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Marie Siew I'm currently a Faculty Early Career Award (FECA) Fellow in the Information Systems Technology and Design Pillar (ISTD) at the Singapore University of Technology and Design (SUTD). I was a postdoctoral researcher in the ECE department, Carnegie Mellon University, advised by Prof Carlee Joe-Wong. I obtained my PhD from SUTD in 2021, advised by Prof Tony Quek and Dr Desmond Cai. Prior to that, I obtained my BSc. in Mathematical Sciences, from Nanyang Technological University, Singapore in 2016. Research Interests My research broadly revolves around resource allocation for enabling distributed intelligence in networked systems. In particular, I have worked on edge computing resource allocation from the perspective of user and device heterogeneity, in terms of differing incentives and differing latency and compute requirements; statistical resource allocation for multiple model federated learning; along with other resources allocation strategies to enable intelligence and decision making in networked systems. My research uses tools from Mathematical Modelling and Analysis, Machine Learning, Optimization, Mechanism Design and Network Economics, and Game Theory. I am currently also exploring human in the loop learning in networked systems, and foundation model/LLM enhanced edge and IoT intelligence. Email: [email protected] Google Scholar, LinkedIn, University webpage In my free time, I enjoy reading mystery novels, watercolor painting, cooking, exploring new places, and watching movies! Publications: Working papers: 1. Marie Siew, Shikhar Sharma, Zekai Li, Kun Guo, Chao Xu, Tania Lorido-Botran, Tony Q. S. Quek and Carlee Joe-Wong, "FIRE: A Failure-Adaptive Reinforcement Learning Framework for Edge Computing Migrations," submitted. [Preprint link]. 2. Marie Siew, Yi Hu, Shikhar Sharma, Zekai Li, Lingxiang Li, Tania Lorido-Botran, and Carlee Joe-Wong, "Towards Resilient Edge Computing: a Failure-Aware Reinforcement Learning Framework". 3. Marie Siew, Haoran Zhang, Jong-Ik Park, Yuezhou Liu, Yichen Ruan, Lili Su, Stratis Ioannidis, Edmund Yeh, and Carlee Joe-Wong, "Fair Concurrent Training of Multiple Models in Federated Learning" [Preprint link] 4. Kai Han, Marie Siew*, Bingbing Xu, Shengjun Guo Wenbin Gong*, Tony Q. S. Quek*, and Qianyi Ren, "On-Demand Optimization Method for Cross-Layer Topology in Multi-Task VLEO and Mega-LEO Heterogeneous Satellite Networks", submitted. [Preprint link] *corresponding authors 5. "Distributed ML paper", submitted. 6. Kai Han, Marie Siew*, Bingbing Xu, Shengjun Guo, Tianxiang Wang, Wenbin Gong*, Tony Q. S. Quek*, and Qianyi Ren, "A Distributed Collaborative Data Relay Method: VLEO Earth Observation Constellation Cross-Layer Access to the Mega-LEO Satellite Internet", submitted. [Preprint link] 7. Xuang Liang, Jianhua Tang, Marie Siew, and Tony Q. S. Quek, "Adaptive Clustering- Enabled Large-Scale Decentralized Federated Learning", submitted. Peer-reviewed Publications: 16. Kai Han, Bingbing Xu, Marie Siew*, Wenbin Gong*, Tony Q. S. Quek*, and Qianyi Ren, "Distributed Multi-objective Topology Optimization Method in VLEO-LEO Satellite Networks", in Proc. IEEE Global Communications Conference (GLOBECOM), Cape Town, South Africa, December 2024. *corresponding authors 15. Haoran Zhang, Zekai Li, Zejun Gong, Marie Siew*, Carlee Joe-Wong, Rachid El-Azouzi, "Optimal Variance-Reduced Client Sampling for Multiple Model Federated Learning", in Proc. IEEE International Conference on Distributed Computing Systems (ICDCS Posters), Jersey City, July 2024. [preprint link] [poster link] *corresponding author Best Poster Award!! 