Mikael Skoglund, Professor
| Dr. Skoglund received the Ph.D. degree in 1997 from Chalmers University of Technology,
Göteborg, Sweden. He was appointed Docent in Signal Processing
in February 2001 and Professor of Communication Theory in October
2003, both at KTH.
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During 2003-09 he was an associate editor for IEEE Trans. on Communications and in the period 2009-12 he was on the editorial board for IEEE Trans. on Information Theory. From 2021 he is once again an editor for IEEE Trans. on Information Theory. Skoglund was general co-chair for IEEE ITW 2019 (Visby, Gotland) and served as TPC co-chair for IEEE ISIT 2022 (Helsinki). Starting January 1st, 2023, he is an elected member of the IEEE Information Theory Society Board of Governors. Skoglund is a Fellow of the IEEE. |
| Address: Information Science and Engineering School of Electrical Engineering and Computer Science KTH Royal Institute of Technology 100 44 Stockholm, Sweden |
Office: KTH Main Campus Malvinas väg 10, Room A:415 |
| Email: skoglund@kth.se | Phone: +46 8 790 8430 |
| Personal web-page: people.kth.se/~skoglund | |
| KTH profile page: www.kth.se/profile/skoglund |
Recent Publications
- A. Gouverneur, B. Rodríguez Gálvez, T. Oechtering and M. Skoglund, "An information-theoretic analysis of Thompson sampling for logistic bandits," in Proc. NeurIPS 2024 (BDU Workshop ).
- A. Zamani and M. Skoglund, "Improving achievability of cache-aided private variable-length coding with zero leakage," in Proc. IEEE WiOpt 2024.
- B. Rodríguez Gálvez, R. Thobaben and M. Skoglund, "An information-theoretic approach to generalization theory," arXiv:2408.13275 [stat.ML], August 2024.
- C. Li, M. Xiao and M. Skoglund, "A communication-efficient semi-decentralized approach for federated learning with stragglers," in Proc. IEEE ITW 2024.
- V. Ramachandran, T. Oechtering and M. Skoglund, "Multi-terminal strong coordination with degraded source observations," in Proc. IEEE ITW 2024.
- A. Zamani, B. Rodríguez Gálvez and M. Skoglund, "Information theoretic fairness: Compressed representations with perfect demographic parity," in Proc. IEEE ITW 2024.
- S. Weng, C. Li, M. Xiao and M. Skoglund, "Cooperative gradient coding for collaborative federated learning," in Proc. IEEE Globecom 2024.
- S. Ye, S. Zhang, M. Xiao and M. Skoglund, "Integrated communication and computation empowered by fluid antenna array," in Proc. IEEE SPAWC 2024.
- S. Daei, M. Skoglund and G. Fodor, "Improved downlink channel estimation in time-varying FDD massive MIMO systems," in Proc. IEEE SPAWC 2024.
- M. Lindström, B. Rodríguez Gálvez, R. Thobaben and M. Skoglund, "A coding-theoretic analysis of hyperspherical prototypical learning geometry," in Proc. ICML 2024 (GRaM workshop).
- A. Gouverneur, B. Rodríguez Gálvez, T. Oechtering and M. Skoglund, "Chained information-theoretic bounds and tight regret rate for linear bandit problems," in Proc. ICML 2024 (workshop on found. RL and control).
- B. Rodríguez Gálvez, R. Thobaben and M. Skoglund, "More PAC-Bayes bounds: From bounded losses, to losses with general tail behaviors, to anytime-validity," in Proc. NeurIPS, 2024.
- C. Li and M. Skoglund, "Gradient coding in decentralized learning for evading stragglers," in Proc. EUSIPCO 2024.
- A. Zamani, T. Oechtering and M. Skoglund, "Statistical privacy mechanism design using separation technique," in Proc. EUSIPCO 2024.
- S. Daei, G. Fodor and M. Skoglund, "Optimal transmitter design and pilot spacing in MIMO non-stationary aging channels," in Proc. EUSIPCO 2024.
- S. Daei, M. Skoglund and G. Fodor, "Improved downlink channel estimation in time-varying FDD massive MIMO systems," arXiv:2405.07906.
- S. Rivetti, Ö. Tugfe Demir, E. Björnson and M. Skoglund "Destructive and constructive RIS beamforming in an ISAC-multi-user MIMO network," arXiv:2404.11314.
- S. Saedian, T. Oechtering and M. Skoglund, "Evaluating differential privacy on correlated datasets using pointwise maximal leakage," in Proc. Annual Privacy Forum, 2024.
