
Ph.D. Student @ SNU · Embodied AI · Video-Language · Multi-Agent Reasoning
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Assessing your cultural and operational fit
isr-dpo
June 17, 2024 – November 25, 2025
Official Implementation of ISR-DPO:Aligning Large Multimodal Models for Videos by Iterative Self-Retrospective DPO (AAAI'25)
View Projectvlm-rlaif
February 5, 2024 – September 12, 2024
ACL'24 (Oral) Tuning Large Multimodal Models for Videos using Reinforcement Learning from AI Feedback
View Projectsdp
March 2, 2023 – September 13, 2024
Official Implementation of SDP (Scheduled Data Prior) (ICLR 2023)
View Projectmcr-agent
November 27, 2022 – September 12, 2024
Official Implementation of MCR-Agent (Multi-Level Compositional Reasoning Agent) (AAAI'23)
View ProjectCultural Fit Analysis
The candidate's project portfolio is heavily skewed towards academic research and personal projects in advanced AI/ML domains, specifically large multimodal models and reinforcement learning. This indicates a strong fit for a research-heavy or innovation-focused data science role. The diversity of projects within this niche is good, but there is no evidence of experience in traditional business intelligence, data engineering, or broader data science applications, which might limit fit for roles requiring a wider range of industry experience. The lack of team-based or professional experience makes it difficult to assess collaboration and broader cultural fit.
Soft Skills & Operational Fit
The candidate's project history, particularly involvement in academic research and official implementations, suggests a strong drive for problem-solving and a research-oriented mindset. However, without specific psychometric or English test results, it is difficult to assess communication, teamwork, or stress handling abilities. The candidate's focus on personal projects indicates self-motivation.