Papers
- Nalchigar, S., Yu, E., Keshavjee, K. (2021). Modeling machine learning requirements from three perspectives: a case report from the healthcare domain. Requirements Engineering, Springer. [PDF]
- Nalchigar, S., Yu, E., Keshavjee, K. (2020). Modeling machine learning requirements from three perspectives: a case report from the healthcare domain. Requirements Engineering, Springer. [To Appear]
- Nalchigar, S., Yu, E. (2020). Designing Business Analytics Solutions. Business & Information Systems Engineering, Springer. [PDF]
- Nalchigar, S., Yu, E. (2018). Business-driven data analytics: A conceptual modeling framework. Data & Knowledge Engineering, Elsevier. [PDF]
- Nalchigar, S., Yu, E., Obeidi, Y., Carbajales, S., Green, J., Chan, A. (2019). Solution Patterns for Machine Learning. 31st International Conference on Advanced Information Systems Engineering (CAiSE'19), Rome, Italy. [PDF]
- Nalchigar, S., Yu, E. (2017). Conceptual Modeling for Business Analytics: A Framework and Potential Benefits. 19th IEEE International Conference on Business Informatics (CBI'17), Thessaloniki, Greece. [PDF]
- Nalchigar, S., Yu, E., Ramani, R. (2016). A Conceptual Modeling Framework for Business Analytics. 35th International Conference on Conceptual Modeling (ER'16), Gifu, Japan. [PDF]
- Nalchigar, S., Yu, E., Easterbrook, S. (2014). Towards Actionable Business Intelligence: Can System Dynamics Help? Proceedings of 7th IFIP WG 8.1 working conference on the Practice of Enterprise Modelling (PoEM'14), Manchester, UK, 12-13 Nov 2014. [PDF]
- Nalchigar, S., Yu, E. (2013). From Business Intelligence Insights to Actions: A Methodology for Closing the Sense-and-Respond Loop in Adaptive Enterprises. In Janis Grabis, Marite Kirikova, Jelena Zdravkovic, and Janis Stirna, editors, The Practice of Enterprise Modeling, volume 165 of Lecture Notes in Business Information Processing, pp 114-128. Springer Berlin Heidelberg. [PDF]
Tutorials
© 2021 Soroosh Nalchigar (last update: January 2021)