×

Volkan Atalay

Senior Lecturer of Information Systems

Volkan Atalay is an experienced academician with a background in teaching computer science and engineering, complemented by interdisciplinary research in machine learning applications and bioinformatics. He also has substantial administrative experience.

Over the years, Dr. Atalay has designed, revised, and taught numerous computer science and engineering courses while actively engaging in academic activities and service. He regularly publishes and serves as a referee for prestigious international journals and conferences in bioinformatics and machine learning. He has led teams that developed web-based prediction systems and stand-alone software tools, with program code and data available on GitHub.

Dr. Atalay’s research focuses on developing and applying computational tools to analyze large-scale biomolecular data using various dimensionality reduction methods, machine learning algorithms, and deep learning models to solve biological problems at the systems level.

Education

  • Ph.D., Computer Science, Paris Cité University
  • M.S., Electrical and Electronics Engineering, METU
  • B.S., Electrical and Electronics Engineering, METU

Research Interests

  • Machine Learning Applications
  • Bioinformatics
  • Deep Learning
  • Data Stream Clustering

Professional Employment

  • Professor, METU, 2005-23
  • Associate Professor, METU, 1998-2005
  • Visiting Research Associate Professor, Virginia Tech, 2004-05
  • Assistant Professor, METU, 1993-98
  • Instructor, Paris Cité University, 1992-93
  • Visiting Scholar, NJIT, 1991-92

Professional/Community Affiliations

  • Associate Editor, Signal, Image and Video Processing,
  • International Society for Computational Biology (ISCB)

Courses Taught

  • ISSCM 241: Business Statistics
  • ISSCM 349: Project Management
  • INFS 247: Business Information Systems

Publications/Research Listings

'Dalkıran, A., Atakan, A., Rifaioğlu, A.S., Martin, M.J., Çetin Atalay, R., Acar, A., Doğan, T., Atalay, V. (2023). Transfer Learning for Drug-Target Interaction Prediction. ISMB/ECCB 2023 Proceedings Track Presentation and Bioinformatics. https://doi.org/10.1093/bioinformatics/btad234

Özen, S., Atalay, V. (2023). Power Consumption Forecasting by Hybrid Deep Architectures with Data Fusion. Computing and Informatics. https://www.cai.sk/ojs/index.php/cai/article/view/2023_1_126

Zubaroglu, A., Atalay, V. (2022) Online embedding and clustering of data streams. Statistical Analysis and Data Mining, https://doi.org/10.1002/sam.11590

Rifaioglu, A.S., Cetin Atalay, R., Cansen Kahraman, D., Doğan, T., Martin, M., Atalay, V. (2021). MDeePred: novel multi-channel protein featurization for deep learning-based binding affinity prediction in drug discovery. Bioinformatics https://doi.org/10.1093/bioinformatics/btaa858

Zubaroglu, A., Atalay, V. (2021) Data stream clustering: a review. Artificial Intelligence Review https://doi.org/10.1007/s10462-020-09874-x