Marie Siew
I'm currently a postdoc in the Learning, Incentives and Optimization for Networked Systems (LIONS) Group, in the Electrical and Computer Engineering department, Carnegie Mellon University, advised by Prof Carlee Joe-Wong. I'm working on the areas of resilient and failure-adaptive edge computing systems, and resource allocation in federated learning. My research lies alongst the intersection of networking resource allocation and machine learning.

I obtained my PhD from the Singapore University of Technology and Design in 2021, advised by Prof Tony Quek and Dr Desmond Cai. My thesis was on resource sharing in mobile edge computing, from the perspective of aligning heterogeneous user and device incentives. 
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Prior to that, I obtained my BSc. in Mathematics, from Nanyang Technological University, Singapore in 2016. 
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Email - marie_siew@alumni.sutd.edu.sg
Google Scholar, LinkedIn
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In my free time, I enjoy reading mystery novels, watercolor painting, cooking, exploring new restaurants and places, and watching movies!

Research Interests:
Edge Computing, Federated Learning, Resource Allocation, Reinforcement Learning, Network Economics, Game Theory, Distributed Optimization, Resilient Resource Allocation.

News:
May 2023: I attended CPS-IoT Week at San Antonio! Our work on Fair Multiple-Model Federated Learning received the Best Poster Award at IEEE/ACM IPSN 2023!
Mar 2023:​ I attended IEEE CISS at Baltimore! It was great attending my first in-person conference in a long while.
Jan 2023: Our paper on actor critic reinforcement learning for resilient resource allocation in edge computing has been accepted at IEEE CISS
Jan 2023: Our paper on differentially private Q-learning for MEC offloading has been accepted at IEEE ICC!
Sep 2022: We organized the second ECOFEC: Workshop on the Economics of Fog and Edge Computing workshop, at IEEE SECON 2022. [Workshop link!]


Publications:
Working papers:
1. M. Siew, S. Sharma, K. Guo, C. Xu, T. Q. S. Quek and C. Joe-Wong, "FIRE: A Failure-Adaptive Reinforcement Learning Framework for Edge Computing Migrations," [Preprint link].

2. M. Siew, Y. Hu, S. Sharma, L. Li, and C. Joe-Wong, "Resilience Towards Disruptions in AI-Managed Networks: Challenges, Solutions and Future Directions".

Conference Publications:
6. S. Gan, M. Siew, C. Xu and T. 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. [Preprint Link]

5. M. Siew, S. Arunasalam, Y. Ruan, Z. Zhu, L. Su, S. Ioannidis, E. Yeh, and C. Joe-Wong, "Poster Abstract: 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. Best Poster Award! [Link]

4. M. Siew, S. Sharma, and C. 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]

3. M. Siew, K. Guo, D. Cai, L. Li, and T. 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. [Acceptance rate: 19.9%] [Link],[Preprint LINK]

2. M. Siew, D. Cai, L. Li, and T. 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]

1. L. Li, M. Siew, and T. 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]

Journal Publications:
3. M. Siew, K. Guo, D. Cai, W. Wen, C. Joe-Wong, T.Q.S Quek, "Towards Effective Resource Procurement in MEC: a Resource Re-selling Framework", submitted to IEEE Trans. Services Computing, [Preprint link], under revision. 

2. L. Li, M. Siew, T. Q. S. Quek, and Z. Chen, “Optimal Pricing for Job Offloading in the MEC System with Two Priority Classes,” IEEE Trans. Vehicular Technology, vol. 70, no. 8, pp. 8080-8091, Aug. 2021. [LINK]

1. M. Siew, D. Cai, L. Li, T.Q.S. Quek, "Dynamic Pricing for Resource-Quota Sharing in Multi-Access Edge Computing", IEEE Trans. Network Science and Engineering, vol. 7, no. 4, pp. 2901-2912, Oct 2020. [LINK]

Book Chapters:
1. Chen, Z., Li, L., Siew, M. and Quek, T.Q. (2020). Edge/Fog Computing Networks. In Wiley 5G Ref. [LINK]

Experience:
Oct 2021 - Present: Postdoctoral Researcher, Carnegie Mellon University.
Mar 2021 - Sep 2021: Postdoctoral Researcher, Singapore University of Technology and Design.
Jan 2017- Jan 2021: PhD Candidate. Information Systems Technology and Design, Singapore University of Technology and Design.
Aug 2012 - July 2016: BSc. Mathematical Sciences, Nanyang Technological University.
​Jan - June 2015: Exchange Student, University of Bristol, United Kingdom.
June - Sep 2014: Internship, Future Urban Mobility Group, Singapore - MIT Alliance for Research and Technology (SMART), CREATE Research Institute, Singapore.
June - July 2013: Internship, Data Analytics Department, Institute of Infocom Research (I2R), Singapore.

Services:
Conference/ Workshop Organizing:
​Co-Organizer of The Second ECOFEC: Workshop on the Economics of Fog, Edge and Cloud Computing, held at IEEE SECON, September 2022.  [Workshop link]

TPC Member:
WiOpt (International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks) 2023.
CrossFL Workshop, held at MLSys 2022.
MobiCom 2021 Posters / Student Research Competition.

Reviewer for conferences:
IEEE INFOCOM
IEEE GLOBECOM
IEEE CloudNet
IEEE EdgeCom

Reviewer for journals:
IEEE Journal on Selected Areas in Communications
IEEE Transactions on Mobile Computing
IEEE Transactions on Wireless Communication
IEEE Transactions on Network Science and Engineering
Digital Communication and Networks
IEEE Transactions on Vehicular Technology.

Session Chair:
IEEE Conference on Information Science and Systems (CISS) 2023: Networks III


Teaching/Mentoring Experience
Teaching Assistant for 50.038 Computational Data Science, SUTD (2018)
- Facilitated weekly lab sessions. During the labs, students gain exposure to data pre-processing and management skills, techniques to visualise data, and machine learning and deep learning tools for data analysis. The aim is to equip students such that they can handle their own data science projects in future.

Assistant Mentor for CY1500 Introductory Research Methodology, NTU (2015) 
- The module helped to prepare freshmen for research attachments, through learning about fundamental research principles and scientific writing skills. I helped to facilitate group discussions, give feedback plus critique proposals and weekly assignments, plus shared my experience of research with them. 

Teaching Assistant for MH1401 Algorithms and Computing 1, NTU (2015) 
- I mentored Year 1 Mathematics and Physics students during weekly lab sessions in this introductory course to MATLAB and computing.


Scholarships and Awards
Best Poster Award, IEEE/ACM International Conference on Information Processing in Sensor Networks (IPSN) 2023, held at CPS-IoT Week 2023.
SUTD Presidential Postdoctoral Fellowship (PPF) - under the Singapore Teaching and Academic Research Talent Scheme (START), 2021-Present.
A*Star (Agency for Science, Technology and Research, Singapore) Computing and Information Science Scholarship, 2019-2020.
A*Star Graduate Scholarship, 2017-2019.
Dean’s List – School of Physical and Mathematical Sciences, Nanyang Technological University. Academic Year 2013/2014.
A*Star Chairman’s Honours List, 2014.
NTU President Research Scholar, 2014, for the URECA Programme.        
SMURF: Singapore – MIT Undergraduate Research Fellowship, 2014, for an internship at SMART, CREATE, Singapore.
A*STAR Undergraduate Scholarship, 2012-2016.
NTU CN Yang Scholars’ Programme, 2012-2016. The CN Yang Programme provided an interdisciplinary and research focused curriculum for science and engineering undergraduates in NTU interested in research.