- B. Rodríguez Gálvez, O. Rivasplata, R. Thobaben and M. Skoglund, "A note on generalization bounds for losses with finite moments," in Proc. IEEE ISIT 2024.
- L. Grosse, S. Saeidian, P. Sadeghi, T. Oechtering and M. Skoglund, "Quantifying privacy via information density," in Proc. IEEE ISIT 2024.
- A. Zamani, S. Daei, T. Oechtering and M. Skoglund, "Multi-task private semantic communication," in Proc. IEEE ISIT 2024.
- Y. Chen, T. Oechtering, H. Boche, M. Skoglund and Y. Luo, "Distribution-preserving integrated sensing and communication with secure reconstruction," in Proc. IEEE ISIT 2024.
- V. Ramachandran, T. Oechtering and M. Skoglund, "Multi-terminal strong coordination over noisy channels with secrecy constraints," in Proc. IEEE ISIT 2024.
- J. He, M. Xiao and M. Skoglund, "Fast-converging decentralized ADMM for consensus optimization," in Proc. IEEE CAI 2024.
- J. He, M. Xiao and M. Skoglund, "Straggler-resilient asynchronous decentralized ADMM for consensus optimization," in Proc. CISS 2024.
- S. Rivetti, E. Björnsson and M. Skoglund, "Secure spatial signal design for ISAC in a cell-free MIMO network," in Proc. IEEE WCNC 2024.
- D. Zhang, M. Xiao, M. Skoglund and H. V. Poor, "Federated learning via active RIS assisted over-the-air computation," in Proc. IEEE ICMLCN 2024.
- A. Zamani, S. Daei Omshi, T. Oechtering, D. Gunduz and M. Skoglund, "Semantic communication with privacy constraints," in Proc. IZS 2024.
- V. Ramachandran, T. Oechtering and M. Skoglund, "Multi-terminal strong coordination over noiseless networks with secrecy constraints," in Proc. IZS 2024.
- C. Ren et al., "Towards quantum federated learning," IEEE Transactions on Neural Networks and Learning Systems. Revised August 2024.
- D. Zhang, M. Xiao, C. Shi, M. Skoglund, Y. Li and H. V. Poor, "Beamforming design for active RIS-aided over-the-air computation," IEEE Transactions on Communications. Submitted November 2024.
- R. Takbiri, S. Daei, F. Haddadi and M. Skoglund, "Distribution-aware l1 analysis minimization," IEEE Transactions on Signal Processing. Submitted October 2024.
- M. M. Omati, S. Daei, A. Amini and M. Skoglund, "Doppler-robust optimization for joint MIMO transmit waveform and filter design in active sensing systems," IEEE Transactions on Signal Processing. Submitted October 2024.
- C. Li, M. Xiao and M. Skoglund, "Coded robust aggregation for distributed learning under Byzantine attacks," IEEE Transactions on Information Forensics & Security. Submitted October 2024.
- Y. Chen, T. Oechtering, H. Boche, M. Skoglund and Y. Luo, "Distribution-preserving integrated sensing and communication," IEEE Transactions on Information Theory. Submitted October 2024.
- C. Ren, Y. Tang, M. Skoglund, Z. Y. Dong, H. Yu, Y. Gao and M. Xiao, "QFEVAL: Quantum federated ensembled variational adaptive learning for dynamic security assessment in cyber-physical systems," IEEE Journal of Selected Areas in Communications. Submitted September 2024.
- C. Li, M. Xiao and M. Skoglund, "Adaptive coded federated learning: Privacy preservation and straggler mitigation," IEEE Transactions on Communications. Submitted September 2024.
- J. He, M. Xiao, M. Skoglund and H. V. Poor, "Straggler-resilient asynchronous ADMM for distributed consensus optimization," IEEE Transactions on Signal Processing. Submitted August 2024.
- S. Ul Zuhra, S. M. Perlaza, H. V. Poor and M. Skoglund, "Simultaneous information and energy transmission with short packets and finite constellations," IEEE Transactions on Communications. Submitted August 2024.
- S. Saeidian, L. Grosse, P. Sadeghi, M. Skoglund and T. Oechtering, "Information density bounds for privacy," IEEE Transactions on Information Theory. Submitted July 2024.
- S. Weng, M. Xiao, C. Ren and M. Skoglund, "Coded cooperative networks for semi-decentralized federated learning," IEEE Wireless Communications Letters. Submitted June 2024.
- C. Li, M. Xiao and M. Skoglund, "Sign-based distributed learning with Byzantine resilience based on audit mechanism," IEEE Transactions on Information Forensics and Security. Submitted June 2024.
