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Wael Korani

Title: Assistant Professor

Department: Data Science

College: College of Information

Curriculum Vitae

Curriculum Vitae Link

Education

  • PhD, University of Regina, 2021
    Major: Computer Science
    Specialization: Artificial intelligence
    Dissertation: Mother Tree Optimization for solving continues and discrete optimization problems
  • MSc, Tuskegee university, 2015
    Major: Bioinformatics
    Specialization: Master of science
  • Certificate, Oracle university, 2008
    Major: database
    Specialization: DBA and DBD
  • MSc, Cairo University, 2008
    Major: Electrical Power and Machines Engineering
    Specialization: Control Systems
  • BS, Ain Shams University, 2002
    Major: Electrical Engineering
    Specialization: Electrical Engineering

Current Scheduled Teaching

DTSC 5501.020Fundamentals of Data ScienceSpring 2026
DTSC 5501.401Fundamentals of Data ScienceSpring 2026
INFO 6900.727Special ProblemsSpring 2026
Texas Education Code 51.974 (HB 2504) requires each institution of higher education to make available to the public, a syllabus for undergraduate lecture courses offered for credit by the institution.

Previous Scheduled Teaching

DTSC 5501.020Fundamentals of Data ScienceFall 2025 SPOT
DTSC 5501.402Fundamentals of Data ScienceFall 2025 SPOT
INFO 6900.042Special ProblemsFall 2025
INFO 4709.401Data VisualizationSummer 10W 2025 Syllabus SPOT
INFO 5707.020Data Modeling for Information ProfessionalsSpring 2025 SPOT
INFO 6900.727Special ProblemsSpring 2025
DTSC 5501.020Fundamentals of Data ScienceFall 2024 SPOT
DTSC 5501.402Fundamentals of Data ScienceFall 2024 SPOT
INFO 6900.042Special ProblemsFall 2024
DTSC 5505.004Applied Machine Learning for Data ScientistsSummer 10W 2024 SPOT
INFO 5505.020Applied Machine Learning for Data ScientistsSpring 2024 SPOT
INFO 6900.727Special ProblemsSpring 2024
INFO 5505.020Applied Machine Learning for Data ScientistsFall 2023 SPOT
INFO 6900.042Special ProblemsFall 2023
INFO 5505.001Applied Machine Learning for Data ScientistsSummer 5W2 2023 SPOT
INFO 5709.002Data Visualization and CommunicationSummer 5W1 2023 SPOT
INFO 5505.020Applied Machine Learning for Data ScientistsSpring 2023 SPOT
INFO 5505.001Applied Machine Learning for Data ScientistsFall 2022 SPOT
INFO 5505.020Applied Machine Learning for Data ScientistsFall 2022 SPOT
INFO 5505.001Applied Machine Learning for Data ScientistsSummer 5W2 2022 SPOT
INFO 5709.002Data Visualization and CommunicationSummer 5W1 2022 SPOT
Texas Education Code 51.974 (HB 2504) requires each institution of higher education to make available to the public, a syllabus for undergraduate lecture courses offered for credit by the institution.

