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Publications

The 50 most recent publications from the Division of Software and Computer Systems:

[1]
H. Boström, "Testing Exchangeability for Multiple Sequences of P-values," in Proceedings of the 14th Symposium on Conformal and Probabilistic Prediction with Applications, COPA 2025, 2025, pp. 615-632.
[2]
Z. Li and H. Boström, "FlowGuard: Guarding Flow Matching via Conformal Sampling," in Proceedings of the 14th Symposium on Conformal and Probabilistic Prediction with Applications, COPA 2025, 2025, pp. 775-777.
[3]
G. Dong, R. Bresson and H. Boström, "Detecting Attacks with Conformal Test Martingales," in Proceedings of the 14th Symposium on Conformal and Probabilistic Prediction with Applications, COPA 2025, 2025, pp. 758-761.
[4]
K. Hammerfald et al., "Leveraging large language models to identify microcounseling skills in psychotherapy transcripts," Psychotherapy Research, pp. 1-19, 2025.
[5]
W. Liu and P. Papadimitratos, "Guardian Positioning System (GPS) for Location Based Services," in WiSec 2025 - Proceedings of the 18th ACM Conference on Security and Privacy in Wireless and Mobile Networks, 2025, pp. 88-99.
[6]
E. Ståhl et al., "On the Benefits of Predictable Traffic in Virtual Switches: A Case Study," in ANRW 2025 - Proceedings of the 2025 Applied Networking Research Workshop, 2025, pp. 113-119.
[7]
V. Gulisano et al., "Foreword," in Debs 2025 Proceedings of the 19th ACM International Conference on Distributed and Event Based Systems, 2025, pp. vi-vii.
[8]
W. Liu and P. Papadimitratos, "Self-supervised federated GNSS spoofing detection with opportunistic data," in 2025 IEEE/ION Position, Location and Navigation Symposium, PLANS 2025, 2025, pp. 381-390.
[9]
W. Liu and P. Papadimitratos, "GNSS Spoofing Detection Based on Opportunistic Position Information," IEEE Internet of Things Journal, 2025.
[10]
Z. Zhou, H. Jin and P. Papadimitratos, "Clogging DoS Resilient Bootstrapping of Efficient V2V Validation," in 40th Annual ACM Symposium On Applied Computing, 2025, pp. 1857-1866.
[11]
Y. Liu et al., "Detecting and removing bloated dependencies in CommonJS packages," Journal of Systems and Software, vol. 230, 2025.
[12]
M. Siavashi et al., "Priority-Aware Preemptive Scheduling for Mixed-Priority Workloads in MoE Inference," in Proceedings of the 2025 The 5th Workshop On Machine Learning And Systems, EUROMLSYS 2025, 2025, pp. 132-138.
[13]
H. Jin and P. Papadimitratos, "Accountable, Scalable and DoS-resilient Secure Vehicular Communication," Computers & Security, vol. 156, 2025.
[14]
G. Dong et al., "Obtaining Example-Based Explanations from Deep Neural Networks," in Advances in Intelligent Data Analysis XXIII - 23rd International Symposium on Intelligent Data Analysis, IDA 2025, Proceedings, 2025, pp. 432-443.
[15]
A. Rao, "Practical Machine Learning for Predictions in Mobile Networks," Doctoral thesis Stockholm : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2025:64, 2025.
[16]
G. Verardo et al., "Reducing the Number of Leads for ECG Imaging with Graph Neural Networks and Meaningful Latent Space," in Statistical Atlases and Computational Models of the Heart. Workshop, CMRxRecon and MBAS Challenge Papers. - 15th International Workshop, STACOM 2024, Held in Conjunction with MICCAI 2024, Revised Selected Papers, 2025, pp. 301-312.
[17]
S. Ennadir et al., "Expressivity of Representation Learning on Continuous-Time Dynamic Graphs: An Information-Flow Centric Review," Transactions on Machine Learning Research, vol. 2025-April, 2025.