- S. Daei, S. Razavikia, M. Skoglund, G. Fodor and C. Fischione, "Timely and painless breakups: Off-the-grid blind message recovery and users' demixing," IEEE Transactions on Information Theory. Submitted June 2024.
- H.S. F. Ardakani, S. Daei, A. Amini, M. Skoglund and G. Fodor, "Subspace-informed matrix completion," IEEE Transactions on Signal Processing. Submitted May 2024.
- C. Li, M. Xiao and M. Skoglund, "Communication-efficient semi-decentralized federated learning in the presence of stragglers," IEEE Transactions on Communications. Submitted April 2024.
- J. He, M. Xiao and M. Skoglund, "Fast-converging decentralized ADMM for consensus optimization in distributed systems," IEEE Transactions on Parallel and Distributed Systems. Submitted April 2024.
- G. Cervia, T. Oechtering and M. Skoglund, "Finite blocklength strong coordination," IEEE Transactions on Information Theory. Submitted March 2024.
- S. Daei, G. Fodor and M. Skoglund, "Exploiting spatial and temporal correlations in massive MIMO systems over non-stationary aging channels," IEEE Transactions on Wireless Communications. Submitted March 2024.
- Y. Chen, T. Oechtering, M. Skoglund and Y. Luo, "On general capacity-distortion formulas of integrated sensing and communication," in IEEE Transactions on Information Theory. Submitted October 2023.
- Y. Gao, C. Ren, H. Yu, M. Xiao and M. Skoglund, "Fairness-aware multi-server federated learning task delegation over wireless networks," IEEE Transactions on Network Science and Engineering. Accepted for publication. (Revised August 2024.)
- S. Daei, G. Fodor, M. Skoglund and M. Telek, "Towards optimal pilot spacing and power control in multi-antenna systems operating over non-stationary Rician aging channels," IEEE Transactions on Communications. Accepted for publication. (Submitted December 2023.) IEEE Transactions on Signal Processing. Accepted for publication. (Submitted February 2024.)
- S. Saeidian, G. Cervia, T. Oechtering and M. Skoglund, "Rethinking disclosure prevention with pointwise maximal leakage," Journal of Privacy and Confidentiality. Accepted for publication. (Submitted July 2023.)
- C. Ren, Z. Y. Dong, M. Skoglund, Y. Gao, T. Wang and R. Zhang "Enhancing dynamic security assessment in smart grids through quantum federated learning," IEEE Transactions on Automation Science and Engineering. Accepted for publication.
- C. Li and M. Skoglund, "Decentralized learning based on gradient coding with compressed communication," IEEE Transactions on Signal Processing, vol. 72, pp. 4713-4729, 2024.
- T. Tanaka, V. Zinage, V. Ugrinovskii and M. Skoglund, "Continuous-time channel gain control for minimum-information Kalman-Bucy filtering," IEEE Transactions on Automatic Control, vol. 69, no. 10, pp. 7255-7262, October 2024.
- C. Li and M. Skoglund, "Distributed learning based on 1-bit gradient coding in the presence of stragglers," IEEE Transactions on Communications, vol. 72, no. 8, pp. 4903-4916, August 2024.
- P. Stavrou and M. Skoglund, "Indirect NRDF for partially observable Gauss-Markov processes with MSE distortion: Characterizations and optimal solutions," IEEE Transactions on Automatic Control, vol. 69, no. 9, pp. 5867-5882, September 2024.
- S. Rivetti, Ö. T. Demir, E. Björnson and M. Skoglund, "Malicious reconfigurable intelligent surfaces: How impactful can destructive beamforming be?," IEEE Wireless Communications Letters, vol. 13, no. 7, pp. 1918-1922, July 2024.
- D. Zhang, S. Ye, M. Xiao, K. Wang, M. Di Renzo and M. Skoglund, "Fluid antenna array enhanced over-the-air computation," IEEE Wireless Communications Letters, vol. 13, no. 6, pp. 1541-1545, June 2024.
- B. Rodríguez Gálvez, R. Thobaben and M. Skoglund, "More PAC-Bayes bounds: From bounded losses, to losses with general tail behaviors, to anytime-validity," Journal of Machine Learning Research, vol. 25, no. 110, pp. 1-43, March 2024.
- A. Zamani, T. Oechtering and M. Skoglund, "On the privacy-utility trade-off with and without direct access to the private data," IEEE Transactions on Information Theory, vol. 70, no. 3, pp. 2177-2200, March 2024.
Present Postdocs
Former Postdocs
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Present Ph.D. Students
Former Ph.D. Students as Main Advisor
Former Ph.D. Students as Co-Advisor
Teaching
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