Michael Siegel is a Principal Research Scientist at the MIT Sloan School of Management and is currently the Co-Director of the PROductivity from Information Technology (PROFIT) Project. Siegel’s research interests include the integration and use of information from multiple and the use of modeling and data analytics to analyze complex systems.
His work has been published in areas including the use of information technology in financial risk management and global financial systems, cybersecurity, applications of computation social science to analyze state stability, digital business, financial account aggregation, healthcare information systems, heterogeneous database systems, managing data semantics, query optimization, intelligent database systems, and learning in database systems.
He received his BS in engineering from Trinity College (1977), an MS in engineering from the Solar Energy Laboratory at the University of Wisconsin-Madison (1980), and an MA and PhD in computer science from Boston University (1989).
Huang, Keman, Michael Siegel, and Stuart Madnick. ACM Computing Surveys (CSUR) Vol. 51, No. 4 (2018): 1-36.
"Decision-Making and Biases in Cybersecurity Capability Development: Evidence from a Simulation Game Experiment."
Jalali, Mohammad, Michael Siegel, and Stuart Madnick. The Journal of Strategic Information Systems Vol. 28, No. 1 (2019): 66-82. Download Paper.
"An Economic Analysis of Policies for the Protection and Reuse of Noncopyrightable Database Contents."
Zhu, Hongwei, Stuart E. Madnick and Michael D. Siegel. Journal of Management Information Systems Vol. 25, No. 1 (2008): 199-232.
Zhu, Hongwei, Stuart E. Madnick and Michael D. Siegel. International Journal of Electronic Business Vol. 6, No. 4 (2008): 319-341.
Ang, Wee Horng, Vicki Deng, Yang Lee, Stuart E. Madnick, Dinsha Mistree, Michael Siegel, Diane Strong, Richard Wang. FSTC Innovator: The Journal for Financial Services Technology Leaders Vol. 1, No. 1 (2007): 19-24.