Published Intellectual Contributions

    Book Chapter

  • Akbari, H., Korani, W., Kumar, P.M., Rostami, R., Kazemi, R. (2025). Prediction of the Effectiveness of rTMS for Depression. Communications in Computer and Information Science. 454-464. Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-85908-3_37
  • Akbari, H., Korani, W., Kumar, P.M., Rostami, R., Kazemi, R. (2025). Prediction of the Effectiveness of rTMS for Depression. Communications in Computer and Information Science. 454-464. Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-85908-3_37
  • Akbari, H., Korani, W., Kumar, P.M. (2025). Prediction of the Outcomes of SSRI Therapy for Depressed Patients Using Tuned Q-factor Wavelet Transform and EEG Signals. Communications in Computer and Information Science. 492-502. Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-85908-3_41
  • Akbari, H., Korani, W., Ding, J., Rostami, R., Kazemi, R. (2025). TOP-EEG: A Robust Software to Predict the Outcomes of Therapies for Depression Using EEG Signals in DGMD Domain. Communications in Computer and Information Science. 403-419. Springer Nature Singapore. https://doi.org/10.1007/978-981-96-7033-8_28
  • Akbari, H., Korani, W., Ding, J., Rostami, R., Kazemi, R. (2025). TOP-EEG: A Robust Software to Predict the Outcomes of Therapies for Depression Using EEG Signals in DGMD Domain. Communications in Computer and Information Science. 403-419. Springer Nature Singapore. https://doi.org/10.1007/978-981-96-7033-8_28
  • Akbari, H., Korani, W., Ding, J., Rostami, R., Kazemi, R. (2025). TOP-EEG: A Robust Software to Predict the Outcomes of Therapies for Depression Using EEG Signals in DGMD Domain. Communications in Computer and Information Science. 403-419. Springer Nature Singapore. https://doi.org/10.1007/978-981-96-7033-8_28
  • Akbari, H., Korani, W., Ding, J., Rostami, R., Kazemi, R. (2025). TOP-EEG: A Robust Software to Predict the Outcomes of Therapies for Depression Using EEG Signals in DGMD Domain. Communications in Computer and Information Science. 403-419. Springer Nature Singapore. https://doi.org/10.1007/978-981-96-7033-8_28
  • Akbari, H., Korani, W., Ding, J., Rostami, R., Kazemi, R. (2025). UNT-AT: A Robust Software to Predict the Outcome of Depression Therapies Using EEG Signals. Communications in Computer and Information Science. 344-360. Springer Nature Singapore. https://doi.org/10.1007/978-981-96-6957-8_24
  • Akbari, H., Korani, W., Ding, J., Rostami, R., Kazemi, R. (2025). UNT-AT: A Robust Software to Predict the Outcome of Depression Therapies Using EEG Signals. Communications in Computer and Information Science. 344-360. Springer Nature Singapore. https://doi.org/10.1007/978-981-96-6957-8_24
  • Akbari, H., Korani, W. (2024). Automatic detection of seizure activity using EEG signals. Artificial Intelligence. 8-1-8-20. IOP Publishing. https://doi.org/10.1088/978-0-7503-5964-1ch8
  • Akbari, H., Korani, W. (2024). Mother tree optimization for early detection of focal seizure using entropy-based features. Artificial Intelligence. 7-1-7-25. IOP Publishing. https://doi.org/10.1088/978-0-7503-5964-1ch7
  • Korani, W., Mouhoub, M. (2020). Breast Cancer Diagnostic Tool Using Deep Feedforward Neural Network and Mother Tree Optimization. Communications in Computer and Information Science. 229-240. Springer International Publishing. https://doi.org/10.1007/978-3-030-41913-4_19
  • Korani, W., Mouhoub, M. (2020). Breast Cancer Diagnostic Tool Using Deep Feedforward Neural Network and Mother Tree Optimization. Communications in Computer and Information Science. 229-240. Springer International Publishing. https://doi.org/10.1007/978-3-030-41913-4_19

