H. Tian, X. Li, Z. Wu, and S. Magnússon, "Communication-efficient online federated composite optimization", Elsevier Automatica, 2025. 

A. Beikmohammadi and S. Magnússon, "Human-inspired framework to accelerate reinforcement learning", The Journal of Supercomputing, 2025. 

X. Wu, C. Liu, S. Magnússon, Mikael Johansson, "Asynchronous Distributed Optimization with Delay-free Parameters", IEEE Transactions on Automatic Control, 2025.

Z. Kharazian, T. Lindgren, S. Magnússon, O. Steinert, and R. Andersson, "Scania component X dataset: A real-world multivariate time series dataset for predictive maintenance", Scientific Data, 2025. 

H. Wang, W. Huang, S. Magnússon, T. Lindgren, C. Chen, J. Wu, and Y. Song, "Crowding distance and IGD-driven grey wolf reinforcement learning approach for multi-objective agile earth observation satellite scheduling." International Journal of Digital Earth, 2025. 

A. Beikmohammadi, S. Khirirat, and S. Magnússon, "Parallel Momentum Methods Under Biased Gradient Estimations", IEEE Transactions on Control of Network Systems, 2025.  

S. Vaishnav, S. Khirirat, and S. Magnússon, "Communication-Adaptive Gradient Sparsification for Federated Learning with Error Compensation," IEEE Internet of Things Journal, 2025.

H Wang, W Huang, S Magnússon, T Lindgren, R Wang, Y Song, "A Strategy Fusion-Based Multi-Objective Optimization Approach for Agile Earth Observation Satellite Scheduling Problem,"  IEEE Transactions on Geoscience and Remote Sensing, 2024.

A. Beikmohammadi, S. Khirirat, and S. Magnússon, "On the Convergence of Federated Learning Algorithms without Data Similarity", IEEE Transactions on Big Data, 2024. 

A. Beikmohammadi and S. Magnússon, "Accelerating actor-critic-based algorithms via pseudo-labels derived from prior knowledge", Elsevier Information Sciences, March 2024. 

M. Zhang, G. Guo, S. Magnússon, R. CN Pilawa-Podgurski, and Q. Xu, "Data Driven Decentralized Control of Inverter based Renewable Energy Sources using Safe Guaranteed Multi-Agent Deep Reinforcement Learning", IEEE Transactions on Sustainable Energy, Dec. 2023. 

D. Benalcazar, S. Magnússon, and C. Enyioha, "Average Consensus With Error Correction", IEEE Control Systems Letters vol. 8, Dec. 2023. 

D. Fay, S. Magnússon, J. Sjölund, and M. Johansson, "Adaptive Hyperparameter Selection for Differentially Private Gradient Descent " Transactions on Machine Learning Research, 2023. Link to paper: https://openreview.net/pdf?id=LLKI5Lq2YN

T. Timoudas, Z. Zhang, S. Magnússon, and C. Fischione, "General Framework to Distribute Iterative Algorithms with Localized Information over Networks", IEEE Transactions on Automatic Control, 2023.

X. Wu, S. Magnússon, and M. Johansson, "Distributed Safe Resource Allocation using Barrier Functions", Elsevier Automatica, 2023.

S. Khirirat, X. Wang, S. Magnússon, and M. Johansson, "Improved Step-Size Schedules for Proximal Noisy Gradient Methods", IEEE Transactions on Signal Processing, 2023.

L. Huang, T. Westin, M. Eladhari, S. Magnússon, H. Chen, "Eyes can draw: A high-fidelity free-eye drawing method with unimodal gaze control", International Journal of Human-Computer Studies, vol. 170, February 2023.

N. Victor, R. Chengoden, M. Alazab, S. Bhattacharya, S. Magnússon, P. Maddikunta, K. Ramana, and T. Gadekallu., "Federated Learning for IoUT: Concepts, Applications, Challenges and Future Directions", IEEE Internet of Things Magazine vol. 5, no. 4, Dec. 2022.  

E. Berglund, S. Magnússon, and M. Johansson, "Distributed Newton Method Over Graphs: Can Sharing of Second-order Information Eliminate the Condition Number Dependence?", IEEE Signal Processing Letters, vol. 28, May 2021.

