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Biografia

Niclas F. Sturm obteve a sua licenciatura na Universidade de Heidelberg (Alemanha) em Economia e História Antiga (50%-50%). Depois de terminar o mestrado na Nova School of Business and Economics (Carcavelos), trabalhou no Data Science Knowledge Centre da mesma faculdade. Atualmente, está a fazer um doutoramento na Nova IMS, focando-se na deteção de estruturas irregulares em contratos públicos.

Publicações Cientificas

Rodrigues, F. A., Sturm, N. F., & Pinheiro, F. L. (2026)

A linguistic comparison between human- and AI-generated content. ISCIENCE, 29(3), Article 114976. https://doi.org/10.1016/j.isci.2026.114976

Semedo, L. P., Pinto, C., Monteiro, B., Sturm, N. F., Damásio, B., & Pinheiro, F. L. (2026)

Inference of Firm-Firm Competing Networks in the Portuguese Public Procurement Market. In H. Cherifi, L. M. Rocha, C. Cherifi, & M. Z. Ertem (Eds.), Complex Networks & Their Applications XIV: Proceedings of the Fourteenth International Conference on Complex Networks and Their Applications: COMPLEX NETWORKS 2025, Volume 3 (Vol. 3, pp. 135-143). (Studies in Computational Intelligence; No. 1265). Springer. https://doi.org/10.1007/978-3-032-16723-1_12

Sturm, N. F., Candia, C., Damásio, B., & Pinheiro, F. L. (2026)

Augmenting Firm Diversification Behavior Prediction with Graph Embeddings. In H. Cherifi, L. M. Rocha, C. Cherifi, & M. Z. Ertem (Eds.), Complex Networks & Their Applications XIV: Proceedings of the Fourteenth International Conference on Complex Networks and Their Applications: COMPLEX NETWORKS 2025, Volume 3 (Vol. 3, pp. 111-122). (Studies in Computational Intelligence; No. 1265). Springer. https://doi.org/10.1007/978-3-032-16723-1_10

Natália, E., Borges, R., Semedo, L., Vasconcelos, C., Sturm, N. F., Damásio, B., & Pinheiro, F. L. (2026)

Embedded Knowledge and Networks: Complexity in Antitrust Collusion Mitigation. Zenodo. https://doi.org/10.5281/zenodo.18462756

Sturm, N. F., Candia, C., Damásio, B., & Pinheiro, F. L. (2025)

High earnings through firm influence: the role of hierarchical structures in public procurement. EPJ Data Science, 14, 1-20. Article 27. https://doi.org/10.1140/epjds/s13688-025-00543-z

Hlacs, A., Wells, H., Damásio, B., Vasconcelos, C., Sturm, N. F., Gonçalves, A., & Batista, P. (2025)

Using digital technology to strengthen oversight of public procurement in Portugal: The use of data analytics and machine learning by the Tribunal de Contas. (pp. 1-33). (OECD Working Papers on Public Governance; No. 83). OECD Publishing. https://doi.org/10.1787/43add03b-en