Khalil Al Hussaeni Headshot

Khalil Al Hussaeni

Associate Professor of Computing Sciences

RIT Dubai
Assistant Professor of Computing Sciences
kxacad@rit.edu

Khalil Al Hussaeni

Associate Professor of Computing Sciences

RIT Dubai
Assistant Professor of Computing Sciences

Education

Ph.D. in Electrical and Computer Engineering, Concordia University, Montreal (Canada) - 2017

Bio

Khalil Al Hussaeni is an Associate Professor of Computing Sciences at RIT Dubai. He received his Ph.D. degree in 2017 from the Faculty of Engineering and Computer Science, Concordia University, Montreal, Canada. His doctoral thesis proposed efficient and scalable techniques for anonymizing high-dimensional data. Dr. Al Hussaeni’s Ph.D. thesis was ranked “Outstanding” (highest honor at the university level), and he was nominated for the Governor General's Gold Medal Award (most prestigious academic award across Canada).

Dr. Al Hussaeni’s research interest goes under the umbrella of privacy-preserving data publishing. Particularly, this area of research targets anonymizing relational data, trajectories, data streams, and Big Data for various data mining tasks. He served as a reviewer for major venues, including The ACM International Conference on Information and Knowledge Management (CIKM), IEEE BigData, IEEE Transactions on Information Forensics and Security (TIFS), and IEEE Transactions on Knowledge and Data Engineering (TKDE).

Dr. Al Hussaeni was a member of the Data Mining and Security Laboratory research team at McGill University and a Research Assistant in the Computer Security Laboratory at Concordia University. He received his Master’s degree in Information Systems Security in 2009 from Concordia Institute for Information Systems Engineering, Concordia University, Canada. 

kxacad@rit.edu
Personal Links
ORCID
Google Scholar
Areas of Expertise
Data Privacy
Privacy-Preserving Data Publishing
Data Mining
AI Applications
Computer Forensics
Information Security

Select Scholarship

Selected peer-reviewed book chapters:

  • Al-Hussaeni, K., & Fung, B. C. (2025). (X, Y)-Privacy. In Encyclopedia of Cryptography, Security and Privacy (pp. 2799-2802). Cham: Springer Nature Switzerland.

Selected peer-reviewed conference papers:

  • Kanavos, A., Papadimitriou, O., Al-Hussaeni, K., Karamitsos, I., & Maragoudakis, M. (2024, December). Analyzing deep learning techniques in natural scene image classification. In 2024 IEEE International Conference on Big Data (BigData) (pp. 5682-5691). IEEE.
  • Kanavos, A., Vonitsanos, G., Karamitsos, I., & Al-Hussaeni, K. (2024, December). Exploring network dynamics: community detection and influencer analysis in multidimensional social networks. In 2024 IEEE International Conference on Big Data (BigData) (pp. 5692-5701). IEEE.

 Selected peer-reviewed journals:

  • Amawi, R. M., Al-Hussaeni, K., Keeriath, J. J., & Ashmawy, N. S. (2024). A Machine Learning Approach to Evaluating the Impact of Natural Oils on Alzheimer’s Disease Progression. Applied Sciences, 14(15), 6395.
  • Al-Hussaeni, K., Sameer, M., & Karamitsos, I. (2023). The impact of data pre-processing on hate speech detection in a mix of English and Hindi–English (code-mixed) tweets. Applied Sciences, 13(19), 11104.
  • Al-Hussaeni, K., Karamitsos, I., Adewumi, E., & Amawi, R. M. (2023). CNN-based pill image recognition for retrieval systems. Applied Sciences, 13(8), 5050.
  • Khokhar, R. H., Fung, B. C., Iqbal, F., Al-Hussaeni, K., & Hussain, M. (2023). Differentially private release of heterogeneous network for managing healthcare data. ACM Transactions on Knowledge Discovery from Data, 17(6), 1-30.
  • Al-Hussaeni, K., Fung, B. C., Iqbal, F., Dagher, G. G., & Park, E. G. (2018). SafePath: Differentially-private publishing of passenger trajectories in transportation systems. Computer Networks, 143, 126-139.
  • Al-Hussaeni, K., Fung, B. C., Iqbal, F., Liu, J., & Hung, P. C. (2018). Differentially private multidimensional data publishing. Knowledge and Information Systems, 56(3), 717-752.
  • Al-Hussaeni, K., Fung, B. C., & Cheung, W. K. (2014). Privacy-preserving trajectory stream publishing. Data & knowledge engineering, 94, 89-109.
  • Fung, B. C., Trojer, T., Hung, P. C., Xiong, L., Al-Hussaeni, K., & Dssouli, R. (2011). Service-oriented architecture for high-dimensional private data mashup. IEEE Transactions on Services Computing, 5(3), 373-386.