S. Khirirat, S. Magnússon, and M. Johansson, "Compressed Gradient Methods with Hessian-Aided Error Compensation",  IEEE Transactions on Signal Processing, vol. 69, 2021.

S. Magnússon, H. Shokri-Ghadikolaei, and N. Li, "On Maintaining Linear Convergence of Distributed Learning and Optimization under Limited Communication", IEEE Transactions on Signal Processing, vol 68, 2020.

R. Du, S. Magnússon, and C. Fischione, "The Internet of Things as a Deep Neural Network", IEEE Communications Magazine, Internet of Things and Sensor Networks Series, vol. 58, no. 9, September 2020.

S. Magnússon, G. Qu, and N. Li, "Distributed Optimal Voltage Control with Asynchronous and Delayed Communication", IEEE Transactions on Smart Grid, vol. 11, no. 4, July 2020.

S. Magnússon, G. Qu, C. Fischione, and N. Li, "Voltage Control Using Limited Communication", IEEE Transactions on Control of Network Systems, vol. 6 , no. 3, Sept. 2019. 

S. Magnússon, C. Enyioha, N. Li, C. Fischione, and V. Tarokh, "Communication Complexity of Dual Decomposition Methods for Distributed Resource Allocation Optimization", IEEE Journal of Selected Topics in Signal Processing vol. 12, no. 4 , August 2018.

S. Magnússon, C. Enyioha, N. Li, C. Fischione, and V. Tarokh, "Convergence of Limited Communications Gradient Methods", IEEE Transactions on Automatic Control vol. 63, no 5, May 2018.

C. Enyioha, S. Magnússon, N. Li, C. Fischione, and V. Tarokh, "On Variability of Renewable Energy and Online Power Allocation", IEEE Transactions on Power Systems, vol. 33, no. 1, January 2018.

M. Jakobsson, S. Magnússon, C. Fischione, and P. C. Weeraddana, "Extensions of Fast-Lipschitz Optimization", IEEE Transactions on Automatic Control vol. 63, no 4, 2016.

S. Magnússon, P. C. Weeraddana, M. G. Rabbat, and C. Fischione, "On the Convergence of Alternating Direction Lagrangian Methods for Nonconvex Structured Optimization Problems", IEEE Transactions on Control of Network Systems, vol. 3, no. 3, pp. 296-309, September 2016.

S. Magnússon, P. C. Weeraddana, and C. Fischione, "A Distributed Approach for the Optimal Power Flow Problem Based on ADMM and Sequential Convex Approximations", IEEE Transactions on Control of Network Systems, vol. 3, no. 3, pp. 296-309, September 2016.

H. Bjornsson, S. Magnússon, P. Arason, and G. N. Petersen, "Velocities in the plume of the 2010 Eyjafjallajökull eruption" Journal of Geophysical Research: Atmospheres, vol. 118 , no. 20, pp. 11,698-11,711, October 2013.

 S. Vaishnav, P. Donta, and S. Magnússon, "Adaptive Budgeted Multi-Armed Bandits for IoT with Dynamic Resource Constraints", In IEEE Global Communications Conference, Taipei, Taiwan, 2025. 

A. Beikmohammadi, S. Khirirat, P. Richtarik, and S. Magnússon, "Collaborative Value Function Estimation Under Model Mismatch: A Federated Temporal Difference Analysis", In ECML PKDD research track, Porto, Portugal, 2025. 

E. Makridis, S. Magnússon, and T. Charalambous, "Distributed Gradient-Tracking Optimization with Packet-Error Resilience in Unreliable Networks", In European Control Conference (ECC), Thessaloniki, Greece, 2025. 

A. Lapkovskis, B. Sedlak, S. Magnússon, S. Dustdar and P. Donta, "Benchmarking Dynamic SLO Compliance in Distributed Computing Continuum Systems", In  IEEE International Conference on Edge Computing and Communications (IEEE EDGE), Helsinki, Finland, 2025. 

A. Beikmohammadi, S. Khirirat, and S. Magnússon, "Compressed Federated Reinforcement Learning with a Generative Model", In ECML PKDD research track, Vilnius, Lithuania, 2024. 

