Bijan Raahemi
- Location
- DMS 6143
- Telephone
- 613-562-5800 x 4859
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Biography
Professor Raahemi received his Ph.D. in Electrical and Computer Engineering from the University of Waterloo, Canada, in 1997. Prior to joining the Telfer School of Management as a Professor in Management Information Systems and Technologies, Dr. Raahemi held several senior research positions in the telecommunications industry, including Nortel and Alcatel, focusing on computer networks architectures and services, dynamics of internet traffic, systems modelling and performance analysis.
Professor Raahemi's work has appeared in more than 85 peer-reviewed journals and conferences papers. He also holds eight patents in data communications. He is co-editor of the book “Handbook of Research on Data Science for Effective Healthcare Practice and Administration”. Dr. Raahemi received the Research Excellence Award, Established Researcher, Telfer School of Management in 2018. Professor Raahemi’s research are funded by grants from NSERC, MITACS, OCI, NRC, and CFI. His current research interests include artificial Intelligence, machine learning, data mining, big data analytics, their applications in business, and engineering, Information Systems and Technologies, and Data Communications Networks and Services. Dr. Raahemi established the Knowledge Discovery and Data mining (KDD) Research Laboratory compromising graduate students and researchers from multidisciplinary areas of Digital Transformation and Innovation, Systems Science, Computer Science and Engineering. The research projects in the KDD lab focus on two main streams: (a) novel techniques of data mining and machine learning with their emerging applications in business, healthcare, and engineering; and (b) Information systems and technologies, data communications networks and services.
Professor Raahemi is a registered member of Professional Engineers of Ontario (PEO), a senior member of the Institute of Electrical and Electronics Engineering (IEEE), and a member of the Association for Computing Machinery (ACM). He is also a member of Ottawa-Carleton Institute for Electrical and Computer Engineering (OCIECE), and Ottawa-Carleton Institute for Computer Science (OCICS).
Publications during the last 7 years
Papers in Refereed Journals
- Abedin, M.Z., Hayajneh, A., Raahemi, B. Pedagogical Use of Responsible Generative AI in Higher Education; Opportunities and Challenges: A Systematic Literature Review. AI in Education, 2(2): 11.
- Pham, T., Raahemi, B. An Adaptive Feature-Based Quantum Genetic Algorithm for Dimension Reduction with Applications in Outlier Detection. Algorithms, 18(3): 154.
- Motie, S., Raahemi, B. Financial fraud detection using graph neural networks: A systematic review. Expert Systems with Applications, 240(April 2024): 122156.
- Pham, T., Raahemi, B. Bio-Inspired Feature Selection Algorithms With Their Applications: A Systematic Literature Review. IEEE Access, 11: 43733-43758.
- Ashtiani, M.N., Raahemi, B. News-Based Intelligent Prediction of Financial Markets Using Text Mining and Machine Learning: A Systematic Literature Review. Expert Systems with Applications, 217.
- Raahemi, B., Obidallah, W.J. Special Issue in Blockchain Applications in Data Management and Governance. Data.
- Pishgoo, B., Akbari-Azirani, A., Raahemi, B. A Dynamic Feature Selection and Intelligent Model Serving for Hybrid Batch-Stream Processing. Knowledge-Based Systems, 256.
- Obidallah, W.J., Raahemi, B., Rashideh, W. Multi-Layer Web Services Discovery Using Word Embedding and Clustering Techniques. Data, 7(5): 57.
- Riahi-Madvar, M., Akbari-Azirani, A., Nasersharif, B., Raahemi, B. Subspace-based outlier detection using linear programming and heuristic techniques. Expert Systems with Applications, 207.
- Riahi, M., Akbari, A., Nasersharif, B., Raahemi, B. A new density-based subspace selection method using mutual information for high dimensional outlier detection. Knowledge-Based Systems, 216, ().
- Ashtiani, M.N., Raahemi, B. Intelligent Fraud Detection in Financial Statements using Machine Learning and Data Mining: A Systematic Literature Review. IEEE Access.
- Pishgoo, B., Akbari, A., Raahemi, B. A Hybrid Distributed Batch-Stream Processing Approach for Anomaly Detection. Information Sciences, 543: 309-327.
- Obidallah, W.J., Ruhi, U., Raahemi, B. Clustering and Association Rules for Web Service Discovery and Recommendation: A Systematic Literature Review. SN Computer Science, 1(27): 1-33.
Invited Contributions and/or Technical Reports
- <em>(Book review)</em> Raahemi, B.. 2026. "Deep Learning for Students: Concepts, Models, Coding and Exercises".
Funded Research during the last 7 years
| From-To | Source | Title | Purpose | Type | Role | Amount |
|---|---|---|---|---|---|---|
| 2025-2026 | MITACS and Nitrex | Enhancing Heat Treatment Processes through Machine Learning | R | O | PI | $120,000 |
| 2024-2024 | University of Ottawa, Office of the Provost | Excellence in Education Award | S | I | PI | $10,000 |
| 2023-2028 | NSERC - Discovery Grants Program | Reliable AI for Outlier Detection in Unstructured Data with Applications in Engineering and Business | R | C | PI | $250,000 |
| 2023-2026 | SSHRC Partnership Development Grant | Enabling Systems Transitions Towards Inclusive Innovation | R | C | Co-I | $198,793 |
| 2020-2022 | OCE and Ciena | Smart Factory | R | O | PI | $150,000 |
| 2018-2019 | MITACS and Bell Canada | Network Traffic Classification for Cyber Threat and Malware Detection | R | C | PI | $50,000 |
| 2017-2023 | NSERC - Discovery Grants Program | Outlier Detection in High-Dimensional Big Data using Bio-Inspired Methods for Emerging Applications in Engineering, Healthcare, and Business | R | C | PI | $120,000 |
| 2016-2019 | MITACS and ICES | Mining of population-based routinely collected health data to determine risk factors associated with pediatric morbidity in Ontario. | R | O | PI | $90,000 |
LEGEND:
Purpose
C: Contract (R and D) | E: Equipment Grant | R: Research Grant | S: Support Award | P: Pedagogical Grant | O: Other, U: Unknown
Type
C: Granting Councils | G: Government | F: Foundations | I: UO Internal Funding | O: Other | U: Unknown
Role
PI = Principal Investigator | Co-I = Co-Investigator | Co-PI = Co-Principal Investigator
