Pejman Khadivi

Department of Computer Science
Seattle University
Seattle, WA 98122
Google Scholar Profile
LinkedIn Profile

Home Research Teaching Virtual Lab Tools


Pejman Khadivi is an Assistant Professor of Computer Science at Seattle University. Dr. Khadivi's primary research interests are in the field of artificial intelligence, machine learning, and data analytics using large scale datasets, with emphasis time series analytics, deep learning, and information theory.


Ph.D. in Computer Science, Virginia Tech (2016)
Ph.D. in Electrical Engineering, Isfahan University of Technology (2006)
M.Sc. in Computer Engineering, Isfahan University of Technology (2000)
B.Sc. in Computer Engineering, Isfahan University of Technology (1998)

Recent Publications

  • K Chitsaz, M Hajabdollahi, P Khadivi, S Samavi, N Karimi, S Shirani, "Use of Frequency Domain for Complexity Reduction of Convolutional Neural Networks", Pattern Recognition. ICPR International Workshops and Challenges: Virtual Event, Proceedings, Part IV, 2021.
  • P.Khadivi, "Bag of Symbols for Time Series Distance Measurement and Applications", Published in Proc. of IEEE BigData, 2020.
  • M.Bagheri, M.Mohrekesh, N.Karimi, S.Samavi, S.Shirani, P.Khadivi, "Image Watermarking with Region of Interest Determination Using Deep Neural Networks", Proceedings of IEEE ICMLA, 2020.
  • H.Zarrabi, A.Emami, P.Khadivi, N.Karimi, S.Samavi, "BlessMark: a blind diagnostically-lossless watermarking framework for medical applications based on deep neural networks", Accepted in Multimedia Tools and Applications Journal.
  • M.Hajabdollahi, R.Esfandiarpoor, P.Khadivi, S.M.R.Soroushmehr, N.Karimi, S.Samavi, "Simplification of neural networks for skin lesion image segmentationusing color channel pruning", Computerized Medical Imaging and Graphics Journal, 2020.
  • M.Momtazpour, P.Khadivi, "Sales Promotions and Resource Optimization in Sustainable Fashion", IEEE Artificial Intelligence for Industry (AI4I'19), September 2019.
  • P.Khadivi, "Ants, Men, and the Elephant: An Unsupervised Collaboration for 2-D Shape Discovery",Proc. of ACM Collective Intelligence Conference, June 2019.
  • M.Hajabdollahi, R.Esfandiarpoor, P.Khadivi, SMR.Soroushmehr, N.Karimi, K.Najarian, S.Samavi, "Segmentation of bleeding regions in wireless capsule endoscopy for detection of informative frames", Biomedical Signal Processing and Control, 2019.
  • P.Khadivi, R.Tandon, N.Ramakrishnan, "Flow of information in Feed-forward deep neural networks", IEEE 17th International Conference on Cognitive Informatics & Cognitive Computing (ICCI* CC), July 2018.


This is a personal WEB site developed and maintained by an individual and not by Seattle University. The content and link(s) provided on this site do not represent or reflect the view(s) of Seattle University. The individual who authored this site is solely responsible for the site's content. This site and its author are subject to applicable University policies including the Computer Acceptable Use Policy (