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ETH Zurich
Data Scientist
June 25, 2026 – Present
Optimal-Bond-Percolation-in-Networks-by-a-Fast-Decycling-Framework
August 1, 2023 – August 1, 2023
2023 Optimal Bond Percolation in Networks by a Fast-Decycling Framework
View ProjectInformationPopularityPrediction
March 12, 2023 – June 19, 2023
Data and code of the draft: The Minimum Knowledge to Predict the Popularity of Information on Social Networks
View Project2019-Ensemble-approach-for-generalized-network-dismantling
April 9, 2020 – April 9, 2020
2019-Ensemble-approach-for-generalized-network-dismantling — GitHub repository
View ProjectPresentation-Poster-and-Paper
November 6, 2019 – November 6, 2019
The slides of the presentation, poster, and paper
View Project2016-Vital-nodes-identification-in-complex-networks
October 31, 2018 – October 31, 2018
Data of the paper: Lü, Linyuan, Duanbing Chen, Xiao-Long Ren, Qian-Ming Zhang, Yi-Cheng Zhang, and Tao Zhou. "Vital nodes identification in complex networks." Physics Reports 650 (2016): 1-63.
View Project2014-Avoiding-congestion-in-recommender-systems
October 28, 2018 – July 17, 2019
Code and data-sets of the paper "Avoiding congestion in recommender systems."
View Project2018-Underestimated-cost-of-targeted-attacks-on-complex-networks
October 28, 2018 – November 6, 2019
Code and data-sets of Ren, Xiao-Long, Niels Gleinig, Dijana Tolić, and Nino Antulov-Fantulin. "Underestimated cost of targeted attacks on complex networks." Complexity 2018 (2018). https://doi.org/10.1155/2018/9826243
View ProjectGeneralized-Network-Dismantling
October 28, 2018 – June 14, 2023
GND and GNDR network dismantling algorithm
View ProjectCultural Fit Analysis
The candidate's projects are heavily research-oriented, focusing on complex network analysis and theoretical data science problems. While this demonstrates strong analytical capabilities, the diversity of project types and technologies is limited, primarily revolving around C++ and Matlab for academic research. The alignment with a typical industry Data Scientist role might require further assessment of practical application skills beyond academic research. The single listed professional experience as 'Data Scientist' at ETH Zurich, with an 'experienceLevel' of 0, makes it difficult to fully assess cultural fit for a standard industry role.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's experience level is listed as 0, but they have a current role as a Data Scientist at ETH Zurich, which is contradictory. No psychometric test results are available.