Research

Research Interests

  • Applied Machine Learning

  • Distributed Machine Learning

  • Distributed Computing: Cloud Computing, Edge Computing

My Current and Previous Projects

Current

  • Application of machine learning in healthcare - with the focus on diagnosing tropical diseases.

  • Distributed machine learning on resource constrained devices (wearable, IoT, Sensor, cellphones).

  • Machine learning for social challenges

  • Performance analysis of big data applications.

Previous

  • Application of natural language processing in healthcare - extracting structural records from free-text reports.

  • Application of machine learning in healthcare - with the focus on cancer diagnoses.

  • Performance analysis of cloud-based applications.

Publications

Publications a PresentationsThe name of students participated in research publications are marked with (*).

  • Saba F. Lameh*, Wade Noble*, Yasaman Amannejad, Arash Afshar, "Analysis of Federated Learning as a Distributed Solution for Learning on Edge Devices", The International Conference on Intelligent Data Science Technologies and Applications (IDSTA2020), Oct. 2020.

  • Sarah Shah*, Yasaman Amannejad, Diwakar Krishnamurthy, & Mea Wang (2020). PERIDOT: Modeling Execution Time of Spark Applications, Submitted to Elsevier Big Data Research, Jun. 2020.

  • Petter Morrison*, Xia Wang*, Myka Estes, Behnam Sharif, Eileen Shaw, Tara Cowling, Json Tay, Victor Jimenez-Zepeda, Behrouz Far, Yasaman Amannejad, Towards Standardized Structured Reporting for the Management of Multiple Myeloma in Alberta: Insights in Application of Machine Learning, CADTH Symposium, Apr. 2020. (Poster, Video).

  • Xia Wang*, Behnam Sharif, Eileen Shaw, Tara Cowling, Jason Tay, Victor Jimenez-Zepeda, Yasaman Amannejad, "From unstructured clinical data to standardized structured records: An application of NLP on multiple myeloma laboratory data in Alberta" , Women in Data Science (WiDS) Conference, Mar. 2020.

  • Mahmood Moussavi, Yasaman Amannejad, Mohammad Moshirpour, Emily Marasco, and Laleh Behjat, "Importance of Data Analytics for Improving Teaching and Learning Methods", Data Management and Analysis, Springer, 2020.

  • Sarah Shah*, Yasaman Amannejad, Diwakar Krishnamurthy, Mea Wang, "Quick Execution Time Predictions for Spark Applications," Proceedings of the 15th International Conference on Network and Service Management (CNSM 2019), Halifax, NS, Oct.2019.

  • Yasaman Amannejad, Diwakar Krishnamurthy, and Behrouz Far, "Prospective: A Data-Driven Technique to Predict Web Service Response Time Percentiles," IEEE Access, Sep. 2019.

  • Yasaman Amannejad, Sarah Shah*, Diwakar Krishnamurthy, Mea Wang, "Fast and Lightweight Execution Time Predictions for Spark Applications", Proceedings of the IEEE International Conference on Cloud Computing (IEEE CLOUD 2019), Jul. 2019.

  • Yasaman Amannejad, R. Connolly, “The Decade of Machine Learning: A Non-Specialist Guide to Machine Learning”, Presented at Liberal Education Conference (LibEd 2019), Calgary, Canada, May 16-18, 2019.

  • Terrence Plunkett*, Peter Morrison*, Yasaman Amannejad, “Web Accessibility Analysis of Western Canadian Universities: Do Accessibility Services Offer Accessible Websites?”, (Winner of Poster Prize at Faculty of Science Research, Mount Royal University, 2019).

  • Emily Ann Marasco, Mohammad Moshirpour, Mahmood Moussavi, Laleh Behjat, Yasaman Amannejad, "Evidence-Based Best Practices for First-Year Blended Learning Implementation", American Association for Engineering Education (ASEE 2018), 2018.

  • Yasaman Amannejad, Diwakar Krishnamurthy, Behrouz Far, “Predicting Web Service Response Time Percentiles,” Proceedings of the International Conference on Network and Service Management (CNSM 2016), October-Nov. 2016.

  • Yasaman Amannejad, Diwakar Krishnamurthy, Behrouz Far, “Managing Performance Interference in Cloud-Based Web Services,” IEEE Transactions on Network and Service Management (TNSM), Jul. 2015.

  • Yasaman Amannejad, Diwakar Krishnamurthy, Behrouz Far, “Detecting Performance Interference in Cloud-Based Web Services,” Integrated Network Management (IM 2015), May 2015 (*Received Best Paper Award).

  • Vahid Garousi, Yasaman Amannejad, and Aysu Betin Can, “Software test-code engineering: A systematic mapping,” Elsevier, Information and Software Technology (INFSOF), 2014.

  • Yasaman Amannejad, Mohammad Moshirpour, Behrouz Far, Reda Alhajj, “From Requirements to Software Design: An Automated Solution for Packaging Software classes,” IEEE IRI 2014, 2014.

  • Zahara Sahaf, Vahid Garousi, Dietmar Pfahl, Rob Irving, Yasaman Amannejad, “When to Automate Software Testing? Decision Support based on System Dynamics - An Industrial Case Study,” ACM International Conference on Software and Systems Process (ICSSP), 2014, pages 149-158.

  • Yasaman Amannejad, Fatemeh Mirian, and Mohammad Fatemi, “Customer knowledge management in Iranian banking industry,” In International Conference of Electronic Commerce in Developing Countries (ECDC 2012), ECDC, 2012.

  • Solmaz Abbaspour, Yasaman Amannejad, Fatemeh Mirian, and Mohammad Fatemi. “Context-aware user interface adaptation for banking services,” In International Conference of Electronic Commerce in Developing Countries (ECDC 2010), ECDC, 2010.

  • Yasaman Amannejad and Mohammad K. Akbari, “A novel approach for fraud detection using association rules,” In International Conference of Electronic Commerce in Developing Countries (ECDC 2010), ECDC, 2010.

  • Yasaman Amannejad, Vahid Garousi, Rob Irving, Zahra Sahaf, “A Search-based Approach for Cost- Effective Software Test Automation Decision Support and an Industrial Case Study,” International Workshop on Regression Testing, pages 302-311, 2014.

Talk

  • Yasaman Amannejad, “Computing and Creativity; The importance of Technology, Coding & Computational Thinking”, Renart Intelligent Learning, May 2019, Calgary, Canada.

Thesis

  • Yasaman Amannejad, “Performance Management of Web Services Using Machine Learning Techniques,” PhD thesis, University of Calgary, Calgary, Canada, June 2017.

  • Yasaman Amannejad, “A Fraud Detection Method for Pervasive Environments Based on Data Mining,” MSc. thesis, Amirkabir University of Technology, Tehran, Iran, February 2011.

  • Yasaman Amannejad, “Identifying and Clustering Environmental Entities for Messaging in a Pervasive Environment,” BSc. thesis, Amirkabir University of Technology, Tehran, Iran, August 2009.