    • Conference Proceeding

  • Korani, W., Mouhoub, M. (2025). Data Clustering Using Mother Tree Optimization. Proceedings of the 14th International Conference on Operations Research and Enterprise Systems. 215-220. SCITEPRESS - Science and Technology Publications. https://doi.org/10.5220/0013105300003893
  • Korani, W., Mouhoub, M. (2025). Data Clustering Using Mother Tree Optimization. Proceedings of the 14th International Conference on Operations Research and Enterprise Systems. 215-220. SCITEPRESS - Science and Technology Publications. https://doi.org/10.5220/0013105300003893
  • Akbari, H., Korani, W., Kumar, P.M. (2025). Prediction of the Outcomes of SSRI Therapy for Depressed Patients Using Tuned Q-factor Wavelet Transform and EEG Signals. Communications in Computer and Information Science. 492-502. Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-85908-3_41
  • Kumar, P.M., Korani, W., Singh, M., Kavin, B.P. (2025). Predictive Analytic Model for Classifying the Health State of Fetal Heart Using Ensemble Model. 2025 IEEE 4th International Conference on Computing and Machine Intelligence (ICMI). 1-5. IEEE. https://doi.org/10.1109/icmi65310.2025.11141274
  • Kumar, P.M., Korani, W., Singh, M., Kavin, B.P. (2025). Predictive Analytic Model for Classifying the Health State of Fetal Heart Using Ensemble Model. 2025 IEEE 4th International Conference on Computing and Machine Intelligence (ICMI). 1-5. IEEE. https://doi.org/10.1109/icmi65310.2025.11141274
  • Kumar, P.M., Korani, W., Kavin, B.P., Selvaraj, J. (2025). Enhanced IoT Security for Healthcare: A Lionized Remora Optimization-Based Image Encryption Algorithm with Chaotic Maps. 2025 IEEE Green Technologies Conference (GreenTech). 1-5. IEEE. https://doi.org/10.1109/greentech62170.2025.10977643
  • Kumar, P.M., Korani, W., Kavin, B.P., Selvaraj, J. (2025). Enhanced IoT Security for Healthcare: A Lionized Remora Optimization-Based Image Encryption Algorithm with Chaotic Maps. 2025 IEEE Green Technologies Conference (GreenTech). 1-5. IEEE. https://doi.org/10.1109/greentech62170.2025.10977643
  • Kumar, P.M., Korani, W., Kavin, B.P., Selvaraj, J. (2025). Enhanced IoT Security for Healthcare: A Lionized Remora Optimization-Based Image Encryption Algorithm with Chaotic Maps. 2025 IEEE Green Technologies Conference (GreenTech). 1-5. IEEE. https://doi.org/10.1109/greentech62170.2025.10977643
  • Akbari, H., Korani, W., Korani, W., Akbari, H. (2024). Early Detection of Depression and Alcoholism Disorders by EEG Signal.
  • Malarvizhi Kumar, P., Korani, W., C, G., Selvaraj, J. (2024). IoT-Powered BGCNet: Thyroid Disease Detection Enhancement in Healthcare with IBESA based Feature Selection. In 2024 IEEE Green Technologies Conference (GreenTech). IEEE..
  • Akbari, H., Korani, W., Ding, J., Rostami, R., Kazemi, R. (2024). TOP-EEG: a robust software to predict the outcomes of therapies for depression using EEG signals in DGMD domain. International Conference on Neural Information Processing (ICONIP2024).
  • Akbari, H., Korani, W., Ding, J., Rostami, R., Kazemi, R. (2024). UNT-AT: A Robust Software to Predict the Outcome of Depression Therapies Using EEG Signals. International Conference on Neural Information Processing (ICONIP2024).
  • Kumar, P.M., Korani, W., C, G., Selvaraj, J. (2024). IoT-Powered BGCNet: Thyroid Disease Detection Enhancement in Healthcare with IBESA based Feature Selection. 2024 IEEE Green Technologies Conference (GreenTech). 48-53. IEEE. https://doi.org/10.1109/greentech58819.2024.10520604
  • Korani, W. (2023). Binary Mother Tree Optimization Algorithm for 0/1 Knapsack Problem. Springer nature.
  • Korani, W., Mouhoub, M. (2022). Discrete Mother Tree Optimization and Swarm Intelligence for Constraint Satisfaction Problems. Proceedings of the 14th International Conference on Agents and Artificial Intelligence. 234-241. SCITEPRESS - Science and Technology Publications. https://doi.org/10.5220/0010803100003116
  • Korani, W., Mouhoub, M. (2022). Mother Tree Optimization for Conditional Constraints and Qualitative Preferences. 2022 IEEE Symposium Series on Computational Intelligence (SSCI). 1610-1617. IEEE. https://doi.org/10.1109/ssci51031.2022.10022070
  • Korani, W., Mouhoub, M. (2020). Sentiment Analysis of Serious Suicide References in Twitter Social Network. Proceedings of the 12th International Conference on Agents and Artificial Intelligence. 339-346. SCITEPRESS - Science and Technology Publications. https://doi.org/10.5220/0008894003390346
  • Korani, W., Mouhoub, M. (2020). Sentiment Analysis of Serious Suicide References in Twitter Social Network. Proceedings of the 12th International Conference on Agents and Artificial Intelligence. 339-346. SCITEPRESS - Science and Technology Publications. https://doi.org/10.5220/0008894003390346

