Prof. Dr.-Ing. Setareh Maghsudi
Professor
Address:
Ruhr-University Bochum
Faculty for Electrical Engineering and Information Technology
Learning technical Systems
Postbox ID 4
Universitätsstraße 150
D-44801 Bochum
Room:
ID 2/469
Phone:
(+49)(0)234 / 32 - 12777
E-Mail:
setareh.maghsudi(at)rub.de
Website
www.etit.ruhr-uni-bochum.de/en/lts/'
0000-0002-0647-611X
Curriculum Vitae
| Since 08.2023 | Professor, Ruhr-University Bochum - Faculty of Electrical Engineering and Information Technology |
| 2020 - 2023 | Assistant Professor, University of Tübingen - Department of Informatics |
| 2019 | Post-doctoral Fellow, Kyushu University - Department of Informatics |
| 2017 - 2020 | Assitant Professor, Technical University of Berlin - Faculty of Electrical Engineering and Computer Science |
| 2016 - 2017 | Post-doctoral Fellow, Yale University - School of Engineering and Applied Science |
| 2015 - 2016 | Post-doctoral Associate, University of Manitoba - Department of Electrical and Computer Engineering |
| 2011 - 2015 | Ph.D. Student and Postdoc, Technical University of Berlin - Faculty of Electrical Engineering and Computer Science |
| 2008 - 2010 | M.Sc. Student, Kiel University - Faculty of Engineering |
2025
[1]
X. Cheng, B. Nourani-Koliji, and S. Maghsudi, ‘Online Influence Maximization With Semi-Bandit Feedback Under Corruptions’, IEEE transactions on network science and engineering, vol. 2025, Art. no. 10909361, 2025, doi: 10.1109/tnse.2025.3547240.
2024
[1]
X. Cheng and S. Maghsudi, ‘Distributed consensus algorithm for decision-making in multi-agent multi-armed bandit’,
IEEE transactions on control of network systems, vol. 2024, May 2024, doi: 10.1109/tcns.2024.3395850.
[2]
X. Cheng, I. Tsetis, and S. Maghsudi, ‘Distributed Management of Fluctuating Energy Resources in Dynamic Networked Systems’, IEEE transactions on network science and engineering, vol. 12, no. 1, pp. 54–69, Oct. 2024, doi: 10.1109/tnse.2024.3484149.
2023
[1]
X. Cheng and S. Maghsudi, ‘Distributed task management in fog computing: a socially concave bandit game’, IEEE transactions on green communications and networking, vol. 7, no. 3, pp. 1486–1500, Sep. 2023, doi: 10.1109/tgcn.2023.3276415.
[2]
A.-R. Ehyaei, A.-H. Karimi, B. Schölkopf, and S. Maghsudi, ‘Robustness implies fairness in causal algorithmic recourse’, in Proceedings of the 6th ACM conference on fairness, accountability, and transparency (FAcct 2023), Chicago , 2023, pp. 984–1001. doi: 10.1145/3593013.3594057.
[3]
I. Tsetis, X. Cheng, and S. Maghsudi, ‘A bandit online convex optimization approach to distributed energy management in networked systems’, in IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2023, Rhodes Island, 2023, Published. doi: 10.1109/icassp49357.2023.10095936.
[4]
Y. Cao, T. Ohtsuki, S. Maghsudi, and T. Q. S. Quek, ‘Deep learning and image super-resolution-guided beam and power allocation for mmWave networks’, IEEE transactions on vehicular technology / Institute of Electrical and Electronics Engineers, vol. 72, no. 11, pp. 15080–15085, Jun. 2023, doi: 10.1109/tvt.2023.3282429.
[5]
A. R. Balef and S. Maghsudi, ‘Piecewise-stationary multi-objective multi-armed bandit with application to joint communications and sensing’, IEEE wireless communications letters, vol. 12, no. 5, pp. 809–813, 2023, doi: 10.1109/lwc.2023.3244686.
[6]
S. Bilaj, S. Dhouib, and S. Maghsudi, ‘Hypothesis transfer in bandits by weighted models’, in Machine learning and knowledge discovery in databases, Part IV, Grenoble, 2023, vol. 13716, pp. 284–299. doi: 10.1007/978-3-031-26412-2_18.
