- DMS 6143
- 613-562-5800 x 4859
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- Data Communications Services; and Service Oriented Organizations
- Data Mining, Machine Learning, and Big Data Analytics with Applications in Business, Healthcare, and Engineering
- Information Systems
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 an Associate Professor in Management Information Systems and Technology, Dr. Raahemi held several 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 peer-reviewed journals and conferences papers. He also holds several patents in data communications. His current research interests include data mining and knowledge discovery, information systems, business intelligence, data communications networks and services, service oriented architecture, systems modelling, and performance analysis. Dr. Raahemi established the Knowledge Discovery and Data mining (KDD) Research Laboratory compromising graduate students and researchers from multidisciplinary areas of E-Business Technology, Systems 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, data communications, and service oriented organizations.
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
Chapters in Books
Asgharian, Z., Asgharian, H., Akbari, A. and Raahemi, B. Detecting Denial of Service Attacks on SIP Based Services and Proposing Solutions. In Kabiri, P.. Privacy, Intrusion Detection and Response: Technologies for Protecting Networks . Pennsylvania, USA: IGI Global Publishers, 2011.
Papers in Refereed Journals
Obidallah, W. and Raahemi, B. 2017. Managing Changes in Service Oriented Virtual Organizations: A Structural and Procedural Framework to Facilitate the Process of Change. Journal of Electronic Commerce in Organizations, 15(1): 59-83.
Shangying, X. and Raahemi, B. 2016. A Semantic-Based Service Discovery Framework for Collaborative Environments. International Journal of Simulation Modelling, 15(1): 83-96.
Mohammadi, M., Raahemi, B. and Akbari, A. 2015. A Geometric Density-based Sample Reduction Method. Intelligent Data Analysis: An International Journal, 19(6): 1233-1257.
Tekieh, M., Raahemi, B. and Izadshenas, S.A. 2015. Analyzing Healthcare Coverage using Data Mining Techniques. International Journal of Society Systems Science, 7(3): 198-221.
Asgharian, H., Akbari, A. and Raahemi, B. 2015. Feature Engineering for Detection of Denial of Service Attacks in Session Initiation Protocol. Journal of Security and Communication Networks, 8(8): 1587-1601.
Bigdeli, E., Mohammadi, M., Raahemi, B. and Matwin, S. 2015. A Fast and Noise Resilient Cluster-based Anomaly Detection. Journal of Pattern Analysis and Applications.
Mohammadi, M., Mehraban, S.A., Bigdeli, E., Raahemi, B. and Akbari, A. 2015. An enhanced noise resilient K-associated graph classifier. Expert Systems with Applications, 42(21): 8283-8289.
Mohammadi, M., Al-Azab, F., Raahemi, B., Richards, G.S., Jaworska, N., Smith, D.C., de la Salle, S., Blier, P. and Knott, V. 2015. Data Mining EEG Signals in Depression for their Diagnostic Value. BMC Medical Informatics and Decision Making, 15(1): 108.
Mohammadi, M., Akbari, A., Raahemi, B., Nasersharif, B. and Asgharian, H. 2014. A fast anomaly detection system using probabilistic artificial immune algorithm capable of learning new attacks. Evolutionary Intelligence, 6(3): 135-156.
Izadshenas, S.A., Raahemi, B., Tekieh, M.H. and Kuziemsky, C.E. 2014. Identifying High-cost Patients using Data Mining Techniques and a Small Set of Non-trivial Attributes. Computers in Biology and Medicine, 53(1): 9-18.
Roodaki, M., Raahemifar, K. and Raahemi, B. 2014. Analysis of Quality of Services in LTE and Mobile WiMax. Computers & Electrical Engineering, 40(5): 1508-1523.
Zhong, W., Raahemi, B. and Liu, J. 2013. Classifying Peer-to-Peer Applications Using Imbalanced Concept-Adapting Very Fast Decision Tree on IP Data Stream. Peer-to-Peer Networking and Applications, 6(3): 233-246.
Danesh, M.H., Raahemi, B., Kamali, S.M.A. and Richards, G.S. 2013. A Framework for Process and Performance Management in Service Oriented Virtual Organizations. International Journal of Computer Information Systems and Industrial Management, 5: 203-215.
Tavakoli, E., Tabandeh, M., Kaffash, S. and Raahemi, B. 2013. Multi-hop communications on wireless network-on-chip using optimized phased-array antennas. Computers & Electrical Engineering, 39(7): 2068-2085.
Mohammadi, M., Raahemi, B., Akbari, A. and Nassersharif, B. 2012. New Class-Dependent Feature Transformation for Intrusion Detection Systems. Journal of Security and Communication Networks, 5(12): 1296-1311.
Mohammadi, M., Raahemi, B., Akbari, A., Nassersharif, B. and Moinzadeh, H. 2012. Improving Linear Discriminate Analysis with Artificial Immune System-Based Evolutionary Algorithms. Journal of Information Science, 189: 219-232.
Liu, P., Raahemi, B. and Benyoucef, M. 2011. Knowledge Sharing in Dynamic Virtual Enterprises: A Socio-Technological Perspective. Knowledge-Based Systems Journal, 24(3): 427-443.
Mohammadi, M., Raahemi, B., Akbari, A., Moeinzadeh, H. and Nasersharif, B. 2011. Genetic Based Minimum Classification Error Mapping for Accurate Identifying Peer-to-Peer Applications in the Internet Traffic. Expert Systems with Applications, 38(6): 64l7-6423.
Raahemi, B. and Mumtaz, A. 2010. Classification of Peer-to-peer Traffic Using a Two-stage Window-based Classifier with Fast Decision Tree and IP Layer Attributes. International Journal of Data Warehousing and Mining, 6(3): 28-42.
Other Scholarly Contributions
(Book review) Raahemi, B. 2011. "Business Driven Information Systems (McGraw-Hill Ryerson)".
Funded Research during the last 7 years
|2017-2021||NSERC||Outlier Detection in High-Dimensional Big Data using Bio-Inspired Methods for Emerging Applications in Engineering, Healthcare, and Business (PI)||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|
|2015-2016||Ontario Ministry of Energy, and NSERC||SecCharge: Secure Electric Vehicle Ecosystem for Smart Grid||C||C||Co-I||$ 3,090,800|
|2015||NSERC Engage||Capturing and Analyzing Data from SensorSuite's Devices using Big Data Analytics Techniques||R||C||PI||$ 25,000|
|2014||MITACS Cluster and IBM||An Integrated Approach using Process Models and Business Analytics for Efficient Delivery of Patient Care||R||O||Co-I||$ 120,000|
|2014||NSERC Engage||Capturing and analyzing data from Giatec's testing devices using web applications||R||C||PI||$ 23,250|
|2012-2017||NSERC||Feature Engineering using Bio-Inspired Methods for the Internet Data Analytics||R||C||PI||$ 105,000|
|2011-2012||MITACS and IBM||Design and Implementation of a Framework for Performance Management in Service Oriented Virtual Organization||R||O||PI||$ 30,000|
|2007-2011||NSERC||Stream Data Mining in Telecommunication Industry with Privacy Preserving Consideration||R||C||PI||$ 45,000|
|2007-2011||CFI / ORF||Knowledge Discovery and Data Mining Laboratory at the School of Management||R||C||PI||$ 39,102|
*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