Kijung Shin
Data ScientistAssociate Professor at KAIST
KAIST Data Mining Lab
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Associate Professor at KAIST
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
KAIST Data Mining Lab
Data Scientist
June 26, 2026 – Present
slugger
December 5, 2021 – December 13, 2021
SLUGGER: Lossless Hierarchical Summarization of Massive Graphs
View Projectthinkd
June 15, 2018 – October 30, 2024
Think before You Discard: Accurate Triangle Counting in Graph Streams with Deletions (ECML/PKDD'18 & TKDD'20)
View Projectwaiting_room
September 5, 2017 – October 30, 2024
WRS: Waiting Room Sampling for Accurate Triangle Counting in Real Graph Streams (ICDM'17 & VLDBJ'20)
View Projectdensealert
May 19, 2017 – October 30, 2024
DenseAlert: Incremental Dense-SubTensor Detection in Tensor Streams (KDD'17)
View Projectdcube
November 21, 2016 – October 30, 2024
D-Cube: Dense-Block Detection in Terabyte-Scale Tensors (WSDM'17 & Frontiers in Big Data'21)
View Projectcorescope
September 21, 2016 – October 30, 2024
CoreScope: Graph Mining Using k-Core Analysis - Patterns, Anomalies and Algorithms (ICDM'16 & KAIS'18)
View Projectmzoom
June 27, 2016 – October 30, 2024
M-Zoom: Fast Dense-Block Detection in Tensors with Quality Guarantees (ECML/PKDD'16 & TKDD'18)
View ProjectCultural Fit Analysis
The candidate's projects are heavily focused on academic research in graph mining and tensor analysis, primarily using Java. While this demonstrates deep technical expertise in a specific domain, the breadth of technologies and project types is limited. The target role is 'Data Scientist', which typically requires a broader set of skills including machine learning frameworks (beyond GNNs), statistical modeling, and experience with diverse data sources and deployment environments. The current profile suggests a strong research background but a potential gap in industry-standard data science tools and practices, which might impact cultural fit in a fast-paced, product-oriented data science team.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. Psychometric test scores are 0, indicating no completed assessment.