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Mohammed Aledhari

Title: Assistant Professor

Department: Information Science

College: College of Information

Curriculum Vitae

Curriculum Vitae Link

Education

  • PhD, Western Michigan University, 2017
    Major: Computer Science
    Specialization: AI/ML
    Dissertation: A Deep Learning-Based Data Minimization Algorithm for Big Genomics Data in Support of loT and Secure Smart Health Services

Current Scheduled Teaching

DTSC 5505.020Applied Machine Learning for Data ScientistsSpring 2025
DTSC 5505.021Applied Machine Learning for Data ScientistsSpring 2025
DTSC 5505.402Applied Machine Learning for Data ScientistsSpring 2025
INFO 4910.401Special ProblemsSpring 2025
DTSC 5505.401Applied Machine Learning for Data ScientistsFall 2024
INFO 6900.046Special ProblemsFall 2024
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 5505.002Applied Machine Learning for Data ScientistsSummer 10W 2024 SPOT
INFO 5505.001Applied Machine Learning for Data ScientistsSpring 2024 SPOT
INFO 6900.724Special ProblemsSpring 2024
INFO 5505.001Applied Machine Learning for Data ScientistsFall 2023 SPOT
INFO 5505.002Applied Machine Learning for Data ScientistsSummer 10W 2023 SPOT
INFO 5505.001Applied Machine Learning for Data ScientistsSpring 2023 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

    Conference Proceeding

  • Aledhari, M., Razzak, R., Parizi, R.M., Srivastava, G. (2021). Multimodal Machine Learning for Pedestrian Detection. IEEE Vehicular Technology Conference. 2021-April https://api.elsevier.com/content/abstract/scopus_id/85112406615
  • Aledhari, M., Razzak, R., Parizi, R.M., Srivastava, G. (2021). Sensor Fusion for Drone Detection. IEEE Vehicular Technology Conference. 2021-April https://api.elsevier.com/content/abstract/scopus_id/85112401473
  • Aledhari, M., Razzak, R., Parizi, R.M., Srivastava, G. (2021). Deep Neural Networks for Detecting Real Emotions Using Biofeedback and Voice. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 12664 LNCS 302-309. https://api.elsevier.com/content/abstract/scopus_id/85103460753
  • Aledhari, M., Razzak, R. (2020). An Adaptive Segmentation Technique to Detect Brain Tumors Using 2D Unet. Proceedings - 2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020. 2328-2334. https://api.elsevier.com/content/abstract/scopus_id/85100332648
  • Aledhari, M., Razzak, R., Parizi, R.M., Dehghantanha, A. (2020). A Deep Recurrent Neural Network to Support Guidelines and Decision Making of Social Distancing. Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020. 4233-4240. https://api.elsevier.com/content/abstract/scopus_id/85103829199
  • Aledhari, M., Parizi, R.M., Dehghantanha, A., Choo, K.K. (2019). A Hybrid RSA algorithm in support of IoT greenhouse applications. Proceedings - IEEE International Conference on Industrial Internet Cloud, ICII 2019. 233-240. https://api.elsevier.com/content/abstract/scopus_id/85085936644
  • Aledhari, M., Joji, S., Hefeida, M., Saeed, F. (2019). Optimized CNN-based Diagnosis System to Detect the Pneumonia from Chest Radiographs. Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019. 2405-2412. https://api.elsevier.com/content/abstract/scopus_id/85084331555
  • Aledhari, M., Di Pierro, M., Saeed, F. (2018). A Fourier-Based Data Minimization Algorithm for Fast and Secure Transfer of Big Genomic Datasets. Proceedings - 2018 IEEE International Congress on Big Data, BigData Congress 2018 - Part of the 2018 IEEE World Congress on Services. 128-134. https://api.elsevier.com/content/abstract/scopus_id/85057766459
  • Aledhari, M., Marhoon, A., Hamad, A., Saeed, F. (2017). A New Cryptography Algorithm to Protect Cloud-Based Healthcare Services. Proceedings - 2017 IEEE 2nd International Conference on Connected Health: Applications, Systems and Engineering Technologies, CHASE 2017. 37-43. https://api.elsevier.com/content/abstract/scopus_id/85029361992
  • Aledhari, M., Hefeida, M.S., Saeed, F. (2016). A variable-length network encoding protocol for big genomic data. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 9674 212-224. https://api.elsevier.com/content/abstract/scopus_id/84978968786
  • Aledhari, M., Saeed, F. (2015). Design and Implementation of Network Transfer Protocol for Big Genomic Data. Proceedings - 2015 IEEE International Congress on Big Data, BigData Congress 2015. 281-288. https://api.elsevier.com/content/abstract/scopus_id/84959452732

    • Journal Article

  • Aledhari, M. (2024). Motion Comfort Optimization for Autonomous Vehicles: Concepts, Methods, and Techniques. Internet of Things. No. IEEE.
  • Aledhari, M., Razzak, R., Qolomany, B., Al-Fuqaha, A., Saeed, F. (2022). Biomedical IoT: Enabling Technologies, Architectural Elements, Challenges, and Future Directions. IEEE Access. 10 31306-31339. https://api.elsevier.com/content/abstract/scopus_id/85126555606
  • HaddadPajouh, H., Dehghantanha, A., M. Parizi, R., Aledhari, M., Karimipour, H. (2021). A survey on internet of things security: Requirements, challenges, and solutions. Other. 14 https://api.elsevier.com/content/abstract/scopus_id/85115019256
  • Aledhari, M., Razzak, R., Parizi, R.M. (2021). Machine learning for network application security: Empirical evaluation and optimization. Other. 91 https://api.elsevier.com/content/abstract/scopus_id/85101838345
  • Shahid, O., Nasajpour, M., Pouriyeh, S., Parizi, R.M., Han, M., Valero, M., Li, F., Aledhari, M., Sheng, Q.Z. (2021). Machine learning research towards combating COVID-19: Virus detection, spread prevention, and medical assistance. Other. 117 https://api.elsevier.com/content/abstract/scopus_id/85104356194
  • Yazdinejad, A., Parizi, R.M., Dehghantanha, A., Karimipour, H., Srivastava, G., Aledhari, M. (2021). Enabling Drones in the Internet of Things with Decentralized Blockchain-Based Security. Other. 8 (8) 6406-6415. https://api.elsevier.com/content/abstract/scopus_id/85097148493
  • Tariq, M.U., Haseeb, M., Aledhari, M., Razzak, R., Parizi, R.M., Saeed, F. (2021). Methods for Proteogenomics Data Analysis, Challenges, and Scalability Bottlenecks: A Survey. IEEE Access. 9 5497-5516. https://api.elsevier.com/content/abstract/scopus_id/85098771417
  • Yazdinejad, A., Srivastava, G., Parizi, R.M., Dehghantanha, A., Choo, K.K., Aledhari, M. (2020). Decentralized authentication of distributed patients in hospital networks using blockchain. Other. 24 (8) 2146-2156. https://api.elsevier.com/content/abstract/scopus_id/85085736060
  • Al-Fuqaha, A., Guizani, M., Mohammadi, M., Aledhari, M., Ayyash, M. (2015). Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications. Other. 17 (4) 2347-2376. https://api.elsevier.com/content/abstract/scopus_id/84941085241

    • Review, Journal

  • Aledhari, M., Razzak, R., Parizi, R.M., Saeed, F. (2020). Federated Learning: A Survey on Enabling Technologies, Protocols, and Applications. IEEE Access. 8 140699-140725. https://api.elsevier.com/content/abstract/scopus_id/85089512304
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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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