Department of Digitalization

mhadigi

Department of Digitalization

Mikkel
Harlev
PhD fellow


Room: HOW/60-2.sal
E-mail: mha.digi@cbs.dk
Mikkel Harlev
Presentation

Mikkel is a Privatist Ph.d. fellow at the Department of Digitalization. His research examines Computational Modelling and Deep Learning Methods and its application in the financial sector, specifically to model the marketing metric Customer Lifetime Value (CLV). He holds a Master's degree in Information Systems from Copenhagen Business School and has several years of experience as a software engineer in the financial sector.

Primary research areas
  • Applied Deep Learning
  • Applied Machine Learning
  • Customer Lifetime Value
  • Blockchain Forensics
Social media
Links

Personal Website

Link to this homepage
www.cbs.dk/en/staff/mhadigi
Courses
  • Foundations of Data Science: Programming and Linear Algebra
Supervision
  • Computer Science
  • Data Science
Selected publications
  • Yin, H. S., Langenheldt, K. C., Harlev, M. A., Mukkamala, R. R., Vatrapu, R. (2018). Regulating Cryptocurrencies: A Supervised Machine Learning Approach to De-Anonymising the Bitcoin Blockchain. Journal of Management Information Systems, FT-50 Journal.
  • Harlev, M. A., Yin, H. S., Langenheldt, K. C., Mukkamala, R. R., Vatrapu, R. (2018). Breaking Bad: De-Anonymising Entity Types on the Bitcoin Blockchain Using Supervised Machine Learning. Hawaii International Conference on System Sciences (HICSS-51) Best Paper Award and ISSIP-IBM Student Paper Award
Publications sorted by:
2019
Hao Hua Sun Yin; Klaus Langenheldt; Mikkel Harlev; Raghava Rao Mukkamala; Ravi Vatrapu / Regulating Cryptocurrencies : A Supervised Machine Learning Approach to De-Anonymizing the Bitcoin Blockchain.
In: Journal of Management Information Systems, Vol. 36, No. 1, 2019, p. 37-73
Journal article > peer review
2018
Mikkel Alexander Harlev; Haohua Sun Yin; Klaus Christian Langenheldt; Raghava Rao Mukkamala; Ravi Vatrapu / Breaking Bad : De-Anonymising Entity Types on the Bitcoin Blockchain Using Supervised Machine Learning.
In: Proceedings of the 51st Hawaii International Conference on System Sciences 2018Honolulu : Hawaii International Conference on System Sciences (HICSS) 2018, p. 3497-3506 (Proceedings of the Annual Hawaii International Conference on System Sciences)
Article in proceedings > peer review
Outside activities
2020:
  • Danske Bank: Ph.d. student