Tina Eliassi-Rad
(she/her)
Joseph E. Aoun Professor
Research interests
- Data mining
- Machine learning
- Network science
- Ethics and artificial intelligence
Education
- PhD in Computer Science, University of Wisconsin-Madison
- MS in Computer Science, University of Illinois at Urbana-Champaign
- BS in Computer Science, University of Wisconsin-Madison
Biography
Tina Eliassi-Rad is the inaugural Joseph E. Aoun Professor at Northeastern University, based in Boston. She is also a core faculty member at Northeastern's Network Science Institute and the Institute for Experiential AI, as well as an external faculty member at the Santa Fe Institute and the Vermont Complex Systems Center.
Eliassi-Rad's research is at the intersection of data mining, machine learning, and network science. She has more than 100 peer-reviewed publications — including a few best paper and best paper runner-up awards — and has given more than 200 invited talks and 14 tutorials. Eliassi-Rad's work has been applied to personalized searches on the World Wide Web, statistical indices of large-scale scientific simulation data, fraud detection, mobile ad targeting, cyber situational awareness, drug discovery, democracy and online discourse, and ethics in machine learning. Her algorithms have been incorporated into systems used by governments and industry (e.g., IBM System G Graph Analytics) as well as open-source software (e.g., Stanford Network Analysis Project).
In 2017, Eliassi-Rad served as the program co-chair for the ACM International Conference on Knowledge Discovery and Data Mining and the International Conference on Network Science. In 2020, she served as the program co-chair for the International Conference on Computational Social Science. Eliassi-Rad received an Outstanding Mentor Award from the US Department of Energy's Office of Science in 2010, became an ISI Foundation Fellow in 2019, was named one of the 100 Brilliant Women in AI Ethics in 2021, received Northeastern University's Excellence in Research and Creative Activity Award in 2022, and was awarded the prestigious Lagrange-CRT Foundation Prize in 2023.
Prior to joining Northeastern, Eliassi-Rad was an associate professor of computer science at Rutgers University, and before that she was a member of technical staff and principal investigator at Lawrence Livermore National Laboratory.
Labs and groups
Recent publications
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Using overlapping methods to counter adversaries in community detection
Citation: Benjamin A. Miller, Kevin S. Chan, Tina Eliassi-Rad. (2024). Using overlapping methods to counter adversaries in community detection J. Complex Networks, 12. https://doi.org/10.1093/comnet/cnae030 -
Complex network effects on the robustness of graph convolutional networks
Citation: Benjamin A. Miller, Kevin S. Chan, Tina Eliassi-Rad. (2024). Complex network effects on the robustness of graph convolutional networks Appl. Netw. Sci., 9, 5. https://doi.org/10.1007/s41109-024-00611-9 -
A Survey on Hypergraph Mining: Patterns, Tools, and Generators
Citation: Geon Lee, Fanchen Bu, Tina Eliassi-Rad, Kijung Shin. (2024). A Survey on Hypergraph Mining: Patterns, Tools, and Generators CoRR, abs/2401.08878. https://doi.org/10.48550/arXiv.2401.08878 -
Using sequences of life-events to predict human lives
Citation: Germans Savcisens, Tina Eliassi-Rad, Lars Kai Hansen, Laust Hvas Mortensen, Lau Lilleholt, Anna Rogers, Ingo Zettler, Sune Lehmann. (2024). Using sequences of life-events to predict human lives Nat. Comput. Sci., 4, 43-56. https://doi.org/10.1038/s43588-023-00573-5 -
Attacking Shortest Paths by Cutting Edges
Citation: Benjamin A. Miller, Zohair Shafi, Wheeler Ruml, Yevgeniy Vorobeychik, Tina Eliassi-Rad, Scott Alfeld. (2024). Attacking Shortest Paths by Cutting Edges ACM Trans. Knowl. Discov. Data, 18, 35:1-35:42. https://doi.org/10.1145/3622941 -
TenGAN: adversarially generating multiplex tensor graphs
Citation: William Shiao, Benjamin A. Miller, Kevin Chan , Paul L. Yu, Tina Eliassi-Rad, Evangelos E. Papalexakis. (2024). TenGAN: adversarially generating multiplex tensor graphs Data Min. Knowl. Discov., 38, 1-21. https://doi.org/10.1007/s10618-023-00947-3 -
Modeling self-propagating malware with epidemiological models
Citation: Alesia Chernikova, Nicolò Gozzi, Nicola Perra, Simona Boboila, Tina Eliassi-Rad, Alina Oprea. (2023). Modeling self-propagating malware with epidemiological models Appl. Netw. Sci., 8, 52. https://doi.org/10.1007/s41109-023-00578-z -
Defense Against Shortest Path Attacks
Citation: Benjamin A. Miller, Zohair Shafi, Wheeler Ruml, Yevgeniy Vorobeychik, Tina Eliassi-Rad, Scott Alfeld. (2023). Defense Against Shortest Path Attacks CoRR, abs/2305.19083. https://doi.org/10.48550/arXiv.2305.19083 -
STABLE: Identifying and Mitigating Instability in Embeddings of the Degenerate Core
Citation: David Liu, Tina Eliassi-Rad. (2023). STABLE: Identifying and Mitigating Instability in Embeddings of the Degenerate Core SDM, 406-414. https://doi.org/10.1137/1.9781611977653.ch46 -
PATHATTACK: Attacking Shortest Paths in Complex Networks
Citation: B.A. Miller, Z. Shafi, W. Ruml, Y. Vorobeychik, T. Eliassi-Rad, S. Alfeld. "PATHATTACK: Attacking Shortest Paths in Complex Networks". In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), September 2021.
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Current PhD Students
Previous PhD Students
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Leonardo Torres
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Timothy LaRock