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Master's Student @ KAIST AI
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Arguinas
April 16, 2026 – Present
Official Implementation of "Argument Reconstruction as Supervision for Critical Thinking in LLMs"
View Projectclover
February 19, 2025 – May 12, 2025
Official code for "Divide and Translate: Compositional First-Order Logic Translation and Verification for Complex Logical Reasoning", ICLR 2025.
View Projectargdown-feedback
February 9, 2025 – December 3, 2025
Hindsight Instruction Relabeling Preferences
View Projectsimpsi
June 16, 2023 – January 22, 2025
Official code for "SimPSI: A Simple Strategy to Preserve Spectral Information in Time Series Data Augmentation", AAAI 2024.
View Projectemc2net
October 6, 2022 – May 30, 2023
Official code for "EMC2-Net: Joint Equalization and Modulation Classification based on Constellation Network", ICASSP 2023.
View ProjectCultural Fit Analysis
The candidate's projects are heavily research-focused and academic, primarily in machine learning, signal processing, and NLP. While these skills are relevant to a Data Scientist role, the lack of diverse project types (e.g., industry applications, product development, team-based projects) suggests a potential gap in experience with typical corporate data science environments. The candidate's experience level is listed as 0, which contradicts the advanced nature of their projects and publications, indicating a potential mismatch in self-assessment or a focus on academic rather than industry experience. This could impact cultural fit within a fast-paced, product-driven data science team.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions indicate a strong focus on research and technical implementation.