Currently Teaching

CSEC-464
Computer System Forensics
3 Credits
This course focuses on the fundamental incident response and computer forensics procedures for computer systems. Students will follow the forensics procedures and use forensically-sound tools to uncover the activities of computer users (deleted and hidden files, cryptographic steganography, illegal software, etc.). Students will also technologies to gather and preserve this evidence to ensure admissibility in court.
CSEC-499
Cooperative Education in CSEC
0 Credits
Students will gain experience and a better understanding of the application of technologies discussed in classes by working in the field of computing security. Students will be evaluated by their employer. If a transfer student, they must have completed one term in residence at RIT and be carrying a full academic load.
CSEC-790
MS Thesis
1 - 6 Credits
This course is one of the capstone options in the MS in Computing Security program. It offers students the opportunity to investigate a selected topic and make an original contribution which extends knowledge within the computing security domain. Students must submit an acceptable proposal to a thesis committee (chair, reader, and observer) before they may be registered by the department for the MS Thesis. Students must defend their work in an open thesis defense and complete a written report of their work before a pass/fail grade is awarded. As part of their original work, students are expected to write and submit an article for publication in a peer reviewed journal or conference.
ISTE-230
Introduction to Database and Data Modeling
3 Credits
A presentation of the fundamental concepts and theories used in organizing and structuring data. Coverage includes the data modeling process, basic relational model, normalization theory, relational algebra, and mapping a data model into a database schema. Structured Query Language is used to illustrate the translation of a data model to physical data organization. Modeling and programming assignments will be required. Note: students should have one course in object-oriented programming.
ISTE-260
Designing the User Experience
3 Credits
The user experience is an important design element in the development of interactive systems. This course presents the foundations of user-centered design principles within the context of human-computer interaction (HCI). Students will explore and practice HCI methods that span the development lifecycle from requirements analysis and creating the product/service vision through system prototyping and usability testing. Leading edge interface technologies are examined. Group-based exercises and design projects are required.
ISTE-436
Database Management and Access
3 Credits
Students will be introduced to issues in client/server database implementation and administration. Students will configure, test, and establish client-server communication and server-server communication with single and multiple database servers. Topics such as schema implementation, storage allocation and management, user creation and access security, backup and recovery, and performance measurement and enhancement will be presented in lecture and experienced in a laboratory environment. Students will configure and demonstrate successful communication between a database file server and multiple clients.
ISTE-470
Data Mining And Exploration
3 Credits
Rapidly expanding volumes of data from all areas of society are becoming available in digital form. High value information and knowledge is embedded in many of these data volumes. Unlocking this information can provide many benefits, and may also raise ethical questions in certain circumstances. This course provides students with a hands-on introduction to how interactive data exploration and data mining software can be used for data-driven knowledge discovery, including domains such as business, environmental management, healthcare, finance, and transportation. Data mining techniques and their application to large data sets will be discussed in detail, including classification, clustering, association rule mining, and anomaly detection. In addition, students will learn the importance of applying data visualization practices to facilitate exploratory data analysis.
ISTE-499
Undergraduate Co-op
0 Credits
Students perform paid, professional work related to their program of study. Students work full-time during the term they are registered for co-op. Students must complete a student co-op work report for each term they are registered; students also are evaluated each term by their employer. A satisfactory grade is given for co-op when both a completed student co-op report and a corresponding employer report that indicates satisfactory student performance are received.
MGIS-360
Building a Web Business
3 Credits
This course gives students both a conceptual and hands-on understanding of the launching of web businesses. Students will study the full process of web business creation, including domain name registration, frameworks for application creation, hosting of web applications and search engine optimization. Students will apply their knowledge by designing and building a business website that can actually make money.

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Website last updated: December 4, 2025