[7]
M. M. Caliskan, F. Chini, and S. Maghsudi, ‘Multi-agent learning from learners’, in Proceedings of the 40th International Conference on Machine Learning (ICML 2023), 2023, vol. 202, pp. 3525–3540.
[8]
X. Cheng, C. Pan, and S. Maghsudi, ‘Parallel online clustering of bandits via hedonic game’, in Proceedings of the 40th International Conference on Machine Learning (ICML 2023), 2023, vol. 202, pp. 5485–5503.
[9]
M. Eberhardinger, J. Maucher, and S. Maghsudi, ‘Towards explainable decision making with neural program synthesis and library learning’, in Neural-Symbolic Learning and Reasoning 2023, Siena, 2023, vol. 3432, pp. 348–368.
[10]
D. Ashlock, S. Maghsudi, D. P. Liebana, P. Spronck, and M. Eberhardinger, Eds., Human-Game AI Interaction: Dagstuhl Seminar 22251, Jun 19 – Jun 24, 2022, no. 6. Wadern: Schloss Dagstuhl, 2023. doi: 10.4230/dagrep.12.6.28.
[11]
S. Dai, S. Maghsudi, L. Thiele, and S. Stanczak, ‘Overhead reduction in UAV-assisted federated learning with fast-varying environment’, in WSA & SCC 2023, Braunschweig, 2023, vol. 308. [Online]. Available: https://ieeexplore.ieee.org/document/10104035
[12]
A. R. Balef, S. Maghsudi, and S. Stanczak, ‘Adaptive energy-efficient waveform design for joint communication and sensing using multiobjective multiarmed bandits’, in WSA & SCC 2023, Braunschweig, 2023, vol. 308. [Online]. Available: https://ieeexplore.ieee.org/document/10104580
[13]
D. P. Liebana, D. Cakmak, S. Maghsudi, P. Spronck, and T. Thompson, ‘The tabletop board games AI tutor’, in Dagstuhl Reports, Wadern, Schloss Dagstuhl, 2023, vol. 12, no. 6.
[14]
Q. He, T. Zhou, M. Fang, and S. Maghsudi, ‘Eigensubspace of Temporal-Difference Dynamics and How It Improves Value Approximation in Reinforcement Learning’, in Machine learning and knowledge discovery in databases: research track, Turin, Sep. 2023, vol. 14172, pp. 573–589. doi: 10.1007/978-3-031-43421-1_34.
2022
[1]
M. Yahya, S. Maghsudi, and S. Stanczak, ‘Federated learning in UAV-enhanced networks: joint coverage and convergence time optimization’, in European Wireless 2022, Dresden, 2022, pp. 40–46.
[2]
B. Nourani-Koliji, S. Ghoorchian, and S. Maghsudi, ‘Linear combinatorial semi-bandit with causally related rewards’, in Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, Wien, 2022, pp. 4878–4884.
[3]
A. Bozorgchenani, S. Maghsudi, D. Tarchi, and E. Hossain, ‘Computation offloading in heterogeneous vehicular edge networks: on-line and off-policy bandit solutions’, IEEE transactions on mobile computing, vol. 21, no. 12, pp. 4233–4248, Dec. 2022, doi: 10.1109/tmc.2021.3082927.
[4]
N. Agrawal et al., ‘A learning-based approach to approximate coded computation’, in 2022 IEEE Information Theory Workshop (ITW), Mumbai, Dec. 2022, pp. 600–605. doi: 10.1109/itw54588.2022.9965865.
[5]
A. H. C. Vlot, S. Maghsudi, and U. Ohler, ‘Cluster-independent marker feature identification from single-cell omics data using SEMITONES’, Nucleic acids research, vol. 50, no. 18, Art. no. e107, Oct. 2022, doi: 10.1093/nar/gkac639.
[6]
X. Cheng and S. Maghsudi, ‘Distributed task management in the heterogeneous fog: a socially concave bandit game’, in 2022 IEEE 23rd International Workshop on Signal Processing Advances in Wireless Communication (SPAWC), Oulu, 2022, Published. doi: 10.1109/spawc51304.2022.9833943.
[7]
F. Fredj, Y. Al-Eryani, S. Maghsudi, M. Akrout, and E. Hossain, ‘Distributed beamforming techniques for cell-free wireless networks using deep reinforcement learning’, IEEE transactions on cognitive communications and networking, vol. 8, no. 2, pp. 1186–1201, Apr. 2022, doi: 10.1109/tccn.2022.3165810.
