Enayat Rajabi



I am currenlty an Assistant Professor of Data Analytics at Shannon School of Business, Cape Breton University in Sydney, Canada. I am also an Adjunct Professor at Dalhsouie University , Affiliate Scientist at Nova Scotia Health , and a researcher in machine learning at Halmstad University . I provide Data Science consultancy for different companies as well.

Assistant Professor in Data Analytics

  • Ph.D.: Information and Knowledge Engineering
  • Master: Software Engineering
  • Bachelor: Software Engineering
  • Research Interests: Machine Learning, Knowledge Engineering

I was a postdoctoral fellow at Dalhousie University. I received my PhD in “Information and Knowledge Engineering” from University of Alcala in Spain. I participated in different European research projects during my PhD and published several JCR papers in Computer Science journals (Google Scholar).


Enayat Rajabi

  • Knowledge of Data Analytics, Data Visualization, Knowledge Engineering, and Semantic Web
  • Experienced in teaching computer science and data analytics courses at graduate and undergraduate level
  • Awarded NSERC Discovery Grant and Mitacs Research Training


PhD in Information and Knowledge Engineering

2012 - 2015

Univeristy of Alcala, Alcala de Henares, Spain

  • Thesis title: Interlinking educational data to Web of Data
  • Thesis mark: Excellent (Cum Laude)

Master of Software Engineering

2001 - 2004

Ferdowsi University of Mashhad, Iran

  • Thesis title: Developing a management information system to manipulate Jini Home Networks
  • Thesis mark: Excellent (20 out of 20)
  • GPA: 18.24 out of 20 (32 Units)
  • Award: First ranked student

Bachelor of Software Engineering

1997 - 2001

Razi University of Kermanshah, Iran

  • Thesis title: Implementation of an ISP accounting system for university
  • Thesis mark: Excellent (19.5 out of 20)
  • GPA: 15.65 out of 20 (140 Units)
  • Award: Second ranked student

Professional Experience

Tenure-track Assistant Professor of Data Analytics

2019 - Present

Shanon School of Business, Cape Breton University, Canada

  • Teaching Data Analytics courses in Business Analytics program
  • Research in Data Analytics and Semantic Web

Data Scientist

2017 - 2019

REDspace, Halifax, Canada

  • Developed several Big Data analytics dashboards
  • Experinced working with Databricks, PySpark and machine learning techniques

Postdoctoral Fellow

2015 - 2017

Faculty of Computer Science, Dalhsouie Univeristy

  • Researched on a semantic data analytics framework in healthcare systems
  • Experinced in developing mobile and web applications in healthcare

Research Assistant

2012 - 2015

Univeristy of Alcala, Alcala de Henares, Spain

  • Researched on Semantic Web and Linked Data projects
  • Developed several Linked Data platforms in different European projects including Open Discovery Space project (http://www.opendiscoveryspace.eu)

Full-time Instructor

2009 - 2012

Islamic Azad University of Saveh, Iran

  • Taught computer science courses
  • Researched on Semantic Web and Linked Data

Research Projects

NSERC Discovery Grant

2020 - 2025
  • Title: Semantic Web Analysis over the Nova Scotia Open Data
  • Amount: $ 156,000
  • Research assistants: Devanshika Gosh, Rishi Midha, Tamanna Moharana, Chandrayog Yadav, Karishma Kumar

New Health Investigator Grant - Research Nova Scotia

2022 - 2024
  • Title: Identifying Alternate Level of Care (ALC) Patients Levergaing Machine Learning Algorithms
  • Amount: $ 97,418
  • Research assistants: TBD

Mitacs Globalink - Mitacs

  • Title: Graph Neural Network Using Knowledge Graphs
  • Amount: $ 4,250
  • Interns: Debjit Sarkar and Saloni Rakholiya

CBU RISE grant

  • Title: Explainable Clinical Decision Support System using Knowledge Graph
  • Amount: $ 7,600
  • Research assistants: TBD

Industrial Research Assistance Program (IRAP)

2020 - 2021
  • Title: Predicting healing time on a Wound dataset using feature engineering techniques
  • Budget: $ 5,000
  • Research assistants: Tressy Thomas, Ankit Anand

CBU RISE grant

  • Title: Multi-label Text Class Classification Using Knowledge Graphs
  • Amount: $ 7,800
  • Research assistants: Divya Prabhu, Muhan Kumar Ganta, and Tressy Thomas

Mitacs Research Training Award

2020 - 2021
  • Title: Building a Knowledge Graph on Top of Open Statistical Data
  • Amount: $ 6,000
  • Research assistants: Rishi Midha

CBU RISE grant

  • Title: Data Imputation using KNN Algorithm
  • Amount: $ 7,400
  • Research assistants: Tressy Thomas