G. Dinis Junior, S. Magnússon, and J. Hollmén, "Policy Control with Delayed, Aggregate, and Anonmyous Feedback", In ECML PKDD research track, Vilnius, Lithuania, 2024. 

Z. Kharazian, T. Lindgren, S. Magnússon, and H. Boström, "CoPAL: Conformal Prediction in Active Learning An Algorithm for Enhancing Remaining Useful Life Estimation in Predictive Maintenance", In Symposium on Conformal and Probabilistic Prediction with Applications, Milano, Italy, 2024.

M. Amiri and S. Magnússon, "On the Convergence of TD-Learning on Markov Reward Processes with Hidden States", In European Control Conference (ECC), Stockholm, Sweden, 2024.

A. Beikmohammadi and S. Magnússon, "TA-Explore: Teacher-assisted exploration for facilitating fast reinforcement learning", In Proceedings of the International Conference on Autonomous Agents and Multiagent Systems (AAMAS), London, UK, 2023.

X. Wu, C. Liu, S. Magnússon, and M. Johansson, "Delay-agnostic asynchronous coordinate update algorithmn", In International Conference on Machine Learning (ICML), Honolulu, HI, 2023.

S. Vaishnav, M. Efthymiou, and S. Magnússon, "Energy-efficient and adaptive gradient sparsification for federated learning", In IEEE International Conference on Communications (ICC), Rome, Italy, 2023.

S. Vaishnav and S. Magnússon, "Intelligent Processing of Data Streams on the Edge Using Reinforcement Learning", In IEEE ICC 2023 Workshop on Scalable and Trustworthy AI for 6G Wireless Networks (6GSTRAIN), Rome, Italy, 2023.

K. Sun, S. Magnússon, O. Steinert, and T. Lindgren, "Robust Contrastive Learning and Multi-shot Voting for High-dimensional Multivariate Data-driven Prognostics", In IEEE International Conference on Prognostics and Health Management (ICPHM), Montreal, QC, 2023.

X. Wu, C. Liu, S. Magnússon, and M. Johansson, "Delay-agnostic asynchronous distributed optimization", IEEE Conference on Decision and Control (CDC), Singapore, 2023.

A. Beikmohammadi and S. Magnússon, "Comparing NARS and Reinforcement Learning: An Analysis of ONA and Q-Learning Algorithms", In International Conference on Artificial General Intelligence, Stockholm, Sweden, 2023.

E. Berglund, S. Khirirat, X. Wu, S. Magnússon, and M. Johansson, "Revisiting the Curvature-aided IAG: Improved Theory and Reduced Complexity" IFAC World Congress, Yokohama, Japan, 2023.

Z. Kharazian, M. Rahat, F. Gama, P. Mashhadi, S. Nowaczyk, T. Lindgren, and S. Magnússon, "AID4HAI: Automatic Idea Detection for Healthcare-Associated Infections from Twitter, A Framework based on Active Learning and Transfer Learning" International Symposium on Intelligent Data Analysis (IDA), Louvain-la-Neuve, Belgium, 2023.

X. Wu, S. Magnússon, M. Feyzmahdavian, and M. Johansson, "Delay-adaptive step-sizes for asynchronous learning", International Conference on Machine Learning (ICML), Baltimore, MD, 2022.

M. Bampa, T. Fasth, S. Magnússon, and P. Papapetrou, "EpidRLearn: Learning Intervention Strategies for Epidemics with Reinforcement Learning", International Conference on Artificial Intelligence in Medicine, Halifax, Canada, 2022.

L. Huang, M. P. Eladhari, S. Magnússon, T. Westin, N. Su, "Interactive Painting Volumetric Cloud Scenes with Simple Sketches Based on Deep Learning", IEEE International conference on Human System Interaction, Melbourne, Australia, 2022.

S. Khirirat, S. Magnússon, and M. Johansson, "Eco-Fedsplit: Federated learning with error-compensated compression", ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Singapore, 2022.

X. Wu, C. Liu, S. Magnússon, and M. Johansson, "Delay-agnostic asynchronous distributed optimization", 61nd IEEE Conference on Decision and Control (CDC), Cancún, Mexico, 2022.