14. Hanqing Yang, Marie Siew*, and Carlee Joe-Wong, "An LLM-Based Digital Twin for Optimizing Human-in-the Loop Systems" in International Workshop on Foundation Models for Cyber-Physical Systems & Internet of Things (FMSys), held at CPS-IoT Week, Hong Kong, May 2024. [Preprint link] *corresponding author 13. Sha Xie, Marie Siew, Lingxiang Li, Zhi Chen, Tianlong Yang, "Minimizing the THz Communication Outage Probability with ISAC for Delay-Sensitive Services", in Proc. IEEE Global Communications Conference (GLOBECOM), Kuala Lumpur, December 2023. [Link] 12. Marie Siew, Shikhar Sharma, Kun Guo, Desmond Cai, Wanli Wen, Carlee Joe-Wong, Tony Q. S. Quek, "Towards Effective Resource Procurement in MEC: a Resource Re-selling Framework", IEEE Trans. Services Computing (TSC), 2023. [IEEE Xplore Early Access link] [Preprint link] 11. Xiongyue Wu, Jianhua Tang, and Marie Siew, “Digital Twin-assisted Semi-Federated Learning Framework for Industrial Edge Intelligence,” China Communications, accepted, 2023. [Link] 10. Yuezhou Liu, Lili Su, Carlee Joe-Wong, Stratis Ioannidis, Edmund Yeh, Marie Siew, "Cache enabled federated learning systems", in Proc. International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing (ACM MobiHoc), Washington DC, October 2023. [Link] 9. Shuying Gan, Marie Siew, Chao Xu and Tony Q. S. Quek, "Differentially Private Deep Q-Learning for Pattern Privacy Preservation in MEC Offloading", in Proc. IEEE International Conference on Communications (ICC), Rome, May 2023. [Link] [Preprint Link] 8. Marie Siew, Shoba Arunasalam, Yichen Ruan, Ziwei Zhu, Lili Su, Stratis Ioannidis, Edmund Yeh, and Carlee Joe-Wong, "Fair Training of Multiple Federated Learning Models on Resource Constrained Network Devices", in Proc ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN Posters, CPS-IoT Week), San Antonio, May 2023. [Link] Best Poster Award! [Link] 7. Marie Siew, Shikhar Sharma, and Carlee Joe-Wong, "ACRE: Actor Critic Reinforcement Learning for Failure-Aware Edge Computing Migrations", in Proc. IEEE Conference on Information Science and Systems (CISS), Baltimore, March 2023. [Link] 6. Lingxiang Li, Marie Siew, Tony Q. S. Quek, and Zhi Chen, “Optimal Pricing for Job Offloading in the MEC System with Two Priority Classes,” IEEE Trans. Vehicular Technology (TVT), vol. 70, no. 8, pp. 8080-8091, Aug. 2021. [LINK] 5. Marie Siew, Kun Guo, Desmond Cai, Lingxiang Li, and Tony Q. S. Quek, "Let’s Share VMs: Optimal Placement and Pricing across Base Stations in MEC Systems," in Proc. IEEE International Conference on Computer Communications (INFOCOM), May 2021. [Link],[Preprint LINK] 4. Marie Siew, Desmond Cai, Lingxiang Li, and Tony Q. S. Quek, “A Sharing-Economy Inspired Pricing Mechanism for Multi-Access Edge Computing,” in Proc. IEEE Global Communications Conference (GLOBECOM), Taipei, Dec 2020. [LINK] 3. Marie Siew, Desmond Cai, Lingxiang Li, Tony Q. S. Quek, "Dynamic Pricing for Resource-Quota Sharing in Multi-Access Edge Computing", IEEE Trans. Network Science and Engineering (TNSE), vol. 7, no. 4, pp. 2901-2912, Oct 2020. [LINK] 2. Zhi Chen, Lingxiang Li, Marie Siew, and Tony Q. S. Quek. Edge/Fog Computing Networks. In Wiley 5G Ref, 2020. [LINK] 1. Lingxiang Li, Marie Siew, and Tony Q. S. Quek, “Learning-Based Pricing for Privacy-Preserving Job Offloading in Mobile Edge Computing,” in Proc. IEEE International Conference on Accoustics, Speech and Signal Processing (ICASSP), Brighton, UK, May 2019. [LINK] |