[18]
C. Ottaviani et al., "Advanced Routing Strategies for LEO and VLEO Constellations : Ensuring Polar Coverage," in 2025 12th Advanced Satellite Multimedia Systems Conference and the 18th Signal Processing for Space Communications Workshop, ASMS/SPSC 2025, 2025.
[19]
M. I. Al Hafiz et al., "A Reconfigurable Stream-Based FPGA Accelerator for Bayesian Confidence Propagation Neural Networks," in Applied Reconfigurable Computing. Architectures, Tools, and Applications - 21st International Symposium, ARC 2025, Proceedings, 2025, pp. 196-213.
[20]
L. Bahri, B. Carminati and E. Ferrari, "Privacy-Aware Access Control in Decentralized Online Social Networks," in Encyclopedia of Cryptography, Security and Privacy, Third Edition, : Springer Nature, 2025, pp. 1924-1927.
[21]
P. Papadimitratos, "Mix-Zones in Wireless Mobile Networks," in Encyclopedia of Cryptography, Security and Privacy, Sushil Jajodia, Pierangela Samarati, Moti Yung Ed., 3rd ed. : Springer Nature, 2025, pp. 1555-1559.
[22]
R. Yadav et al., "Automatic Tracing in Task-Based Runtime Systems," in ASPLOS 2025 - Proceedings of the 30th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2025, pp. 84-99.
[23]
V. Andersson et al., "UPPERCASE IS ALL YOU NEED," in SIGBOVIK : A Record of the Proceedings of SIGBOVIK 2025, 2025, pp. 24-35.
[24]
G. Shang et al., "Atlas-Chat : Adapting Large Language Models for Low-Resource Moroccan Arabic Dialect," in LoResLM 2025 - 1st Workshop on Language Models for Low-Resource Languages, Proceedings of the Workshop, 2025, pp. 9-30.
[25]
A. E. Samy, Z. T. Kefato and Š. Girdzijauskas, "Leap : Inductive Link Prediction via Learnable Topology Augmentation," in Machine Learning, Optimization, and Data Science - 10th International Conference, LOD 2024, Revised Selected Papers, 2025, pp. 448-463.
[26]
V. Komini and S. Girdzijauskas, "Integrating Logit Space Embeddings for Reliable Out-of-Distribution Detection," in Machine Learning, Optimization, and Data Science - 10th International Conference, LOD 2024, Revised Selected Papers, 2025, pp. 255-269.
[27]
R. Bresson et al., "KAGNNs : Kolmogorov-Arnold Networks meet Graph Learning," Transactions on Machine Learning Research, vol. 2025-March, pp. 1-29, 2025.
[28]
M. Spanghero, "Data verification for GNSS systems and protection of GNSS services," Doctoral thesis Stockholm, Sweden : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2025:36, 2025.
[29]
M. Spanghero et al., "GNSS jammer localization and identification with airborne commercial GNSS receivers," IEEE Transactions on Information Forensics and Security, vol. 20, pp. 3550-3565, 2025.
[30]
M. Spanghero and P. Papadimitratos, "UnReference: analysis of the effect of spoofing on RTK reference stations for connected rovers," in Proceedings of the 2025 IEEE/ION Position, Localization and Navigation Symposium (PLANS), Salt Lake City, UT, USA, 2025, pp. 1-12.
[31]
E. Listo Zec et al., "On the effects of similarity metrics in decentralized deep learning under distributional shift," Transactions on Machine Learning Research, vol. 2025-January, pp. 1-23, 2025.
[32]
G. Verardo et al., "FMM-Head: Enhancing Autoencoder-Based ECG Anomaly Detection with Prior Knowledge," in Pattern Recognition and Artificial Intelligence - 4th International Conference, ICPRAI 2024, Proceedings, 2025, pp. 18-32.