G. Dinis, S. Magnússon, and J. Hollmén, "Policy Evaluation with Delayed, Aggregated Anonymous Feedback", In International Conference on Discovery Science, Montpellier, France, 2022.

M. Zhang, Q. Xu, S. Magnússon, R. Pilawa-Podgurski, and G. Guo, "Multi-agent deep reinforcement learning for decentralized voltage-var control in distribution power system", In IEEE energy conversion congress and exposition (ECCE), Detroit, MI, 2022.

L. Lindström, S. Gracy, S. Magnússon, and H. Sandberg, "Leakage localization in water distribution networks: A model-based approach" In European Control Conference (ECC), London, UK, 2022.

X. Wu, S. Magnússon, and M. Johansson, "A new family of feasible methods for distributed resource allocation" In IEEE Conference on Decision and Control (CDC), Online, 2021.

X. Wang, S. Magnússon, M. Johansson, "On the convergence of step decay step-size for stochastic optimization", In Advances in Neural Information Processing Systems (NeurIPS), Online, 2021.

S. Khirirat, X. Wang, S. Magnússon, and M. Johansson, "Improved step-size schedules for noisy gradient methods", In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Online, 2021.

S. Khirirat, S. Magnússon, A. Aytekin, and M. Johansson, "A flexible framework for communication-efficient machine learning", In Proceedings of the AAAI Conference on Artificial Intelligence, Online, 2021.

H. Shokri-Ghadikolaei and S. Magnússon, "Communication-efficient Variance-reduced Stochastic Gradient Descent", IFAC 2020 World Congress, Berlin, Germany, 2020.

S. Magnússon, H. Shokri-Ghadikolaei, and N. Li, "On Maintaining Linear Convergence of Distributed Learning and Optimization under Limited Communication", 53rd Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, 2019.

S. Magnússon, C. Fischione, and N. Li, "Optimal Voltage Control Using Event Triggered Communication", ACM e-Energy conference, Phoenix, AR, 2019.

S. Khirirat, S. Magnússon, and M. Johansson, "Convergence Bounds For Compressed Gradient Methods With Memory Based Error Compensation", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Brighton, UK, 2019. [Best student paper award]

S. Magnússon, G. Qu, and N. Li, "Distributed Voltage Control with Communication Delays", IEEE American Control Conference (ACC), Philadelphia, PA, 2019.

S. Magnússon, G. Qu, C. Fischione and N. Li, "Voltage Control Using Limited Communication", IFAC World Congress, Toulouse, France, 2017.

S. Magnússon, C. Enyioha, N. Li, and C. Fischione, "Practical Coding Schemes For Bandwidth Limited One-Way Communication Resource Allocation", in 56th IEEE Conference on Decision and Control (CDC), Las Vegas, NV, 2016.

S. Magnússon, K. Heal, C. Enyioha, N. Li, C. Fischione, and V. Tarokh, "Convergence of Limited Communications Gradient Methods", in IEEE American Control Conference (ACC), Boston, MA, 2016.

S. Magnússon, M. Jakobsson, C. Fischione, and P. C. Weeraddana, "On Some Extensions of Fast-Lipschitz Optimization", in 2016 IEEE European Control Conference (ECC), Aalborg, Denmark, 2016.

S. Magnússon, P. C. Weeraddana, and C. Fischione, "A Distributed Approach for the Optimal Power Flow Problem", in IEEE European Control Conference (ECC), Aalborg, Denmark, 2016.

S. Magnússon, C. Enyioha, K. Heal, N. Li, C. Fischione, and V. Tarokh, "Distributed Resource Allocation Using One-Way Communication with Applications to Power Networks", IEEE 50th Annual Conference on Information Sciences and Systems (CISS), Princeton, NJ, 2016.

C. Enyioha, S. Magnússon, K. Heal, N. Li, C. Fischione and V. Tarokh, "Robustness Analysis for an Online Decentralized Descent Power allocation algorithm", in IEEE Information Theory and Applications Workshop (ITA), San Diego, CA, 2016.

S. Magnússon, P. C. Weeraddana, M. G. Rabbat, and C. Fischione, "On the Convergence of an Alternating Direction Penalty Method for Nonconvex Problems", IEEE 48th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, 2014.