Chair, Professor, Undergraduate & Graduate Program Director
EEC 256A
(205) 975-0391
Research and Teaching Interests: Component-based software architecture, mobile and cloud computing, internet of things, machine learning
Office Hours: By appointment
Education:
- B.S., Manhattan College, Electrical Engineering
- M.S., Georgia Institute of Technology, Electrical Engineering
- M.S., Polytechnic University, Computer Science
- Ph.D., New Jersey Institute of Technology, Computer Science
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Recent Courses
- Mobile Computing
- Cloud Computing
- Internet of Things
- Basic Data Analytics and Machine Learning
- Introduction to Neural Networks
- Machine Learning in Engineering
- Introduction to Big Data Analytics
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Select Publications
- Bowman, A. D., & Jololian, L., “Introduction to artificial intelligence and machine learning algorithms,” Artificial Intelligence in Tissue and Organ Regeneration, Academic Press, pp. 15-28, 2023.
- Alzahrani, E., Al Qurashi, M., & Jololian, L., “Comparative analysis of the use of pre-trained models to profile authors’ ages and genders,” 2nd International Conference on Computing and Machine Intelligence (ICMI) pp. 1-7, 2022.
- Alharthi, A., Alhefdi, M., & Jololian, L., “Value-based modeling of an addiction recovery healthcare system,” IEEE SoutheastCon 2022, pp. 227-232, 2022.
- Alolaiwy, M., Tanik, M., & Jololian, L., “Crowd path trajectory prediction using least action principle,” IEEE SoutheastCon 2022, pp. 151-157, 2022.
- Bowman, A. D., Prabhakar, S. P., & Jololian, L., “A framework for an automated development environment to support the data-driven machine learning paradigm,” IEEE SoutheastCon 2022, pp. 329-331, 2022.
- Skidmore, F. M., Monroe, W. S., Hurt, C. P., Nicholas, A. P., Gerstenecker, A., Anthony, T., Jololian, L., et al., “The emerging postural instability phenotype in idiopathic Parkinson disease,” npj Parkinson's Disease, 8(1), 28, 2022.
- Lipscomb, M. M., Mohammad, A., Alharthi, A., & Jololian, L., “Value-based modeling for mobile health application development,” Mhealth, 8, AME Publications, 2022.
- Alolaiwy, M., Tanik, M., & Jololian, L., “From CNNs to adaptive filter design for digital image denoising using reinforcement q-learning,” IEEE SoutheastCon 2021, pp. 1-8, 2021.
- Karpurapu, B. S. H., & Jololian, L. “A framework for social network sentiment analysis using big data analytics,” In Big Data and Visual Analytics, Springer, pp. 203-217, 2017.
- Schoepp, K, Danaher, M., Jololian, L., “Effective Alignment of Disciplinary and Institutional Accreditation and Assessment: A UAE Computing Case Study,” Book Chapter in Advances in Engineering Education in the Middle East and North Africa: Current Status, and Future Insights, Springer International Publishing, pp. 343-363, 2016.
- • Said, H. E., Guimaraes, M. A., Maamar, Z., & Jololian, L. “Database and database application security,” ACM SIGCSE Bulletin, 41(3), pp. 90-93, 2009.
- Jololian, L., “Towards Semantic Integration of Components Using a Service-Based Architecture,” Journal of Integrated Design & Process Science, September 2005, Vol. 9, No. 3, pp. 1-13.
- Jololian, L. and Tanik, M., 2001, “A Framework for a Meta-Semantic Language for Smart Component-Adapters,” J. Systems Integration, Vol. 10, No. 3, pp. 269-297.
- Rossak, W., Kirova, V., Jololian, L., Lawson, H., and Zemel, T., 1997, “A Generic Model for the Use and Specification of Software Architecture,” IEEE Software, Vol. 14, No. 4, pp. 84-92.