[8]
M. Yahya and S. Maghsudi, ‘Joint coverage and resource allocation for federated learning in UAV-enabled networks’, in 2022 IEEE Wireless Communications and Networking Conference (WCNC), Austin, May 2022, pp. 2476–2481. doi: 10.1109/wcnc51071.2022.9771880.
[9]
A. Y. Ding et al., ‘Roadmap for edge AI: a dagstuhl perspective’, Computer communication review, vol. 52, no. 1, pp. 28–33, 2022, doi: 10.1145/3523230.3523235.
[10]
M. Eberhardinger, J. Maucher, and S. Maghsudi, ‘Imitation learning of logical program policies for multi-agent reinforcement learning’, in KI 2022 Workshops, Tutorials and Doctoral Consortium, Trier, 2022, vol. 3457.
2021
[1]
O. Atan, S. Ghoorchian, S. Maghsudi, and M. van der Schaar, ‘Data-driven online recommender systems with costly information acquisition’, IEEE transactions on services computing / Institute of Electrical and Electronics Engineers, vol. 16, no. 1, pp. 235–245, Sep. 2021, doi: 10.1109/tsc.2021.3113002.
[2]
B. Ghosh, M. Motagh, M. H. Haghighi, M. S. Vassileva, T. R. Walter, and S. Maghsudi, ‘Automatic detection of volcanic unrest using blind source separation with a minimum spanning tree based stability analysis’, IEEE journal of selected topics in applied earth observations and remote sensing / Institute of Electrical and Electronics Engineers, vol. 14, pp. 7771–7787, Jul. 2021, doi: 10.1109/jstars.2021.3097895.
[3]
B. Ghosh, M. Haghshenas Haghighi, M. Motagh, and S. Maghsudi, ‘Using generative adversarial networks for extraction of insar signals from large-scale Sentinel-1 interferograms by improving tropospheric noise correction’, in ISPRS annals of the photogrammetry, remote sensing and spatial information sciences, online, Jun. 2021, vol. 5, no. 3. doi: 10.5194/isprs-annals-v-3-2021-57-2021.
[4]
Y. Cao, S. Maghsudi, and T. Ohtsuki, ‘Mobility-aware routing and caching: a federated learning assisted approach’, in ICC 2021 - IEEE International Conference on Communications, Montreal, Quebec, Aug. 2021, Published. doi: 10.1109/icc42927.2021.9500804.
[5]
S. Maghsudi, A. Lan, J. Xu, and M. van der Schaar, ‘Personalized education in the artificial intelligence era: what to expect next’, IEEE signal processing magazine / Institute of Electrical and Electronics Engineers, vol. 38, no. 3, pp. 37–50, Apr. 2021, doi: 10.1109/msp.2021.3055032.
[6]
V. Mittal, S. Maghsudi, and E. Hossain, ‘Distributed cooperation under uncertainty in drone-based wireless networks: a bayesian coalitional game’, IEEE transactions on mobile computing, vol. 22, no. 1, pp. 206–221, Apr. 2021, doi: 10.1109/tmc.2021.3073772.
2020
[1]
A. Bozorgchenani, S. Maghsudi, D. Tarchi, and E. Hossain, ‘Computation offloading in heterogeneous vehicular edge networks: on-line and off-policy bandit solutions’, IEEE transactions on mobile computing, vol. 21, no. 12, pp. 4233–4248, 2020, doi: 10.1109/tmc.2021.3082927.
[2]
S. Maghsudi and M. Davy, ‘Computational models of human decision-making with application to the internet of everything’, IEEE wireless communications / Institute of Electrical and Electronics Engineers, vol. 28, no. 1, pp. 152–159, Nov. 2020, doi: 10.1109/mwc.001.2000250.
[3]
S. Bayhan, S. Maghsudi, and A. Zubow, ‘EdgeDASH: exploiting network-assisted adaptive video streaming for edge caching’, IEEE transactions on network and service management, vol. 18, no. 2, Art. no. 9253667, Nov. 2020, doi: 10.1109/tnsm.2020.3037147.
