Research output per year
Research output per year
Personal profile
Keywords
- Online privacy
- Privacy in data analytics
- Privacy in social networks
- Probabilistic programming
- Formal methods
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Dive into the research topics where Raúl Pardo Jimenez is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Collaborations and top research areas from the last five years
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Free open source communities sustainability: Does it make a difference in software quality?
Alami, A., Pardo, R. & Linåker, J., 23 Jul 2024, In: Empirical Software Engineering. 29, 114.Research output: Journal Article or Conference Article in Journal › Journal article › Research › peer-review
Open Access -
Exact and Efficient Bayesian Inference for Privacy Risk Quantification
Rønneberg, R. C., Pardo, R. & Wasowski, A., 31 Oct 2023, Proceedings of Software Engineering and Formal Methods (SEFM'23). Springer, Cham, Vol. 14323. p. 263-281 18 p. (Lecture Notes in Computer Science).Research output: Conference Article in Proceeding or Book/Report chapter › Article in proceedings › Research › peer-review
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A Specification Logic for Programs in the Probabilistic Guarded Command Language
Pardo, R., Broch Johnsen, E., Schaefer, I. & Wasowski, A., Oct 2022, A Specification Logic for Programs in the Probabilistic Guarded Command Language. Springer, Cham, Vol. 13572. 19 p. (Proceedings of 19th International Colloquium on Theoretical Aspects of Computing - ICTAC 2022).Research output: Conference Article in Proceeding or Book/Report chapter › Article in proceedings › Research › peer-review
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How Attacker Knowledge Affects Privacy Risks: An Analysis Using Probabilistic Programming
Halvorsen, L., Steffensen, S. L., Rafnsson, W., Kulyk, O. & Pardo, R., 2022, IWSPA '22: Proceedings of the 2022 ACM on International Workshop on Security and Privacy Analytics. Association for Computing MachineryResearch output: Conference Article in Proceeding or Book/Report chapter › Article in proceedings › Research › peer-review
Open AccessFile -
Privacy with Good Taste: A Case Study in Quantifying Privacy Risks in Genetic Scores
Pardo, R., Rafnsson, W., Steinhorn, G., Lavrov, D., Lumley, T., Probst, C., Ziedins, I. & Wasowski, A., 2022, Privacy with Good Taste: A Case Study in Quantifying Privacy Risks in Genetic Scores. Springer, Cham, Vol. 13619. p. 1-16 16 p.Research output: Conference Article in Proceeding or Book/Report chapter › Article in proceedings › Research › peer-review