Yash Raj Shrestha

Prof. Dr. Yash Raj Shrestha
Born	Eastern Hills, Nepal
Nationality	Nepali
Alma mater	ETH Zurich, Saarland University, National Institute of Technology
Website	HEC Lausanne Page

Prof. Dr. Yash Raj Shrestha is a researcher and professor known for his work in algorithm design, data science, and organizational theory. He is currently affiliated with HEC Lausanne, where his research focuses on bridging the gap between computer science and organizational theory, particularly in the study of new forms of organizations such as online communities.

Early Life and Education

Yash Raj Shrestha was born and raised in the eastern hills of Nepal. He completed his undergraduate studies in Electronics and Communication Engineering at the National Institute of Technology, Durgapur in India. He then pursued a Master’s degree in Computer Science at Saarland University, Germany, where he focused on algorithmic complexity in graph theory.

Shrestha completed his PhD in Data Science and Strategy at ETH Zurich under the supervision of Prof. Dr. Georg von Krogh, Prof. Dr. Phanish Puranam, and Prof. Dr. Ce Zhang. His dissertation, titled "Bridging Data Science and Organization Science: Leveraging Algorithmic Induction to Research Online Communities", explored how algorithmic methods could be applied to organizational research, particularly in the context of online communities.

Career

Prior to his academic career, Shrestha worked as a research associate at the Cluster of Excellence MMCI in Germany from 2010 to 2014. His work there focused on computational social choice and theoretical computer science. Shrestha has also been a visiting scholar at the Laboratory of Innovation Science, Harvard University, and the Institute of Mathematical Sciences, Chennai. He has also worked as a software engineer at Samsung.

Shrestha's research is supported by various institutions, including the Swiss National Science Foundation (SNSF), the German Research Foundation (DFG), and the Government of India (EdCIL).

Research

Shrestha's research interests lie at the intersection of data science, algorithm design, and organizational theory. His work explores how computational methods, particularly machine learning and algorithmic induction, can inform the study of organizational structures and decision-making processes, especially in new and emerging forms of organizing such as online communities and open source software development. His contributions include:

• The application of deep learning algorithms to augment organizational decision-making (Shrestha, Y. R., et al., 2021, *Journal of Business Research*)
• Exploring the role of artificial intelligence in strategizing and organizational governance (Shrestha, Y. R., et al., 2019, *California Management Review*)
• Research on consensus formation and governance in non-hierarchical organizations, particularly in open-source software projects (Shrestha, Y. R., et al., 2020, *Strategic Management Journal*)

Shrestha has been awarded grants for his research, including a CHF 569,754 grant from the Swiss National Science Foundation in 2021 for the project "Sustaining Knowledge Creation in Online Communities."

Professional Service

Shrestha serves as an ad-hoc reviewer for numerous academic journals and conferences, including:

• Strategic Management Journal
• Information Systems Research
• Organization Science
• California Management Review
• Research Policy

He is also involved in several international conferences, including the International Conference on Information Systems (ICIS) and the Annual Meetings of the Academy of Management (AOM).

Teaching

Shrestha teaches courses related to strategic management and innovation, with a focus on the intersection of technology and organizational theory. He has supervised numerous Master’s theses at ETH Zurich and HEC Lausanne. Notable students of his include Matteo Frondoni, who received the SEW-EURODRIVE Foundation Student Prize in 2016, and Christoph Hirnschall, who received the Willie Studer Prize in 2017.

Selected Publications

Shrestha has authored numerous papers, including:

• Shrestha, Y. R., Krishna, V., and von Krogh, G., (2021) "Augmenting Organizational Decision-Making with Deep Learning Algorithms: Principles, Promises, and Challenges." *Journal of Business Research, 123*, 588–603.
• Shrestha, Y. R., He, V. F., Puranam, P., and von Krogh, G., (2021) "Algorithm Supported Induction for Building Theory: How Can We Use Prediction Models to Theorize?" *Organization Science, 32*(3), 856–880.
• Shrestha, Y. R., Ben-Menahem, S., and von Krogh, G. (2019) "Organizational Decision-Making Structures in the Age of Artificial Intelligence." *California Management Review.*

External Links

• Official website at HEC Lausanne
• Google Scholar profile
• Website at ETH Zurich