Pejman Khadivi

Contact
khadivip@seattleu.edu
Department of Computer Science
Seattle University
Seattle, WA 98122
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Research

Dr. Khadivi's primary research interests are in the field of artificial intelligence, machine learning, and data analytics using large scale datasets, with emphasis on time series analytics, which is considered as a critical component in various domains including forecasting, cyber-physical systems, anomaly detection, and reliable system design.

In cyber-physical systems, beside forecasting and prediction tasks, machine learning techniques can be used in other applications such as anomaly detection, smart controller design, and surveillance systems. Furthermore, one of the important issues with machine learning and time series analytics is the existence of noise in datasets. Machine learning algorithms are sensitive to noise and hence, denosing is a crucial step to perform before using any machine learning algorithm. Current research problems that I am working on them are as follows:

  • Real time techniques for time series denoising using information theory and deep learning
  • Anomaly detection in cyber-physical systems in order to perform fault detection and fault location with the aim of reliability improvement
  • Using open source datasets for forecasting applications in health science and tourism industry
  • Wikipedia usage behavior modeling

Selected 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”, Proceedings of IEEE Artificial Intelligence for Industry (AI4I’19), 2019.

  • P.Khadivi, “Ants, Men, and the Elephant: An Unsupervised Collaboration for 2-D Shape Discovery”, Proceedings of ACM Collective Intelligence Conference, 2019.

  •  M.Hajabdollahi, R.Esfandiarpoor, P.Khadivi, S.M.R.Soroushmehr, N.Karimi,K.Najarian, S.Samavi, “Segmentation of bleeding regions in wireless capsule endoscopy for detection of informative frames”, Journal of Biomedical Signal Processing and Control, Vol. 53, 2019.

  •  P.Khadivi, R.Tandon, N.Ramakrishnan, “Flow of Information in Feed-Forward Denoising Neural Networks”, Proceedings of 17th IEEE International Conference on Cognitive Informatics and Cognitive Computing, 2018.

  • P.Khadivi, R.Tandon, N.Ramakrishnan, “Hierarchical Quantized Online Denoising for Discrete Noisy Time Series”, Ready for Submitted to IEEE Transactions on Signal Processing, 2017.

  • P.Khadivi, R.Tandon, N.Ramakrishnan, “Flow of Information in Feed-Forward Deep Neural Networks”, Ready for Submitted to IEEE International Symposium on Information Theory, 2017.

  • P.Khadivi, N.Ramakrishnan, “Wikipedia in Tourism Industry: Forecasting and Usage Behavior”, Accepted in 28th Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-16), Feb. 2016.

  • P.Khadivi, P.Chakraborty, R.Tandon, N.Ramakrishnan, “Time Series Forecasting via Noisy Channel Reversal”, Proceeding of the IEEE International Workshop on Machine Learning for Signal Processing, 2015.

  • P.Khadivi, R.Tandon, N.Ramakrishnan, “Online Denoising of Discrete Noisy Data”, Proceedings of the IEEE International Symposium on Information Theory (ISIT'15), June 2015.

  • P.Chakraborty, P.Khadivi, et al. “Forecasting a Moving Target: Ensemble Models for ILI Case Count Predictions”, Proceedings of the SIAM International Conference on Data Mining (SDM 2014), 2014.

  • M.Zarifneshat, P.Khadivi, H.Saidi, “A Semi-Localized Algorithm for Cluster Head Selection for Target Tracking in Grid Wireless Sensor Network”, Journal of Ad Hoc & Sensor Wireless Networks, Vol. 25, Issue 3/4, p263-287, 2015.

  • M.Zarifneshat, P.Khadivi, “Using mobile node speed changes for movement direction change prediction in a realistic category of mobility models”, Journal of Network and Computer Applications, Vol. 36, No. 3, , Pages 1078–1090, May 2013.

  • M.Houshmand, S.M.R.Soroushmehr, P.Khadivi, S.Samavi, S.Shirani, “Visual Sensor Network Lifetime Maximization by Prioritized Scheduling of Nodes”, Journal of Networks and Computer Applications, Vol. 36, No. 1, pp. 409-419, Jan. 2013.

  • Z.Alavikia, P.Khadivi, M.R.Hashemi, “A Model for QoS-aware Wireless Communication in Hospitals”, Journal of Medical Signals and Sensors, Vol 2, No1, pp 15-23, January 2012.

  • S.Poursheikhali, M.Mahdavi, P.Khadivi, “Energy-aware node placement to reach coverage in hybrid wireless sensor networks”, Proceedings of 17th Asia-Pacific Conference on Communications, 2011.

  • P.Khadivi, “Adaptive Distance Estimation and Localization in Wireless Networks with Triangle and Ptolemy Inequalities”, Proc. of IEEE Int. Conference on Advanced Networks and Telecommunication Systems, 2010.

  • A. Ehyaei, M. Hashemi, P.Khadivi, “Using Relay Networks to Increase Life Time in Wireless Body Area Sensor Networks”, Proceedings of 10th IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM 2009), Greece, 2009.

  • M.Sheikh Zefreh, A.Fouladgar, F.Eskandari, P.Khadivi, “Transmission Capacity of Underwater Sensor Networks: A Case for Fixed Distance”, Proceedings of Second International Conference on Sensor Technologies and Applications (SENSORCOMM '08), PP. 669-704, France, 2008.

  •  P.Khadivi, T.D.Todd, S.Samavi, H. Saidi, D.Zhao, “Mobile Ad Hoc Relaying for Upward Vertical Handoff in Hybrid WLAN/Cellular Systems”, Journal of Ad Hoc Networks, Vol. 6, No. 2, pp 307-324, April 2008.

  • P.Khadivi, S.Samavi, T.D.Todd, "Multi-constraint QoS routing using a new single mixed metrics", Journal of Network and Computer Applications, Vol. 31, Issue 4, pp 656-676, Nov. 2008.

  • P.Khadivi, S.Samavi, H. Saidi, T.D.Todd, D.Zhao, “Dropping Rate Reduction in Hybrid WLAN/Cellular Systems by Mobile Ad Hoc Relaying”, Wireless Personal Communications, Springer, pp 515-542, 2006.

  • P.Khadivi, S.Samavi, H.Saidi, T.D.Todd, “Handoff in Hybrid Wireless Networks based on Self-Organization”, Proceedings of IEEE International Conference on Communications (ICC), June 2006.

  • P.Khadivi, S.Samavi, T.D.Todd, H.Saidi, “Multi-Constraint QoS Routing Using a New Single Mixed Metric”, Proceedings of IEEE International Conference on Communications (ICC), June 2004.

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