Management of Technology & Entrepreneurship Institute

The establishment of the Management of Technology & Entrepreneurship Institute demonstrates a commitment to advancing knowledge and understanding in the areas of technology management, entrepreneurship, and public policy. Institutes like these play a crucial role in promoting research, fostering innovation, and developing programs that equip individuals with the skills and knowledge needed to succeed in these fields.

By combining these three domains, the Management of Technology & Entrepreneurship Institute aims to create a comprehensive understanding of how technology, entrepreneurship, and public policy intersect and influence each other. This interdisciplinary approach is crucial for addressing the challenges and opportunities in today’s rapidly evolving business and societal landscape.

MTEI teaching programs

Fields of Competences

  • Business analytics
  • Economic Analysis
  • Entrepreneurial strategies
  • Machine Learning
  • Management of innovation
  • Operations & supply chain management
  • Optimization
  • Policy & Sustainability
  • Technology commercialization
  • Technology & IP Policy 

UPCOMING EVENTS

RECENT PUBLICATIONS

2026

Labor market risk shapes individuals’ environmental attitudes and policy preferences

V. González-Rostani; L. Beiser-McGrath; M. Aklin 

Ecological Economics. 2026. Vol. 246. DOI : 10.1016/j.ecolecon.2026.108973.

Group-and-cut approach for dynamic programming with Fréchet-distributed quantizers

A. Timonina-Farkas 

Omega (United Kingdom). 2026. Vol. 141, p. 103502. DOI : 10.1016/j.omega.2025.103502.

Anonymous Linear Bandits for Multi-User Systems

M. R. Badri; H. Esfandiari; S. Hossein Ghorban; A. Rezaeimoghadam 

2026. The ACM Web Conference 2026, Dubai United Arab Emirates, 2026-06-29 – 2026-07-03. p. 8573 – 8576. DOI : 10.1145/3774904.3792913.

Patents and Supra‐Competitive Prices: Evidence From Consumer Products

G. de Rassenfosse; L. Zhou 

Journal of Empirical Legal Studies. 2026. DOI : 10.1111/jels.70028.

Recursive Causal Discovery (Abstract Reprint)

E. Mokhtarian; S. Elahi; S. Akbari; N. Kiyavash 

Proceedings of the AAAI Conference on Artificial Intelligence. 2026. Vol. 40, num. 47, p. 39884 – 39884. DOI : 10.1609/aaai.v40i47.41399.

CONTACT

Director of the Institute:
Prof. Daniel Kuhn
EPFL CDM MTEI
Odyssea, Station 5, 1015 Lausanne

Administration:
Amandine Weissbrodt
T: +41 21 693 0122