Research Interests

  • Machine Learning

Courses Taught

Number

Name

Level

ECE 1111

Engineering Computation I

Undergraduate

ECE 3822

Engineering Computation II

Undergraduate

ECE 3822

Software Tools for Engineers

Undergraduate

ECE 4110

Special Topics:Introduction to Machine Learning and Pattern Recognition

Undergraduate

ECE 4110

Special Topics: Artificial Intelligence

Undergraduate

ECE 8527

Introduction to Machine Learning and Pattern Recognition

Graduate

Selected Publications

  • Golmohammadi, M., Torbati, A.H.H.N., Diego, S.L.d.e., Obeid, I., & Picone, J. (2019). Automatic analysis of EEGs using big data and hybrid deep learning architectures. Frontiers in Human Neuroscience, 13. doi: 10.3389/fnhum.2019.00076

  • Ferrell, S., Weltin, E.V., Obeid, I., & Picone, J. (2019). Open Source Resources to Advance EEG Research. 2018 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2018 - Proceedings. doi: 10.1109/SPMB.2018.8615622

  • Houser, D., Shadhin, G., Anstotz, R., Campbell, C., Obeid, I., Picone, J., Farkas, T., Persidsky, Y., & Jhala, N. (2019). The Temple University Hospital Digital Pathology Corpus. 2018 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2018 - Proceedings. doi: 10.1109/SPMB.2018.8615619

  • Shah, V., Anstotz, R., Obeid, I., & Picone, J. (2019). Adapting an Automatic Speech Recognition System to Event Classification of Electroencephalograms 1. 2018 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2018 - Proceedings. doi: 10.1109/SPMB.2018.8615625

  • Capp, N., Campbell, C., Elseify, T., Obeid, I., & Picone, J. (2019). Optimizing EEG Visualization Through Remote Data Retrieval. 2018 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2018 - Proceedings. doi: 10.1109/SPMB.2018.8615613

  • Campbell, C., Mecca, N., Duong, T., Obeid, I., & Picone, J. (2019). Expanding an HPC Cluster to Support the Computational Demands of Digital Pathology. 2018 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2018 - Proceedings. doi: 10.1109/SPMB.2018.8615614

  • Golmohammadi, M., Ziyabari, S., Shah, V., Obeid, I., & Picone, J. (2019). Deep Architectures for Spatio-Temporal Modeling: Automated Seizure Detection in Scalp EEGs. Proceedings - 17th IEEE International Conference on Machine Learning and Applications, ICMLA 2018, pp. 745-750. doi: 10.1109/ICMLA.2018.00118

  • Jungreis, D., Capp, N., Golmohammadi, M., & Picone, J. (2019). Predicting Endogenous Bank Health from FDIC Statistics on Depository Institutions Using Deep Learning. Advances in Intelligent Systems and Computing, 997, pp. 563-572. doi: 10.1007/978-3-030-22871-2_38

  • Shah, V., Weltin, E.v., Lopez, S., McHugh, J.R., Veloso, L., Golmohammadi, M., Obeid, I., & Picone, J. (2018). The temple university hospital seizure detection corpus. Frontiers in Neuroinformatics, 12. doi: 10.3389/fninf.2018.00083

  • Saleheen, F., Wang, Z., Picone, J., Butz, B.P., & Won, C.H. (2018). Efficacy of a virtual teaching assistant in an open laboratory environment for electric circuits. Advances in Engineering Education, 6(3), pp. 1-27.

  • Shah, V., Golmohammadi, M., Ziyabari, S., Weltin, E.V., Obeid, I., & Picone, J. (2018). Optimizing channel selection for seizure detection. 2017 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2017 - Proceedings, 2018-January, pp. 1-5. doi: 10.1109/SPMB.2017.8257019

  • Weltin, E.V., Ahsan, T., Shah, V., Jamshed, D., Golmohammadi, M., Obeid, I., & Picone, J. (2018). Electroencephalographic slowing: A primary source of error in automatic seizure detection. 2017 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2017 - Proceedings, 2018-January, pp. 1-5. doi: 10.1109/SPMB.2017.8257018

  • Capp, N., Krome, E., Obeid, I., & Picone, J. (2018). Facilitating the annotation of seizure events through an extensible visualization tool. 2017 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2017 - Proceedings, 2018-January, pp. 1-3. doi: 10.1109/SPMB.2017.8257043

  • Campbell, C., Mecca, N., Obeid, I., & Picone, J. (2018). The Neuronix HPC cluster: Cluster management using free and open source software tools. 2017 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2017 - Proceedings, 2018-January, pp. 1-3. doi: 10.1109/SPMB.2017.8257042

  • Golmohammadi, M., Ziyabari, S., Shah, V., Weltin, E.V., Campbell, C., Obeid, I., & Picone, J. (2018). Gated recurrent networks for seizure detection. 2017 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2017 - Proceedings, 2018-January, pp. 1-5. doi: 10.1109/SPMB.2017.8257020

  • Veloso, L., McHugh, J., Weltin, E.V., Lopez, S., Obeid, I., & Picone, J. (2018). Big data resources for EEGs: Enabling deep learning research. 2017 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2017 - Proceedings, 2018-January, pp. 1-3. doi: 10.1109/SPMB.2017.8257044

  • Lazarou, G.Y., Alam, M.S., & Picone, J. (2017). Measuring the variability of CAIDA internet traffic traces. 19th International Conference on Computer and Information Technology, ICCIT 2016, pp. 1-6. doi: 10.1109/ICCITECHN.2016.7860158

  • Torbati, A.H.H.N. & Picone, J. (2017). A nonparametric Bayesian approach for automatic discovery of a lexicon and acoustic units. 2016 IEEE Workshop on Spoken Language Technology, SLT 2016 - Proceedings, pp. 71-75. doi: 10.1109/SLT.2016.7846247