Industrial Research Assistance Program (IRAP)

2019 - 2020
  • Title: Building a data analytics dashboard on how2trak database in clinical practice
  • Amount: $ 5,000
  • Research assistants: Devanshika Gosh


Journal papers:

  • Gomes Jr, J., Bernardino3 H.S., Francisco de Souza, J.,Rajabi, E. (2022). Indexing, enriching, and understanding Brazilian missing person cases from data of distributed repositories on the web, , AI & Society. doi: https://doi.org/10.1007/s00146-022-01456-5
  • Rajabi, E., Sahebari, M., Tressy, T. (2022). Analyzing Systemic Lupus Erythematosus Publications using Neural-Network-based Multi-Label Classification Algorithms, Lupus doi: https://doi.org/10.1177/09612033221093548 .
  • Nadeau, J., Wardley, L. J., & Rajabi, E. (2021). Tourism destination image resiliency during a pandemic as portrayed through emotions on Twitter, Tourism and Hospitality Research Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1177/14673584211038317
  • Thomas, T. and Rajabi, E. (2021). A systematic review of machine learning-based missing value imputation techniques, Data Technologies and Applications Vol. 55 No. 4, pp. 558-585. https://doi.org/10.1108/DTA-12-2020-0298
  • Rajabi, E. (2020). Towards Linking Government Data in Canada, International Journal of Metadata, Semantics, and Ontologies, vol. 14, No. 3, pp. 209-217.
  • Rajabi, E., Sanchez-Alonso, S. (2019). Knowledge Discovery using SPARQL Property Path: The Case of Disease Dataset, Journal of Information Science (JIS), published online: https://doi.org/10.1177/0165551519865495 .
  • Rajabi, E., Greller, W. (2019), Exposing Social Data as Linked Data in Education, International Journal of Semantic Web and Information System, 15(2), 92-106. doi:10.4018/IJSWIS.2019040105.
  • Rajabi, E., Sanchez-Alonso S., Sicilia M.-A., Manouselis N. (2015). A linked and open dataset from a network of learning repositories on organic agriculture, British Journal of Educational Technology, published online: ,doi:10.1111/bjet.12341.
  • Rajabi, E., Vogias K., Sanchez-Alonso S., Hatzakis I. (2015). e-Learning Object Ingestion in an Open Educational Environment. Bulletin of the IEEE Technical Committee on Learning Technology, vol. 12, No. 1-2, pp. 14-17.
  • Rajabi, E., Sicilia M.-A., Sanchez-Alonso S. (2015). Interlinking Educational Resources to Web of Data through IEEE LOM. Computer Science and Information Systems, vol. 12, no. 1, pp. 233–255. https://doi.org/10.2298/CSIS140330088R
  • Rajabi, E., Sicilia M.-A., Sanchez-Alonso S. (2015). Discovering Duplicate and Related Resources using Interlinking Approach: The case of Educational Datasets, Journal of Information Science , vol. 41, no. 3, pp. 329-341. https://doi.org/10.1177/0165551515575922
  • Valiente M-C., Sicilia M.-A., E. Garcia-Barriocanal, Rajabi, E. (2015). Adopting the metadata approach to improve the search and analysis of educational resources for online learning, Computers in Human Behavior, vol. 51, pp. 1134-1141. https://doi.org/10.1016/j.chb.2014.12.059
  • Rajabi, E., Sicilia M.-A., Sanchez-Alonso S. (2015). Interlinking Educational Data: An Experiment with Engineering-related Resources in GLOBE , International Journal of Engineering Education , vol. 31, no. 3, pp. 893-900.
  • Rajabi, E., Sicilia M.-A., Sanchez-Alonso S. (2014). An Empirical Study on the Evaluation of Interlinking Tools on the Web of Data, Journal of Information Science, vol. 40, No. 5, pp. 637-648. https://doi.org/10.1177%2F0165551514538151
  • Rajabi, E., Sanchez-Alonso S., Sicilia M.-A. (2014). Analyzing Broken Links on the Web of Data: An Experiment with DBpedia, Journal of the Association for Information Science and Technology (JASIST), vol. 65, no. 8, pp. 1721-1727. https://doi.org/10.1177%2F0165551514538151

Conference papers:

  • Cabunagan-Cinco G.J., Rajabi, E., Nowaczyk S. (2022), Cluster Analysis on Sustainable Transportation: The Case of New York City Open Data 2022 International Conference on Applied Artificial Intelligence (ICAPAI) | Halden, Norway. https://doi.org/10.1109/ICAPAI55158.2022.9801569
  • Rajabi E., Nowaczyk S., Pashami S., and Bergquist M. (2022), An Explainable Knowledge-based AI Framework for Mobility as a Service, The 34th International Conference on Software Engineering & Knowledge Engineering | Pittsburgh, USA. https://doi.org/10.18293/SEKE2022-020
  • Ghosh, D., Rajabi, E. (2022). KG-Visual: A Tool for Visualizing RDF Knowledge Graphs. In Research Conference on Metadata and Semantics Research | Online, pp. 126-136. https://doi.org/10.1007/978-3-030-98876-0_11
  • Rajabi, E., Sravani, K., Shekarpour S. (2021). Analysis of Scientific Literature of LDOW Workshops: A Scientometric and NLP approach. 2nd Workshop on Data and Research Objects Management for Linked Open Science | Online, pp. 1-10. https://doi.org/10.4126/FRL01-006429416
  • Rajabi, E., & Etminani, K. (2021). Towards a Knowledge Graph-Based Explainable Decision Support System in Healthcare. Studies in health technology and informatics, 281, 502–503. https://doi.org/10.3233/SHTI210215
  • Sanchez-Alonso S., Sicilia M.-A., Rajabi, E., Cantallops M.-M., García Barriocanal E. (2020) Class and Instance Equivalences in the Web of Linked Data: Distribution and Graph Structure, MTSR 2020, pp. 13-21.
  • Rajabi, E., Debruyne C., O’sullivan D. (2017). Towards a Personalized Query Answering Framework on the Web of Data, Linked Data on the Web (LDOW2017), WWW 2017, Perth, Australia, Apr. 2017.
  • Rajabi, E., Abidi, SSR. (2017). Discovering Central Practitioners in a Medical Discussion Forum using Semantic Web Analytics, Informatics for Health 2017, Manchester Central, UK, Apr. 2017. https://pubmed.ncbi.nlm.nih.gov/28423840/
  • Fazeli, S., Rajabi, E., Lezcano L., Drachsler H., Sloep, P. (2016). Supporting Users of Open Online Courses with Recommendations: An Algorithmic Study, Advanced Learning Technologies (ICALT), 16th International Conference on , Austin, Texas, USA. doi: 10.1109/ICALT.2016.119
  • Rajabi, E., Marenzi I. (2015). Linking a Community Platform to the Linked Open Data Cloud, Learning & Education with the Web of Data (LILE) workshop, WWW2015, pp. 701-703. https://doi.org/10.1145/2740908.2741742
  • Rajabi, E., Sicilia M.-A., Sánchez-Alonso S. (2013). Interlinking educational data: an experiment with GLOBE resources, The First International Conference on Technological Ecosystem for Enhancing Multiculturality (TEEM 2013), pp. 339-348, Salamanca, Spain. https://doi.org/10.1145/2536536.2536588
  • Rajabi, E., Sicilia M.-A., Sanchez-Alonso S. (2013). A Simple Approach towards SKOSification of Digital Repositories, Metadata and Semantics Research (MTSR 2013), vol. 390, pp. 67-74. https://link.springer.com/chapter/10.1007/978-3-319-03437-9_8
  • Rajabi, E., Greller W., Niemann K., Kastrantas K., Sanchez-Alonso S. (2013). Social data interoperability in educational repositories and federations, International Journal of Metadata, Semantics and Ontologies, vol. 8, no. 2, pp. 169-178. https://doi.org/10.1504/IJMSO.2013.056606
  • Sicilia M.-A., Sánchez-Alonso S., Garcia-Barriocanal E., Minguillón J., Rajabi, E. (2013). Exploring the keyword space in large learning resource aggregations: the case of GLOBE, LACRO Workshop, LAK 2013.
  • Rajabi, E., Kahani M. (2003). In Home Network Management, 3rd Electrical & Computer Conference, Kermanshah, Iran.
  • Rajabi, E., Kahani M. (2002). Comparison of Software and Hardware Home Networking Technologies, National Computer Conference NCC2002, Mashhad, Iran, (In Persian).

Poster and abstract papers:

  • Rajabi, E., Wardley L. J., Nadeau, J., Levallet, N., O’Reilly, N., (2020). Analysis of Tourist Emotions Shared in Social Media: The Case of Mount Kilimanjaro, Administrative Sciences Association of Canada (ASAC), Virtual conference (Abstract).
  • Rajabi, E., Kahani M., Sicilia M.-A. (2012). Trustworthiness of Linked Data Using PKI , 21st International World Wide Web Conference, Lyon, France.
  • Rajabi, E., Kahani M. (2011). Designing a Step-by-step User Interface for Finding Provenance Information over Linked Data, 11th International Conference on Web Engineering (ICWE 2011), vol. 6757, pp. 403-406, Paphos, Cyprus. https://link.springer.com/chapter/10.1007/978-3-642-22233-7_36
  • Rajabi, E., Kahani M. (2004). Design of an MIB for the management of Jini-based Home Networks, 9th CSI Computer Conference, Tehran, Iran.

