Dimensionality reduction via community detection in small sample datasets Bhardwaj, Kartikeya; Marculescu, Radu Pacific-Asia Conference on Knowledge Discovery and Data Mining, pp. 102–114, Springer, Cham 2018. Links@inproceedings{bhardwaj2018dimensionality,
title = {Dimensionality reduction via community detection in small sample datasets},
author = {Kartikeya Bhardwaj and Radu Marculescu},
url = {https://link.springer.com/chapter/10.1007/978-3-319-93040-4_9},
year = {2018},
date = {2018-01-01},
booktitle = {Pacific-Asia Conference on Knowledge Discovery and Data Mining},
pages = {102--114},
organization = {Springer, Cham},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Weighted betweenness preferential attachment: A new mechanism explaining social network formation and evolution Topirceanu, Alexandru; Udrescu, Mihai; Marculescu, Radu Scientific reports, 8 (1), pp. 1–14, 2018. Links@article{topirceanu2018weighted,
title = {Weighted betweenness preferential attachment: A new mechanism explaining social network formation and evolution},
author = {Alexandru Topirceanu and Mihai Udrescu and Radu Marculescu},
url = {https://www.nature.com/articles/s41598-018-29224-w},
year = {2018},
date = {2018-01-01},
journal = {Scientific reports},
volume = {8},
number = {1},
pages = {1--14},
publisher = {Nature Publishing Group},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
PGLasso: Microbial Community Detection through Phylogenetic Graphical Lasso Lo, Chieh; Marculescu, Radu arXiv preprint arXiv:1807.08039, 2018. Links@article{lo2018pglasso,
title = {PGLasso: Microbial Community Detection through Phylogenetic Graphical Lasso},
author = {Chieh Lo and Radu Marculescu},
url = {https://arxiv.org/abs/1807.08039},
year = {2018},
date = {2018-01-01},
journal = {arXiv preprint arXiv:1807.08039},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Computational Approaches for Incorporating Short-and Long-Term Dynamics in Smart Water Networks Bhardwaj, Kartikeya; Stamoulis, Dimitrios; Ding, Ruizhou; Marculescu, Diana; Marculescu, Radu Smart Water Grids, pp. 297–323, CRC Press, 2018. Links@incollection{bhardwaj2018computational,
title = {Computational Approaches for Incorporating Short-and Long-Term Dynamics in Smart Water Networks},
author = {Kartikeya Bhardwaj and Dimitrios Stamoulis and Ruizhou Ding and Diana Marculescu and Radu Marculescu},
url = {https://www.researchgate.net/publication/331756641_Computational_Approaches_for_Incorporating_Short-_and_Long-Term_Dynamics_in_Smart_Water_Networks},
year = {2018},
date = {2018-01-01},
booktitle = {Smart Water Grids},
pages = {297--323},
publisher = {CRC Press},
keywords = {},
pubstate = {published},
tppubtype = {incollection}
}
|
Modeling computational, sensing, and actuation surfaces Stanley-Marbell, Phillip; Marculescu, Diana; Marculescu, Radu; Khosla, Pradeep K Low-Power Processors and Systems on Chips, pp. 16–1, 2018. Links@article{stanley2018modeling,
title = {Modeling computational, sensing, and actuation surfaces},
author = {Phillip Stanley-Marbell and Diana Marculescu and Radu Marculescu and Pradeep K Khosla},
url = {https://www.researchgate.net/publication/329321383_Modeling_Computational_Sensing_and_Actuation_Surfaces},
year = {2018},
date = {2018-01-01},
journal = {Low-Power Processors and Systems on Chips},
pages = {16--1},
publisher = {CRC Press},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
A Dynamic Network and Representation LearningApproach for Quantifying Economic Growth fromSatellite Imagery Dong, Jiqian; Atulya, Gopaljee; Bhardwaj, Kartikeya; Marculescu, Radu arXiv preprint arXiv:1812.00141, 2018. Links@article{dong2018dynamic,
title = {A Dynamic Network and Representation LearningApproach for Quantifying Economic Growth fromSatellite Imagery},
author = {Jiqian Dong and Gopaljee Atulya and Kartikeya Bhardwaj and Radu Marculescu},
url = {https://arxiv.org/abs/1812.00141},
year = {2018},
date = {2018-01-01},
journal = {arXiv preprint arXiv:1812.00141},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
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.