On-chip networks: Two sides of the same coin Marculescu, Radu IEEE Annals of the History of Computing, 27 (4), pp. 80–80, 2010. Links@article{marculescu2010chip,
title = {On-chip networks: Two sides of the same coin},
author = {Radu Marculescu},
url = {https://ieeexplore.ieee.org/abstract/document/5512532},
year = {2010},
date = {2010-01-01},
journal = {IEEE Annals of the History of Computing},
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The Chip Is the Network Marculescu, Radu; Bogdan, Paul 2008. Links@misc{marculescu2008chip,
title = {The Chip Is the Network},
author = {Radu Marculescu and Paul Bogdan},
url = {https://books.google.com/books?hl=en&lr=&id=QOwgfSCHxvcC&oi=fnd&pg=PA1&dq=The+Chip+Is+the+Network&ots=H4u_M4a7Dw&sig=noPNk8FTppHJf40jRJd_7zwniDg#v=onepage&q=The%20Chip%20Is%20the%20Network&f=false},
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Fresh air: the emerging landscape of design for networked embedded systems Marculescu, Radu; Nikolic, Borivoje; Sangiovanni-Vincentelli, Alberto Proceedings of the 5th IEEE/ACM international conference on Hardware/software codesign and system synthesis, pp. 124–124, 2007. Links@inproceedings{marculescu2007fresh,
title = {Fresh air: the emerging landscape of design for networked embedded systems},
author = {Radu Marculescu and Borivoje Nikolic and Alberto Sangiovanni-Vincentelli},
url = {https://ieeexplore.ieee.org/document/5753825},
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booktitle = {Proceedings of the 5th IEEE/ACM international conference on Hardware/software codesign and system synthesis},
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Is “Network” the Next “Big Idea” in Design? Marculescu, Radu; Rabaey, Jan; Sangiovanni-Vincentelli, Alberto Proceedings of the Design Automation & Test in Europe Conference, pp. 1–3, IEEE 2006. Links@inproceedings{marculescu2006network,
title = {Is “Network” the Next “Big Idea” in Design?},
author = {Radu Marculescu and Jan Rabaey and Alberto Sangiovanni-Vincentelli},
url = {https://ieeexplore.ieee.org/abstract/document/1656885?casa_token=1rrdgtTD4F4AAAAA:eDvYafmkTVAH8Zpg4EV1U9Ew2PYF9c0U5_K78xFmyIW30L0P3MHJm9BPtxMdsN6cX3elmyjhrA},
year = {2006},
date = {2006-01-01},
booktitle = {Proceedings of the Design Automation & Test in Europe Conference},
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Communication and task scheduling of application-specific networks-on-chip Hu, Jingcao; Marculescu, Radu IEE Proceedings-Computers and Digital Techniques, 152 (5), pp. 643–651, 2005. Links@article{hu2005communication,
title = {Communication and task scheduling of application-specific networks-on-chip},
author = {Jingcao Hu and Radu Marculescu},
url = {https://ieeexplore.ieee.org/document/1532086},
year = {2005},
date = {2005-01-01},
journal = {IEE Proceedings-Computers and Digital Techniques},
volume = {152},
number = {5},
pages = {643--651},
publisher = {IET Digital Library},
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Adaptive data partitioning for ambient multimedia Hu, Xiaoping; Marculescu, Radu Proceedings of the 41st annual Design Automation Conference, pp. 562–565, 2004. Links@inproceedings{hu2004adaptive,
title = {Adaptive data partitioning for ambient multimedia},
author = {Xiaoping Hu and Radu Marculescu},
url = {https://dl.acm.org/doi/10.1145/996566.996721},
year = {2004},
date = {2004-01-01},
booktitle = {Proceedings of the 41st annual Design Automation Conference},
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Epidemics
Viral outbreaks spread throughout networks of people via transmission events. We aim to combine human mobility data, network science, and machine learning to inform and mitigate the disease dynamics for COVID-19. Furthermore, we aim to build an always-on social sensing system to improve a population’s resilience to a novel virus.
Social Networks
Objective social media exhibit rich yet distinct temporal dynamics which cover a wide range of different scales. We are able to identify the compositional structures that can accurately characterize the complex social dynamics from these two social media. We further show that identifying these patterns can enable new applications such as anomaly detection and improved social dynamics forecasting. We aim to uncover new insights on understanding and engineering social media dynamics and their consequences on offline behaviors.
Biological Networks
It is well established that bacteria engage in social behavior and form networked communities via molecular signaling. We analyze the network dynamics and biofilm metrics, showing that our method can effectively reveal the underlying intercellular communication process and community organization within the biofilm. We claim that the application of social and network sciences to understanding bacteria population dynamics can aid in developing better drugs to control the many pathogenic bacteria that use social interactions to cause infections.