[33]
S. Sheikholeslami, "Tools and Methods for Distributed and Large-Scale Training of Deep Neural Networks," Doctoral thesis Stockholm : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2025:28, 2025.
[34]
S. Sheikholeslami et al., "Utilizing Large Language Models for Ablation Studies in Machine Learning and Deep Learning," in The 5th Workshop on Machine Learning and Systems (EuroMLSys), co-located with the 20th European Conference on Computer Systems (EuroSys), 2025.
[35]
A. H. Akhavan Rahnama, "Evaluating the Faithfulness of Local Feature Attribution Explanations : Can We Trust Explainable AI?," Doctoral thesis Stockholm : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2025:23, 2025.
[36]
M. Spanghero and P. Papadimitratos, "Consumer INS coupled with carrier phase measurements for GNSS spoofing detection," in ION ITM/PTTI, International Technical Meeting January 27 - 30, 2025 Long Beach, CA, 2025.
[37]
F. Cornell et al., "Unsupervised Ontology- and Taxonomy Construction Through Hyperbolic Relational Domains and Ranges," in Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2023, Revised Selected Papers, 2025, pp. 339-348.
[38]
A. Alkhatib, "Addressing Shortcomings of Explainable Machine Learning Methods," Doctoral thesis Stockholm : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2025:11, 2025.
[39]
E. Listo Zec, "Decentralized deep learning in statistically heterogeneous environments," Doctoral thesis Stockholm : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2025:4, 2025.
[40]
M. Fragkoulis et al., "A survey on the evolution of stream processing systems," The VLDB journal, vol. 33, no. 2, pp. 507-541, 2024.
[41]
J. Spenger, P. Carbone and P. Haller, "A Survey of Actor-Like Programming Models for Serverless Computing," in Active Object Languages : Current Research Trends, Frank de Boer, Ferruccio Damiani, Reiner Hähnle, Einar Broch Johnsen, Eduard Kamburjan Ed., : Springer Nature, 2024, pp. 123-146.
[42]
Z. Xu et al., "A Semi-Supervised Model for Non-Cellular Elements Segmentation in Microscopy Images of Wood," in 2024 IEEE International Conference on Big Data (BigData), 2024, pp. 2049-2056.
[43]
D. Tiwari, "Augmenting Test Oracles with Production Observations," Doctoral thesis Stockholm : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2024:87, 2024.
[44]
B. Lindqvist and A. Podobas, "Algorithms for Fast Spiking Neural Network Simulation on FPGAs," IEEE Access, vol. 12, pp. 150334-150353, 2024.
[45]
V. Palmkvist, "Abstraction, Composition, and Resolvable Ambiguity in Programming Language Implementation," Doctoral thesis Stockholm : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2024:69, 2024.
[46]
F. Schmidt et al., "A Scalable System Architecture for Composition and Deployment of Machine Learning Models in Cognitive Behavioral Therapy," in 2024 IEEE International Conference on Digital Health (ICDH), 2024, pp. 79-86.
[47]
K. Segeljakt, S. Haridi and P. Carbone, "AquaLang : A Dataflow Programming Language," in DEBS 2024 - Proceedings of the 18th ACM International Conference on Distributed and Event-Based Systems, 2024, pp. 42-53.
[48]
M. Polverini et al., "Achieving Best-path Selection at Line Rate through the SRv6 Live-Live Behavior," in Proceedings of IEEE/IFIP Network Operations and Management Symposium 2024, NOMS 2024, 2024.
[49]
A. Q. Khan et al., "A Taxonomy for Cloud Storage Cost," in Management of Digital EcoSystems - 15th International Conference, MEDES 2023, Revised Selected Papers, 2024, pp. 317-330.
[50]
S. Ennadir et al., "A Simple and Yet Fairly Effective Defense for Graph Neural Networks," in AAAI Technical Track on Safe, Robust and Responsible AI Track, 2024, pp. 21063-21071.
Full list in the KTH publications portal