Book chapters:

  • Rajabi, E., Beheshti S. (2016). Interlinking Big Data to Web of Data, in book Big Data Optimization: Recent Developments and Challenges, Edited by Professor Ali Emrouznejad, Springer, Birmingham, UK, May 2016. https://doi.org/10.1007/978-3-319-30265-2_6
  • Amirian E., Rajabi, E., (2009). Database Systems, Sarafraz Publishing , First edition.


I have taught several courses in computer science domain. The following courses, however, are my formal teaching experience in Canada:

Predictive Analytics (MGSC 5125)

2020 - present
  • Course objectives:
    • students will learn how to discover interesting things and reveal valuable information from data by selecting a proper model
    • apply machine learning methods to build predictive models and discover patterns in data
    • learn diverse kinds of regressions (linear, nonlinear, and logistic)
    • learn four modeling techniques will be used: k-nearest neighbors, classification, and regression trees .
  • Software: Python
  • Material for learning:
    • Slides as well as practical examples will be provided alongside the textbook in the class
    • Textbook 1: Abbott, D. Applied Predictive Analytics: Principles and Techniques for the Professional Data Analyst. 2014.
    • Textbook 2: Hastie, T., Tibshirani, R., & Friedman, J. The elements of statistical learning: data mining, inference, and prediction (12th Edition). Springer Science & Business Media, 2017.
    • Textbook 3: Witten, I. H., Frank, Eibe, Hall, Mark A. Data Mining: Practical Machine Learning Tools and Techniques. 1884-1970.; Palestro, Christopher J.

Database Concepts (MGSC 5106)

2019 - present

Data Visualization (MGSC 5127)

2019 - present
  • Course objectives:
    • understand different concepts of visualization
    • learn how to design graphs using visualization tools
    • learn how to choose an appropriate graph for a problem
    • become familiar with some of tools used for data visualization tools
  • Software: Tableau, Excel, D3, and Python visualization libraries
  • Textbooks:
    • Data Visualization Made Simple: Insights into Becoming Visual, Sosulski, K. New York: Routledge, 2018.
    • Visualization Analysis and Design, Munzner, T. AK Peters Visualization Series, CRC Press, 2014.
    • Storytelling with data: A Data Visualization Guide for Business Professionals, Knaflic, C. Wiley, 2015.
  • Material for learning:

Quantitative Methods (MGSC 5113)

2019 - present
  • Course objectives:
    • demonstrate their understanding of basic quantitative techniques
    • learn how quantitative methods can be used to solve managerial problems
    • learn to use IS tools (e.g. MS Excel) can be used in solving business problems
  • Software: Excel
  • Textbooks:
    • Quantitative Analysis for Management,13th Edition, Render, Stair and Hanna, Custom Edition for Cape Breton University. Companion Website: http://wps.prenhall.com/bp_render_qam_11/
    • Quantitative Methods for Business, 13th Edition, D. R. Anderson, D. J. Sweeney, & T. A. Williams.

Open positions

You can find the available positions below. Please read the requirements carefully.

Postdoctoral fellow position

For this position, we are looking for a motivated PostDoc candidate who is interested in applying his/her computational skills to real-world healthcare problems. This position will be initially available for one year. The grade of appointment will be accorded based on candidate’s academic qualifications and years of relevant experience.
  • Requirements:
    • Ph.D. in computer science, or a related field with a research focus on machine learning
    • Great interpersonal communication, creative thinking, and problem-solving ability
    • Demonstrated record of high-quality publications in the field of machine learning
    • Demonstrated analytical, verbal, and scientific writing skills
    • Demonstrated record of high-performance scientific programming with python
    • Working on the healthcare projects will be an asset.
  • Responsibilities
    • Major responsibility of the selected candidate is to develop machine learning models (i.e. neural networks) to solve healthcare challenges. The selected candidate will also be involved in managing, extracting and pre-processing data for various projects.
  • Place of work
    • In accordance with Canadian Employment and Immigration guidelines, applicants must be eligible to work in Canada.
    • The applicant must be in Nova Scotia province during the employment.
  • How to apply
    • Send an email with subject “postdoc-ML-2022” with the following documents to enayat_rajabi@cbu.ca: CV, cover letter, and two sample publications.
    • Employment start date to be mutually agreed. Please submit your application by 2022/06/31.



1250 Grand Lake Dr., Sydney, NS B1P 6L2


+1 902 563 1180