[4]
S. Ghoorchian and S. Maghsudi, ‘Multi-armed bandit for energy-efficient and delay-sensitive edge computing in dynamic networks with uncertainty’, IEEE transactions on cognitive communications and networking, vol. 7, no. 1, Art. no. 9151218, Jul. 2020, doi: 10.1109/tccn.2020.3012445.
[5]
S. Maghsudi and M. van der Schaar, ‘A non-stationary bandit-learning approach to energy-efficient femto-caching with rateless-coded transmission’, IEEE transactions on wireless communications / Institute of Electrical and Electronics Engineers, vol. 19, no. 7, pp. 5040–5056, Apr. 2020, doi: 10.1109/twc.2020.2989179.
[6]
D. Bermbach, S. Maghsudi, J. Hasenburg, and T. Pfandzelter, ‘Towards auction-based function placement in serverless fog platforms’, in 2020 IEEE international conference on fog computing, online, 2020, pp. 25–31. doi: 10.1109/icfc49376.2020.00012.
[7]
U. Habiba, S. Maghsudi, and E. Hossain, ‘A reverse auction model for efficient resource allocation in mobile edge computation offloading’, in 2019 IEEE global communications conference (GLOBECOM), Waikoloa, 2020, Published. doi: 10.1109/globecom38437.2019.9014240.
[8]
S. Maghsudi and M. van der Schaar, ‘A bandit learning approach to energy-efficient femto-caching under uncertainty’, in 2019 IEEE global communications conference (GLOBECOM), Waikoloa, 2020, Published. doi: 10.1109/globecom38437.2019.9013630.
[9]
B. Ghosh, M. Motagh, M. Haghshenas Haghighi, and S. Maghsudi, ‘Automatic flood monitoring based on SAR intensity and interferometric coherence using machine learning’, in EGU General Assembly 2020, 2020, Published. doi: 10.5194/egusphere-egu2020-12954.
[10]
K. Hoffmann et al., ‘Human-AI coordination’, in Dagstuhl Reports, Wadern, Schloss Dagstuhl, 2020, vol. 9, no. 12.
[11]
S. Samothrakis, B. Bouzy, M. Buro, S. Maghsudi, T. P. Rúnarsson, and T. Schaul, ‘Learning to learn’, in Dagstuhl Reports, Wadern, Schloss Dagstuhl, 2020, vol. 9, no. 12.
2019
[1]
S. Maghsudi and M. Van Der Schaar, ‘Distributed task management in cyber-physical systems: how to cooperate under uncertainty?’, in 2018 IEEE Global Communications Conference (GLOBECOM), Abu Dhabi, Feb. 2019, Published. doi: 10.1109/glocom.2018.8647643.
[2]
S. Eshghi, S. Maghsudi, V. Restocchi, S. Stein, and L. Tassiulas, ‘Efficient influence maximization under network uncertainty’, in IEEE INFOCOM 2019 - IEEE Conference on Computer Communications (INFOCOM WKSHPS 2019), Paris, Sep. 2019, pp. 365–371. doi: 10.1109/infcomw.2019.8845088.
2018
[1]
S. Maghsudi and M. van der Schaar, ‘Distributed task management in cyber-physical systems: how to cooperate under uncertainty?’, IEEE transactions on cognitive communications and networking, vol. 5, no. 1, pp. 165–180, Dec. 2018, doi: 10.1109/tccn.2018.2888970.
[2]
P. Semasinghe, E. Hossain, and S. Maghsudi, ‘Cheat-proof distributed power control in full-duplex small cell networks: a repeated game with imperfect public monitoring’, IEEE transactions on communications / Institute of Electrical and Electronics Engineers, vol. 66, no. 4, pp. 1787–1802, 2018, doi: 10.1109/tcomm.2017.2785765.
[3]
S. Maghsudi and D. Niyato, ‘On power-efficient planning in dynamic small cell networks’, IEEE wireless communications letters, vol. 7, no. 3, pp. 304–307, 2018, doi: 10.1109/lwc.2017.2773598.
[4]
S. Ranadheera, S. Maghsudi, and E. Hossain, ‘Computation offloading and activation of mobile edge computing servers: a minority game’, IEEE wireless communications letters, vol. 7, no. 5, pp. 688–691, 2018, doi: 10.1109/lwc.2018.2810292.
