-scale data management and big data processing in cloud computing platforms. Aktas is a recipient of the prestigious Tubitak Early Career award and is an ACM and IEEE Member.