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Published in International Conference on Pattern Recognition (ICPR), 2014
We propose a method for classifying human-object interactions in videos by combining motion and appearance information.
Recommended citation: Bogun, I., Khan, H., Chen, J., & Ribeiro, E. (2014). "Interaction recognition using sparse portraits." International Conference on Pattern Recognition (ICPR). http://haidark.github.io/files/inter_rec.pdf
Published in American Epilepsy Society Annual Meeting 2015, 2015
In this work, we demonstrate a seizure prediction approach using a collection of one-class SVM as anomaly detectors.
Recommended citation: Khan, Haidar. (2017). "Seizure prediction using anomaly detection." American Epilepsy Society Annual Meeting 2015. Poster. http://haidark.github.io/files/aes_poster.pdf
Published in IEEE Transactions on Biomedical Engineering, 2017
We apply convolutional neural networks to wavelet tensors for focal onset seizure prediction using a change point detection algorithm to set the prediction horizon.
Recommended citation: Khan, H., Marcuse, L., Fields, M., Swann, K., & Yener, B. (2017). "Focal onset seizure prediction using convolutional networks." IEEE Transactions on Biomedical Engineering. http://haidark.github.io/files/seizure_pred_2017.pdf
Published in Advances in Neural Information Processes (NeurIPS), 2018
A novel approach for end-to-end time series classification using neural networks is presented in this work. The wavelet transform is used to learn the optimal spectral decomposition of the time series for any classification task.
Recommended citation: Khan, H., & Yener B. (2018). "Learning filter widths of spectral decompositions using wavelets." Advances in Neural Information Processes (NeurIPS). http://haidark.github.io/files/wavelet_deconv_2018.pdf
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This workshop covered the theoretical and practical fundamentals of neural networks for engineers.
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This talk summarized my completed thesis work on change point detection and proposed new directions.
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This talk was given to a team of neurophysiologists and epileptogists at the Mount Sinai Hospital on our machine learning approach to determining the preseizure period.
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This presentation was given to a number of companies (GE Global Research, MIT Lincoln Labs, Amazon) during my job search.
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This talk was given to at the KAUST AI in Medicine conference. I was invited by Prof. Charlotte Hauser (CBRC) to present our work on epileptic seizure prediction.
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.