    • Journal Article

  • Akbari, H., Korani, W., Rostami, R., Kazemi, R. (2026). Predicting the outcome of depression therapies using a pattern of sixteen consecutive bits of EEG signals. Other. 113 108808. Elsevier BV. https://doi.org/10.1016/j.bspc.2025.108808
  • Akbari, H., Korani, W., Rostami, R., Kazemi, R. (2026). Predicting the outcome of depression therapies using a pattern of sixteen consecutive bits of EEG signals. Other. 113 108808. Elsevier BV. https://doi.org/10.1016/j.bspc.2025.108808
  • Kumar, P.M., Korani, W., Shahwar, T., Gokulnath, C. (2025). A significant framework for epilepsy and seizure clusters detection using MSRS-LSTM and FID-DO. Other. SAGE Publications. https://doi.org/10.1177/1088467x251395618
  • Kumar, P.M., Korani, W., Shahwar, T., Gokulnath, C. (2025). A significant framework for epilepsy and seizure clusters detection using MSRS-LSTM and FID-DO. Other. SAGE Publications. https://doi.org/10.1177/1088467x251395618
  • Kumar, P.M., Korani, W., Shahwar, T., Gokulnath, C. (2025). A significant framework for epilepsy and seizure clusters detection using MSRS-LSTM and FID-DO. Other. SAGE Publications. https://doi.org/10.1177/1088467x251395618
  • Akbari, H., Korani, W., Kumar, P.M., Rostami, R., Kazemi, R. (2025). Dynamical pattern of successive bits to predict the outcomes of the SSRI and rTMS depression therapies using EEG signals. Computers in Biology and Medicine. 196 110500. Elsevier BV. https://doi.org/10.1016/j.compbiomed.2025.110500
  • Akbari, H., Korani, W., Muhammad, S., Rostami, R., Kazemi, R., Sadiq, M.T. (2025). Predicting Depression Therapy Outcomes Using EEG-Derived Amplitude Polar Maps. Brain Sciences. 15 (9) 977. MDPI AG. https://doi.org/10.3390/brainsci15090977
  • Akbari, H., Korani, W., Muhammad, S., Rostami, R., Kazemi, R., Sadiq, M.T. (2025). Predicting Depression Therapy Outcomes Using EEG-Derived Amplitude Polar Maps. Brain Sciences. 15 (9) 977. MDPI AG. https://doi.org/10.3390/brainsci15090977
  • Akbari, H., Korani, W., Muhammad, S., Rostami, R., Kazemi, R., Sadiq, M.T. (2025). Predicting Depression Therapy Outcomes Using EEG-Derived Amplitude Polar Maps. Brain Sciences. 15 (9) 977. MDPI AG. https://doi.org/10.3390/brainsci15090977
  • Korani, W., Domakonda, S.S. (2025). Time frequency images as predictors for depressed patients’ respondent status to SSRI antidepressant. Other. 104 107440. Elsevier BV. https://doi.org/10.1016/j.bspc.2024.107440
  • Korani, W., Domakonda, S.S. (2025). Time frequency images as predictors for depressed patients’ respondent status to SSRI antidepressant. Other. 104 107440. Elsevier BV. https://doi.org/10.1016/j.bspc.2024.107440
  • Kumar, P.M., Korani, W., Shahwar, T., C., G. (2025). Detection of Sub-acute Brain Injury and Hypoxic-ischemic Encephalopathy using I2C2-WGO and CO-GW-RNN. Other. 21 Bentham Science Publishers Ltd.. https://doi.org/10.2174/0115734056352573241118122026
  • Kumar, P.M., Korani, W., Shahwar, T., C., G. (2025). Detection of Sub-acute Brain Injury and Hypoxic-ischemic Encephalopathy using I2C2-WGO and CO-GW-RNN. Other. 21 Bentham Science Publishers Ltd.. https://doi.org/10.2174/0115734056352573241118122026
  • Kumar, P.M., Korani, W., Shahwar, T., C., G. (2025). Detection of Sub-acute Brain Injury and Hypoxic-ischemic Encephalopathy using I2C2-WGO and CO-GW-RNN. Other. 21 Bentham Science Publishers Ltd.. https://doi.org/10.2174/0115734056352573241118122026
  • Korani, W., S. S, D., Malarvizhi Kumar, P. (2024). Early Detection of Brain Tumor Using MRI and Transfer Learning.. Biomedical Engineering: Applications, Basis and Communications.

Contracts, Grants and Sponsored Research

    Grant - Research

  • Malarvizhi Kumar, P. (Principal), Xiao, T. (Co-Principal), Korani, W. (Co-Principal), "Cohort II of the Capacity Building for Research at Minority-Serving Institutions: Infrastructure Research Readiness," sponsored by NSF, Federal, $3000 Funded. (2023 - 2024).
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Overall
Summative Rating		 Challenge and
Engagement Index		 Response Rate

out of 5
out of 7		 %
of
students responded
  • Overall Summative Rating (median):
    This rating represents the combined responses of students to the four global summative items and is presented to provide an overall index of the class’s quality. Overall summative statements include the following (response options include a Likert scale ranging from 5 = Excellent, 3 = Good, and 1= Very poor):
    • The course as a whole was
    • The course content was
    • The instructor’s contribution to the course was
    • The instructor’s effectiveness in teaching the subject matter was
  • Challenge and Engagement Index:
    This rating combines student responses to several SPOT items relating to how academically challenging students found the course to be and how engaged they were. Challenge and Engagement Index items include the following (response options include a Likert scale ranging from 7 = Much higher, 4 = Average, and 1 = Much lower):
    • Do you expect your grade in this course to be
    • The intellectual challenge presented was
    • The amount of effort you put into this course was
    • The amount of effort to succeed in this course was
    • Your involvement in course (doing assignments, attending classes, etc.) was
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