[5]
S. Stein, S. Eshghi, S. Maghsudi, L. Tassiulas, R. K. E. Bellamy, and N. R. Jennings, ‘Influence maximisation beyond organisational boundaries’, in 2017 IEEE SmartWorld, San Francisco, 2018, Published. doi: 10.1109/uic-atc.2017.8397422.
2017
[1]
S. Maghsudi and D. Niyato, ‘On transmission mode selection in D2D-enhanced small cell networks’, IEEE wireless communications letters, vol. 6, no. 5, pp. 618–621, 2017, doi: 10.1109/lwc.2017.2723558.
[2]
S. Maghsudi and E. Hossain, ‘Distributed user association in energy harvesting small cell networks: an exchange economy with uncertainty’, IEEE transactions on green communications and networking, vol. 1, no. 3, pp. 294–308, 2017, doi: 10.1109/tgcn.2017.2715349.
[3]
P. Semasinghe, S. Maghsudi, and E. Hossain, ‘Game theoretic mechanisms for resource management in massive wireless IoT systems’, IEEE communications magazine / Institute of Electrical and Electronics Engineers, vol. 55, no. 2, pp. 121–127, 2017, doi: 10.1109/mcom.2017.1600568cm.
[4]
S. Ranadheera, S. Maghsudi, and E. Hossain, ‘Minority games with applications to distributed decision making and control in wireless networks’, IEEE wireless communications / Institute of Electrical and Electronics Engineers, vol. 24, no. 5, pp. 184–192, 2017, doi: 10.1109/mwc.2017.1600351wc.
[5]
S. Maghsudi and E. Hossain, ‘Distributed user association in energy harvesting dense small cell networks: a mean-field multi-armed bandit approach’, IEEE access / Institute of Electrical and Electronics Engineers, vol. 5, pp. 3513–3523, 2017, doi: 10.1109/access.2017.2676166.
[6]
S. Maghsudi and E. Hossain, ‘Distributed user association in energy harvesting small cell networks: a probabilistic bandit model’, IEEE transactions on wireless communications / Institute of Electrical and Electronics Engineers, vol. 16, no. 3, pp. 1549–1563, 2017, doi: 10.1109/twc.2017.2647946.
[7]
S. Stein, S. Eshghi, S. Maghsudi, L. Tassiulas, R. K. E. Bellamy, and N. R. Jennings, ‘Heuristic algorithms for influence maximization in partially observable social networks’, in 3rd International Workshop on Social Influence Analysis (SocInf 2017), Melbourne, 2017, vol. 1893, pp. 20–32.
2016
[1]
S. Maghsudi and E. Hossain, ‘Distributed downlink user association in small cell networks with energy harvesting’, in 2016 IEEE International Conference on Communications Workshops (ICC) took place May 23-28, 2016 in Kuala Lumpur, Malaysia, Kuala Lumpur, 2016, Published. doi: 10.1109/icc.2016.7511068.
[2]
S. Maghsudi and S. Stańczak, ‘Distributed channel selection for underlay device-to-device communications: a game-theoretical learning framework’, in Communications in interference limited networks, 1st ed., W. Utschick, Ed. Cham: Springer International Publishing, 2016, pp. 173–190. doi: 10.1007/978-3-319-22440-4_8.
[3]
S. Maghsudi and E. Hossain, ‘Multi-armed bandits with application to 5G small cells’, IEEE wireless communications / Institute of Electrical and Electronics Engineers, vol. 23, no. 3, pp. 64–73, Jun. 2016, doi: 10.1109/mwc.2016.7498076.
2015
[1]
B. Nikfar, S. Maghsudi, and A. J. Han Vinck, ‘Multi-armed bandit channel selection for power line communication’, in 2015 IEEE International Conference on Smart Grid Communications (SmartGridComm), Miami, 2015, pp. 19–24. doi: 10.1109/smartgridcomm.2015.7436270.
[2]
S. Maghsudi and S. Stanczak, ‘On channel selection for energy-constrained rateless-coded D2D communications’, in 2015 23rd European Signal Processing Conference (EUSIPCO), Nizza, Dec. 2015, pp. 1028–1032. doi: 10.1109/eusipco.2015.7362539.
