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Iyad Obeid

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Iyad Obeid

  • College of Engineering

    • Electrical and Computer Engineering

      • Associate Professor

Biography

Dr. Obeid is an Associate Professor of Electrical and Computer Engineering with a secondary appointment in Bioengineering. His research focuses recording and decoding signals from neural tissue. This includes applications for brain computer interfaces, brain-in-a-dish studies, and traumatic brain injury. His lab has made extensive use of Field Programmable Gate Array (FPGA) technology to make and decode massively parallel neural recordings. Dr. Obeid is a recipient of the National Science Foundation CAREER Award as well as a Lindback Award for distinguished teaching.

Labs: Neural Instramentation Lab

Research Interests

  • Recording & Decoding Signals from Neural Tissue
  • Applications for Brain Computer Interfaces
  • Brain-in-a-Dish Studies
  • and Traumatic Brain Injury
  • Field Programmable Gate Array (FPGA) Technology to Make and Decode Massively Parallel Neural Recordings

Courses Taught

Number

Name

Level

BIOE 0844

The Bionic Human

Undergraduate

ECE 2112

Electrical Devices & Systems I

Undergraduate

ECE 3822

Engineering Computation II

Undergraduate

ECE 3824

Engineering Computation III

Undergraduate

ECE 5033

Probability and Random Processes

Graduate

Selected Publications

Recent

  • Roy, S., Kiral, I., Mirmomeni, M., Mummert, T., Braz, A., Tsay, J., Tang, J., Asif, U., Schaffter, T., Ahsen, M., Iwamori, T., Yanagisawa, H., Poonawala, H., Madan, P., Qin, Y., Picone, J., Obeid, I., Marques, B., Maetschke, S., Khalaf, R., Rosen-Zvi, M., Stolovitzky, G., & Harrer, S. (2021). Evaluation of artificial intelligence systems for assisting neurologists with fast and accurate annotations of scalp electroencephalography data. EBioMedicine, 66. doi: 10.1016/j.ebiom.2021.103275.

  • Rahman, S., Hamid, A., Ochal, D., Obeid, I., & Picone, J. (2020). Improving the Quality of the TUSZ Corpus. 2020 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2020 - Proceedings. doi: 10.1109/SPMB50085.2020.9353635.

  • Hamid, A., Gagliano, K., Rahman, S., Tulin, N., Tchiong, V., Obeid, I., & Picone, J. (2020). The Temple University Artifact Corpus: An Annotated Corpus of EEG Artifacts. 2020 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2020 - Proceedings. doi: 10.1109/SPMB50085.2020.9353647.

  • Shawki, N., Elseify, T., Cap, T., Shah, V., Obeid, I., & Picone, J. (2020). A Deep Learning-Based Real-time Seizure Detection System. 2020 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2020 - Proceedings. doi: 10.1109/SPMB50085.2020.9353623.

  • Shah, V., Obeid, I., Picone, J., Ekladious, G., Iskander, R., & Roy, Y. (2020). Validation of Temporal Scoring Metrics for Automatic Seizure Detection. 2020 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2020 - Proceedings. doi: 10.1109/SPMB50085.2020.9353631.

  • Rahman, S., Miranda, M., Obeid, I., & Picone, J. (2019). Software and Data Resources to Advance Machine Learning Research in Electroencephalography. 2019 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2019 - Proceedings. doi: 10.1109/SPMB47826.2019.9037851.

  • Hunt, I., Husain, S., Simon, J., Obeid, I., & Picone, J. (2019). Recent Advances in the Temple University Digital Pathology Corpus. 2019 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2019 - Proceedings. doi: 10.1109/SPMB47826.2019.9037859.

  • Jean-Paul, S., Elseify, T., Obeid, I., & Picone, J. (2019). Issues in the Reproducibility of Deep Learning Results. 2019 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2019 - Proceedings. doi: 10.1109/SPMB47826.2019.9037840.

  • Kane, Z., Stecco, E., Napoli, A., Tucker, C., & Obeid, I. (2019). The Instrumented Multitask Assessment System (IMAS). 2019 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2019 - Proceedings. doi: 10.1109/SPMB47826.2019.9037841.

  • Golmohammadi, M., Torbati, A.H.N., Diego, S.L.d., 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.

  • Glass, S., Napoli, A., Thompson, E., Obeid, I., & Tucker, C. (2019). Validity of an automated balance error scoring system. Journal of Applied Biomechanics, 35(1), 32-36. doi: 10.1123/jab.2018-0056.

  • 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.

  • 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.

  • 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.

  • 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.

  • 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, 745-750. doi: 10.1109/ICMLA.2018.00118.

  • Ward, C. & Obeid, I. (2019). Application of identity vectors for EEG classification. Journal of Neuroscience Methods, 311, 338-350. doi: 10.1016/j.jneumeth.2018.09.015.

  • Shah, V., Weltin, E.v., Lopez, S., McHugh, J., 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.

  • Bemal, V., Satterthwaite, N., Napoli, A., Glass, S., Tucker, C., & Obeid, I. (2018). Kinect v2 accuracy as a body segment measuring tool. 2017 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2017 - Proceedings, 2018-January, 1-3. doi: 10.1109/SPMB.2017.8257050.

  • Napoli, A., Glass, S., Tucker, C., & Obeid, I. (2017). The Automated Assessment of Postural Stability: Balance Detection Algorithm. Annals of Biomedical Engineering, 45(12), 2784-2793. doi: 10.1007/s10439-017-1911-8.

  • Napoli, A., Glass, S., Ward, C., Tucker, C., & Obeid, I. (2017). Performance analysis of a generalized motion capture system using microsoft kinect 2.0 Biomedical Signal Processing and Control, 38, 265-280. doi: 10.1016/j.bspc.2017.06.006.

  • Capp, N., Krome, E., Obeid, I., & Picone, J. (2017). 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, 1-3. doi: 10.1109/SPMB.2017.8257043.

  • Weltin, E.V., Ahsan, T., Shah, V., Jamshed, D., Golmohammadi, M., Obeid, I., & Picone, J. (2017). 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, 1-5. doi: 10.1109/SPMB.2017.8257018.

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

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

  • Campbell, C., Mecca, N., Obeid, I., & Picone, J. (2017). 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, 1-3. doi: 10.1109/SPMB.2017.8257042.

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

  • 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.

  • 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.

  • Ward, C. & Obeid, I. (2017). Feasibility of Identity Vectors for use as subject verification and cohort retrieval of electroencephalograms. 2016 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2016 - Proceedings. doi: 10.1109/SPMB.2016.7846853.

  • 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.

  • 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.