Since 1988 Prof. Ayşın Ertüzün is with the Department of Electrical and Electronic Engineering, Boğaziçi University where she is currently a full professor. Dr. Ertüzün’s research activities focus on statistical signal processing and she specifically works on estimation, detection and object tracking problems. She is also interested in texture analysis and pattern recognition. She is affiliated with the Boğaziçi Signal and Image Laboratory (BUSIM) and Intelligent Systems Laboratory (ISL). She has authored and co-authored scientific papers in journals and conference proceedings on topics such as particle filters and Bayesian signal processing, alpha stable distributions, independent component analysis, texture defect detection and pattern recognition, application of statistical methods to defect detection problem, deconvolution and source separation, wind speed prediction, image denoising, 2-D lattice filers, adaptive signal processing, higher order statistics, wavelets and their applications. She is a member of IEEE Signal Processing and Communication Societies, IAPR –International Association of Pattern Recognition, IEICE – The Institute of Electronics, Information and Communication Engineers and TOTIAD – Turkish Pattern Recognition and Image Processing Society and on the editorial board of “Signal Processing” journal. She was the  vice rector in charge of research between November 2016 and January 2021.

RESEARCH TOPICS FOR STUDENTS

• Textile Defect Detection using Signal Processing and Artificial Intelligence Methods
• Anomaly Detection using Signal Processing and Artificial Intelligence Methods
• Signal Processing and Artificial Intelligence Methods for Smart Agriculture
  • Plant Detection and Classification 
  • Plant Health Assesment
  • Field Analysis
  • Yield Estimation
• Signal Processing and Artificail Intelligence Methods for Power Estimation for Renewable Energy Systems
  • Wind Speed Prediction
  • Solar Radiation Prediction 
• Robust Distributed Detection and Decision Fusion_ Bayesian Approach
• Object Tracking under Occlusion using Particle Flters
• Multiple Object Tracking by PHD filters