Rami Mochaourab is a senior researcher with expertise in Trustworthy AI and data privacy.
He is research area leader for Applied AI and Machine Learning at the department of Industrial Systems, RISE Digital Systems and also member of the working group Digitalized Industry at the Digital Futures Centre (https://www.digitalfutures.kth.se).
- R. Mochaourab, A. Venkitaraman, I. Samsten, P. Papapetrou, and C. R. Rojas, “Post-hoc Explainability for Time Series Classification: Towards a Signal Processing Perspective,” IEEE Signal Processing Magazine, Special Issue on Explainability in Data Science: Interpretability, Reproducibility, and Replicability, vol. 39, no. 4, July 2022.
- S. Greenstein, P. Papapetrou, R. Mochaourab, “Embedding Human Values into Artificial Intelligence,” in De Vries, Katja (ed.), De Lege, Uppsala University, 2022. (in press)
- R. Mochaourab, S. Sinha, S. Greenstein, and P. Papapetrou, “Robust Counterfactual Explanations for Privacy-Preserving SVMs,” International Conference on Machine Learning (ICML 2021), Workshop on Socially Responsible Machine Learning, Jul. 2021.
- Post Hoc Explainability for Time Series Classification Toward a signal processi…
- Post-hoc Explainability for Time Series Classification: Towards a Signal Proces…
- Robust Counterfactual Explanations for Privacy-Preserving SVM
- Learning Time Series Counterfactuals via Latent Space Representations
- Distributed Queue-Aware Beamforming in MISO Interference Channels
- Stable Matching with Externalities for Beamforming and User Assignment in Multi…
- Private Filtering for Hidden Markov Models