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Profile

Philipp Cornelius (CV) is an Assistant Professor of Technology and Operations Management at the Rotterdam School of Management. He holds a PhD in Management Science & Innovation from the UCL School of Management, University College London, and a BSc in Information Systems from the University of Mannheim, Germany. Philipp’s research interests are in new product development, innovation management, and crowd-driven innovation. He investigates related questions in large-sample econometric studies using original data from organisations and innovation platforms.

Publications

Academic (3)

Courses

Advanced Statistics & Programming

  • Study year: 2022/2023, 2021/2022
  • Code: BM01BAM
  • Level: Master

Management Science

  • Study year: 2022/2023, 2021/2022
  • Code: BM04BAM
  • Level: Master

Machine Learning & Learning Algorithms

  • Study year: 2022/2023, 2021/2022
  • Code: BM05BAM
  • Level: Master

Business Analytics Applications with Python

  • Study year: 2022/2023, 2021/2022
  • Code: BM23BAM
  • Level: Master

BIM Master Thesis

  • Study year: 2022/2023, 2021/2022, 2020/2021, 2019/2020, 2018/2019
  • Code: BMMTBIM
  • Level: Master

BIM Thesis Clinic

  • Study year: 2022/2023, 2021/2022, 2020/2021
  • Code: BMRM1BIM
  • Level: Master

Past courses

Business Analytics Applications with Python - Extra assignment

  • Study year: 2021/2022
  • Code: BM23BAME
  • Level: Master

Innovation in the Digital Age

  • Study year: 2021/2022, 2020/2021, 2019/2020, 2018/2019, 2017/2018
  • Code: BMME119
  • Level: Master, Master, Master, Master

Introduction to Data Science with Python

  • Study year: 2021/2022, 2020/2021, 2019/2020, 2018/2019, 2017/2018
  • Code: BMME128
  • Level: Master, Master, Master, Master

Information Strategy

  • Study year: 2020/2021
  • Code: BM01BIM
  • ECTS: 5 Level: ERIM, Exchange, IM/CEMS, Master

BIM Research Methods I - Old style

  • Study year: 2019/2020, 2018/2019
  • Code: BM05BIM
  • ECTS: 2

Featured in the media

Featured on RSM Discovery

RSM Discovery magazine 37 – out now!

Issue 37: devoted to understand the benefits of data analytics in an age where big data have become woven into the very fabric of our lives.