[3]
S. Maghsudi and S. Stanczak, ‘Joint channel allocation and power control for underlay D2D transmission’, in 2015 IEEE International Conference on Communications (ICC), London, Sep. 2015, pp. 2091–2096. doi: 10.1109/icc.2015.7248634.
[4]
S. Maghsudi and S. Stanczak, ‘Hybrid centralized–distributed resource allocation for device-to-device communication underlaying cellular networks’, IEEE transactions on vehicular technology / Institute of Electrical and Electronics Engineers, vol. 65, no. 4, pp. 2481–2495, Apr. 2015, doi: 10.1109/tvt.2015.2423691.
[5]
S. Maghsudi, ‘Distributed resource allocation in wireless networks: a game-theoretical learning framework’, Universitätsbibliothek, Technische Universität Berlin , Berlin, 2015. doi: 10.14279/depositonce-4408.
2014
[1]
S. Maghsudi and S. Stańczak, ‘Joint channel selection and power control in infrastructureless wireless networks: a multiplayer multiarmed bandit framework’, IEEE transactions on vehicular technology / Institute of Electrical and Electronics Engineers, vol. 64, no. 10, Art. no. 6953296, Nov. 2014, doi: 10.1109/tvt.2014.2369425.
[2]
S. Maghsudi and S. Stanczak, ‘Transmission mode selection for network-assisted device to device communication: a levy-bandit approach’, in 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014), Florenz, 2014, pp. 7009–7013. doi: 10.1109/icassp.2014.6854959.
[3]
S. Maghsudi and S. Stanczak, ‘Channel selection for network-assisted D2D communication via no-regret bandit learning with calibrated forecasting’, IEEE transactions on wireless communications / Institute of Electrical and Electronics Engineers, vol. 14, no. 3, pp. 1309–1322, Oct. 2014, doi: 10.1109/twc.2014.2365803.
2013
[1]
S. Maghsudi and S. Stanaczak, ‘Dynamic bandit with covariates: strategic solutions with application to wireless resource allocation’, in 2013 IEEE international conference on communications (ICC), Budapest, Nov. 2013, pp. 5898–5902. doi: 10.1109/icc.2013.6655540.
[2]
S. Maghsudi and S. Stanczak, ‘Relay selection problem in wireless networks: a solution concept based on stochastic bandits and calibrated forecasters’, in 2013 IEEE 14th Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2013), Darmstadt, 2013, pp. 385–389. doi: 10.1109/spawc.2013.6612077.
[3]
S. Maghsudi and S. Stanczak, ‘Relay selection with no side information: an adversarial bandit approach’, in IEEE Wireless Communications and Networking Conference; WCNC, Jul. 2013, pp. 715–720. doi: 10.1109/wcnc.2013.6554651.
2012
[1]
S. Maghsudi and S. Stanczak, ‘On network-coded rateless transmission: protocol design, clustering and cooperator assignment’, in 2012 International Symposium on Wireless Communication Systems (ISWCS), Paris, Oct. 2012, pp. 306–310. doi: 10.1109/iswcs.2012.6328379.
[2]
S. Maghsudi and S. Stanczak, ‘A delay-constrained rateless coded incremental relaying protocol for two-hop transmission’, in 2012 IEEE Wireless Communications and Networking Conference (WCNC), Paris, 2012, pp. 168–172. doi: 10.1109/wcnc.2012.6214055.
[3]
S. Maghsudi and S. Stanczak, ‘Joint power allocation and relay selection for network-coded two-way relaying’, in 2012 46th Annual Conference on Information Sciences and Systems (CISS), Princeton, NJ, 2012, Published. doi: 10.1109/ciss.2012.6310805.
[4]
S. Maghsudi and S. Stanczak, ‘A hybrid centralized-decentralized resource allocation scheme for two-hop transmission’, in 8th International Symposium on Wireless Communication Systems (ISWCS), 2011, Aachen, 2012, pp. 96–100. doi: 10.1109/iswcs.2011.6125317.
2011
[1]
B. Nikfar and S. Maghsudi, ‘A new bandwidth allocation scheme for dual-hop transmission using virtual oligopoly market model and Cournot competition’, in 2011 IEEE Swedish Communication Technologies Workshop (Swe-CTW), Stockholm, 2011, pp. 98–102. doi: 10.1109/swe-ctw.2011.6082497.
