Journal Publications
1. A. Akintayo and S. Sarkar, Hierarchical Symbolic Dynamic Filtering of streaming Non-stationary Time Series Data, Elsevier Signal Processing, vol. 151, pp. 76-88, 2018.
2. C. Liu, A. Akintayo, Z. Jiang, G. Henze and S. Sarkar, Multivariate Exploration of Non-intrusive Load Monitoring via Spatiotemporal Pattern Network, Applied Energy, vol. 211, pp. 1106-1122, 2018.
3. Z. Jiang, C. Liu, A. Akintayo, G. Henze and S. Sarkar, Energy Prediction using Spatio-Temporal Pattern Networks, Applied Energy, vol. 206, pp 1022-1039, 2017.
4. K.G. Lore, A. Akintayo & S,Sarkar, LLNet: A Deep Autoencoder Approach to Natural Low Light Image Enhancement, Elsevier Special Issue Journal of Pattern Recognition, vol. 61, pp.650-662, 2017
5. A. Akintayo, K.G. Lore, Soumalya. Sarkar and S. Sarkar, Prognostics of combustion instabilities from Hi-speed flame videos using a deep convolutional selective auto encoder, International Journal of Prognostics and Health Management (Special Issue), vol. 7 no. 023, pp.1-14, 2016
Workshops and Conferences
1. V. Chawla, H. S. Naik, A. Akintayo, D. Hayes, P. Schnable, B. Ganapathysubramanian and S. Sarkar, A-Bayesian Network approach to County-level Corn yield prediction using historical data and expert knowledge, Knowledge discovery and Data Mining Workshop on Data Science for Food, Energy and Water (KDD- DSFEW), pp. 1-8, Aug, 2016.
2. A. Akintayo, K.G. Lore, Soumalya Sarkar and S. Sarkar, Prognostics of combustion instabilities from Hi-speed flame videos using a deep convolutional selective auto encoder Prognostics and Health Management (PHM) conference, Denver Colorado, 2016
3. A. Akintayo, N.Lee, V.Chawla, C. Marett, M. Mullaney, A. K. Singh, A. Singh, G. Tylka, B. Ganapathysubramanian and S. Sarkar, An end-to-end convolutional selective auto encoder approach to Soybean Cyst Nematode SCN eggs detection, Knowledge discovery and Data Mining Workshop on Data Science for Food, Energy and Water (KDD- DSFEW), pp. 1-8, Aug, 2016.
4. A. Akintayo, K.G. Lore, Soumalya Sarkar and S. Sarkar, Early Detection of Combustion Instabilities using Deep Convolutional Selective Autoencoders of Hi-speed Flame Video 1st Knowledge Discovery and Data Mining Workshop on Prognostics and Health Management (KDD - PHM), pp. 1-10, Aug, 2016
5. A. Akintayo, S. Sarkar, A Symbolic Dynamic Filtering Approach to Unsupervised Hierarchical Feature Extraction from Time-Series Data, Proceedings of the American Control Conference, Chicago, 2015
Book Chapter
1. S. Sarkar, Z. Jiang, A. Akintayo, K. Krishnamurthy & A. Tewari, Probabilistic Graphical Model of Distributed Cyber-Physical Systems in Cyber-Physical Systems: Foundations, Applications and Principles ,Elsevier Publication, 2016
1. A. Akintayo and S. Sarkar, Hierarchical Symbolic Dynamic Filtering of streaming Non-stationary Time Series Data, Elsevier Signal Processing, vol. 151, pp. 76-88, 2018.
2. C. Liu, A. Akintayo, Z. Jiang, G. Henze and S. Sarkar, Multivariate Exploration of Non-intrusive Load Monitoring via Spatiotemporal Pattern Network, Applied Energy, vol. 211, pp. 1106-1122, 2018.
3. Z. Jiang, C. Liu, A. Akintayo, G. Henze and S. Sarkar, Energy Prediction using Spatio-Temporal Pattern Networks, Applied Energy, vol. 206, pp 1022-1039, 2017.
4. K.G. Lore, A. Akintayo & S,Sarkar, LLNet: A Deep Autoencoder Approach to Natural Low Light Image Enhancement, Elsevier Special Issue Journal of Pattern Recognition, vol. 61, pp.650-662, 2017
5. A. Akintayo, K.G. Lore, Soumalya. Sarkar and S. Sarkar, Prognostics of combustion instabilities from Hi-speed flame videos using a deep convolutional selective auto encoder, International Journal of Prognostics and Health Management (Special Issue), vol. 7 no. 023, pp.1-14, 2016
Workshops and Conferences
1. V. Chawla, H. S. Naik, A. Akintayo, D. Hayes, P. Schnable, B. Ganapathysubramanian and S. Sarkar, A-Bayesian Network approach to County-level Corn yield prediction using historical data and expert knowledge, Knowledge discovery and Data Mining Workshop on Data Science for Food, Energy and Water (KDD- DSFEW), pp. 1-8, Aug, 2016.
2. A. Akintayo, K.G. Lore, Soumalya Sarkar and S. Sarkar, Prognostics of combustion instabilities from Hi-speed flame videos using a deep convolutional selective auto encoder Prognostics and Health Management (PHM) conference, Denver Colorado, 2016
3. A. Akintayo, N.Lee, V.Chawla, C. Marett, M. Mullaney, A. K. Singh, A. Singh, G. Tylka, B. Ganapathysubramanian and S. Sarkar, An end-to-end convolutional selective auto encoder approach to Soybean Cyst Nematode SCN eggs detection, Knowledge discovery and Data Mining Workshop on Data Science for Food, Energy and Water (KDD- DSFEW), pp. 1-8, Aug, 2016.
4. A. Akintayo, K.G. Lore, Soumalya Sarkar and S. Sarkar, Early Detection of Combustion Instabilities using Deep Convolutional Selective Autoencoders of Hi-speed Flame Video 1st Knowledge Discovery and Data Mining Workshop on Prognostics and Health Management (KDD - PHM), pp. 1-10, Aug, 2016
5. A. Akintayo, S. Sarkar, A Symbolic Dynamic Filtering Approach to Unsupervised Hierarchical Feature Extraction from Time-Series Data, Proceedings of the American Control Conference, Chicago, 2015
Book Chapter
1. S. Sarkar, Z. Jiang, A. Akintayo, K. Krishnamurthy & A. Tewari, Probabilistic Graphical Model of Distributed Cyber-Physical Systems in Cyber-Physical Systems: Foundations, Applications and Principles ,Elsevier Publication, 2016