  • Lopez, S., Gross, A., Yang, S., Golmohammadi, M., Obeid, I., & Picone, J. (2017). An analysis of two common reference points for EEGS. 2016 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2016 - Proceedings. doi: 10.1109/SPMB.2016.7846854

  • Somaru, P., Obeid, I., & Picone, J. (2017). Low-cost high-performance computing via consumer GPUs. 2016 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2016 - Proceedings. doi: 10.1109/SPMB.2016.7846867

  • Yang, S., Lopez, S., Golmohammadi, M., Obeid, I., & Picone, J. (2017). Semi-automated annotation of signal events in clinical EEG data. 2016 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2016 - Proceedings. doi: 10.1109/SPMB.2016.7846855

  • Thiess, M., Krome, E., Golmohammadi, M., Obeid, I., & Picone, J. (2017). Enhanced visualizations for improved real-time EEG monitoring. 2016 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2016 - Proceedings. doi: 10.1109/SPMB.2016.7846868

  • Ward, C., Picone, J., & Obeid, I. (2016). Applications of UBMs and I-vectors in EEG subject verification. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, 2016-October, pp. 748-751. doi: 10.1109/EMBC.2016.7590810

  • Saleheen, F., Wang, Z., Moser, W., Oleksyuk, V., Picone, J., & Won, C.H. (2016). Effectiveness of virtual open laboratory teaching assistant for circuits laboratories. ASEE Annual Conference and Exposition, Conference Proceedings, 2016-June.

  • Trejo, D., Obeid, I., & Picone, J. (2016). Affordable supercomputing using open source software. 2015 IEEE Signal Processing in Medicine and Biology Symposium - Proceedings. doi: 10.1109/SPMB.2015.7405431

  • Lopez, S., Suarez, G., Jungreis, D., Obeid, I., & Picone, J. (2016). Automated identification of abnormal adult EEGs. 2015 IEEE Signal Processing in Medicine and Biology Symposium - Proceedings. doi: 10.1109/SPMB.2015.7405423

  • Moura, A., Lopez, S., Obeid, I., & Picone, J. (2016). A comparison of feature extraction methods for EEG signals. 2015 IEEE Signal Processing in Medicine and Biology Symposium - Proceedings. doi: 10.1109/SPMB.2015.7405430

  • Harati, A., Golmohammadi, M., Lopez, S., Obeid, I., & Picone, J. (2016). Improved EEG event classification using differential energy. 2015 IEEE Signal Processing in Medicine and Biology Symposium - Proceedings. doi: 10.1109/SPMB.2015.7405421

  • Torbati, A. & Picone, J. (2016). A doubly hierarchical dirichlet process Hidden Markov Model with a non-ergodic structure. IEEE/ACM Transactions on Audio Speech and Language Processing, 24(1), pp. 174-184. doi: 10.1109/TASLP.2015.2500732

  • Torbati, A. & Picone, J. (2016). A nonparametric Bayesian approach for spoken term detection by example query. Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH, 08-12-September-2016, pp. 928-932. doi: 10.21437/Interspeech.2016-315

  • Obeid, I. & Picone, J. (2016). The temple university hospital EEG data corpus. Frontiers in Neuroscience, 10(MAY). doi: 10.3389/fnins.2016.00196

  • Parihar, N., Picone, J., Pearce, D., & Hirsch, H.G. (2015). Performance analysis of the Aurora large vocabulary baseline system. European Signal Processing Conference, 06-10-September-2004, pp. 553-556.

  • Alphonso, I. & Picone, J. (2015). Network training for continuous speech recognition. European Signal Processing Conference, 06-10-September-2004, pp. 565-568.

  • Harati, A., Lopez, S., Obeid, I., Picone, J., Jacobson, M.P., & Tobochnik, S. (2015). The TUH EEG CORPUS: A big data resource for automated EEG interpretation. 2014 IEEE Signal Processing in Medicine and Biology Symposium, IEEE SPMB 2014 - Proceedings. doi: 10.1109/SPMB.2014.7002953

  • Steinberg, J., Harati, A., & Picone, J. (2015). A comparative analysis of bayesian nonparametric inference algorithms for acoustic modeling in speech recognition. Lecture Notes in Electrical Engineering, 313, pp. 461-466. doi: 10.1007/978-3-319-06773-5_61

  • Srinivasan, S., Ma, T., Lazarou, G., & Picone, J. (2014). A nonlinear autoregressive model for speaker verification. International Journal of Speech Technology, 17(1), pp. 17-25. doi: 10.1007/s10772-013-9201-9

  • Ma, T., Srinivasan, S., Lazarou, G., & Picone, J. (2014). Continuous speech recognition using linear dynamic models. International Journal of Speech Technology, 17(1), pp. 11-16. doi: 10.1007/s10772-013-9200-x

  • Torbati, A. & Picone, J. (2014). Predicting search term reliability for spoken term detection systems. International Journal of Speech Technology, 17(1), pp. 1-9. doi: 10.1007/s10772-013-9197-1

  • Torbati, A., Picone, J., & Sobel, M. (2014). A left-to-right HDP-HMM with HDPM emissions. 2014 48th Annual Conference on Information Sciences and Systems, CISS 2014. doi: 10.1109/CISS.2014.6814172

  • Sahu, A., Saleheen, F., Oleksyuk, V., McGoverin, C., Pleshko, N., Torbati, A., Picone, J., Sorenmo, K., & Won, C.H. (2014). Characterization of mammary tumors using noninvasive tactile and hyperspectral sensors. IEEE Sensors Journal, 14(10), pp. 3337-3344. doi: 10.1109/JSEN.2014.2323215