Publications

Management

8. Feuerriegel, S., Shrestha, Y.R., von Krogh, G., & Zhang, C. (2022) Bringing artificial intelligence to business management. Nature Machine Intelligence 4, 611–613 paper

7. Arrieta, J. P., & Shrestha, Y. R. (2022). On the strategic value of equifinal choice. Journal of Organization Design, 1-9. paper

6. von Krogh, G., Ben-Menahem, S. & Shrestha, Y. R. (2021) Artificial Intelligence in Strategizing: Prospects and Challenges, In I. Duhaime, M. Hitt & M. Lyles (Eds.), Strategic Management: State of the Field and Its Future, Cambridge University Press paper

5. 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 paper

4. Tinguely, P., Shrestha, Y. R. and von Krogh, G. (2020) How Does Your Labor Force React to COVID-19? Employing Social Media Analytics for Preemptive Decision Making. California Management Review Insights paper

3. 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 paper

2. He. F., Puranam P., Shrestha Y. R., & von Krogh, G. (2020) Resolving governance disputes in communities: A study of license decisions in OSS projects. Strategic Management Journal, 41(10), 1837–1868. paper

1. Shrestha, Y. R., Ben-Menahem, S., & von Krogh, G (2019). Organizational Decision-Making Structures in the Age of Artificial Intelligence. California Management Review. paper

Monographs

2. Shrestha, Y. R. (2019). Bridging Data Science and Organization Science: Leveraging Algorithmic Induction to Research Online Communities (Doctoral dissertation, ETH Zurich).

1. Shrestha, Y. R. (2011). Complexity of Disjoint Π-Vertex Deletion for Disconnected Forbidden Subgraphs. (MSc Thesis, Saarland University)

Computer Science

Erdös Number: 4 (Erdös > Noga Alon > Rudolf Fleischer > Jiong Guo > Yash Raj Shrestha)

16. Keidar, D., Zhong, M., Zhang, C., Shrestha, Y. R., & Paudel, B. (2021). Towards Automatic Bias Detection in Knowledge Graphs. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: Findings (EMNLP 2021). Nov 7–11, 2021 paper video

15. Arduini, M., Noci, L., Pirovano, F., Zhang, C., Shrestha, Y. R., & Paudel, B. (2020). Adversarial learning for debiasing knowledge graph embeddings. In MLG 2020: 16th International Workshop on Miningand Learning with Graphs – A Workshop at the KDD Conference, August 24,2020, San Diego, CA.ACM, New York, NY, USA, 7 pages paper video

14. Leopold F., Shrestha, Y. R. & Paudel, B. (2020). A Deep Learning Pipeline for Patient Diagnosis Prediction Using Electronic Health Records. In BioKDD 2020: 19th International Workshop on Data Mining in Bioinformatics, August 24, 2020, San Diego, CA.ACM, New York, NY, USA paper video

13. Shrestha, Y. R., & Yang, Y. (2019). Fairness in Algorithmic Decision-Making: Applications in Multi-Winner Voting, Machine Learning, and Recommender Systems. Algorithms, 12(9), 199. paper

12. Yang, Y., Shrestha, Y. R., & Guo, J. (2019). On the complexity of bribery with distance restrictions. Theoretical Computer Science, 760, 55-71. paper

11. Yang, Y., Shrestha, Y. R., Li, W., & Guo, J. (2018). On the kernelization of split graph problems. Theoretical Computer Science, 734, 72-82. paper

10. Yang, Y., Shrestha, Y. R., & Guo, J. (2016). How Hard Is Bribery with Distance Restrictions? In Proceedings of European Conference on Artificial Intelligence, 363-371 paper

9. Yang, Y., Shrestha, Y. R., Li, W., & Guo, J. (2016). Kernelization of two path searching problems on split graphs. In Frontiers in Algorithmics , Lecture Notes in Computer Science, 238-249. paper

8. Mnich, M., Shrestha, Y. R., & Yang, Y. (2015). When does Schwartz conjecture hold? In Proceedings of the International Joint Conference on Artificial Intelligence, 603-609 paper

7. Guo, J., Shrestha, Y. R., & Yang, Y. (2015). How Credible is the Prediction of a Party-Based Election? In Proceedings of the International Conference on Autonomous Agents and Multiagent Systems, 1431-1439. International Foundation for Autonomous Agents and Multiagent Systems. paper

6. Yang, Y., Shrestha, Y. R., & Guo, J. (2015). How Hard is Bribery in Party Based Elections?. In Proceedings of the International Conference on Autonomous Agents and Multiagent Systems,1725-1726. International Foundation for Autonomous Agents and Multiagent Systems. paper

5. Guo, J., & Shrestha, Y. R. (2014). Complexity of Disjoint Π-Vertex Deletion for Disconnected Forbidden Subgraphs. Journal of Graph Algorithms and Applications, 18(4), 603–631 paper

4. Guo, J., Shrestha, Y. R. (2014). Controlling Two-stage Voting Rules, In Proceedings of European Conference on Artificial Intelligence, Frontiers of Artificial Intelligence and Applications, 263, 411-416 paper

3. Guo, J., & Shrestha, Y. R. (2014) Parameterized Complexity of Edge Interdiction Problems In: Computing and Combinatorics, Lecture Notes in Computer Science, vol. 8591, 166-178 paper

2. Guo, J., & Shrestha, Y. R. (2014). Complexity of Disjoint Π-Vertex Deletion for Disconnected Forbidden Subgraphs. In Algorithms and Computation, Lecture Notes in Computer Science, vol. 8344, 286-297 paper

1. Guo, J., & Shrestha, Y. R. (2012). Kernelization and Parameterized Complexity of Star Editing and Union Editing. In Algorithms and Computation, Lecture Notes in Computer Science, vol. 7676, 126-135 paper