Subin Kim

Cornell PoRTaLIthaca, NY, U.S.

Research Intern(remote) Sep. 2024 - Feb. 2025, (onsite) Feb. 2025 - May. 2025

Advisor: Sanjiban Choudhury, Arnav Kumar Jain, Gokul Swamy

Hybrid training of Offline diffusion policy & online MBRL (NeurIPS 2025 Spotlight)

• Investigate how the different image representation effects diffusion policy and world models.
• Investigate how offline training with expert data can enhance the online learning through world models.
• Implement MPPI planner (referred from TD-MPC) with n-step TD reward using the trained reward function and critic of the world model.
• Skill: Pytorch, Docker, Singularity

KAIST MLMLabDaejeon, Republic of Korea

M.S.Mar. 2023 - Feb. 2025 (expected)

Advisor: Sungjin Ahn

Divide-and-conquer strategy for goal-conditioned MBRL agent (ICML 2024)

• Proposed the concept of “strategic dreaming” in pixel-based MBRL, where the agent can leverage the structure of the state space to enable a divide-and-conquer-like strategy.
• Improved prior methods in visually complex and partially observable navigation tasks.
• Published “Dr. Strategy: Model-Based Generalist Agents with Strategic Dreaming (ICML 2024)” as first co-author.
• Skill: Pytorch, Docker, Mujoco

KAIST DS Lab Daejeon, Republic of Korea

Research InternJuly. 2022 - Jan. 2023

Advisor: Sundong Kim, Meeyoung Cha

• Built Mini-ARC that extends the original ARC dataset with restricted size.
• Built O2ARC, which is an object-oriented web interface to solve & suggest Mini-ARC.
• Hosted Happy ARC Day including over 40 participants to create and peer review Mini-ARC.
• Published "Playgrounds for Abstraction and Reasoning" in nCSI WS @ NeurIPS 2022.
• Published "Test Bed for Abstraction and Reasoning (Short version)" & Received Best Paper Award in KSC 2022.
• Gave a poster presentation in nCSI WS @ NeurIPS & KSC 2022.
• Skill: HTML, CSS, Javascript, Python, Flask, Django, ML

KAIST DM LabSeoul, Republic of Korea

Research InternDec. 2021 - June. 2022

Advisor: Kijung Shin

• Studied topics related to graph neural networks (GNN)
• Lead to the opportunity of starting "Open Dialogue Generation based on knowledge graph"
• Skill: Python, GNN

KAIST PROSYS LabDaejeon, Republic of Korea

Research InternJune. 2021 - Sep. 2021

Advisor: Kihong Heo

"Tracer: Signature-based Static Analysis for Detecting Recurring Vulnerabilities"(Submitted to ICSE 2022)

• 'Tracer' detects software vulnerabilities by exploiting existing vulnerability patterns.
• Participated as a second author, implementing ML baselines and hunting bugs to use for training data.
• Poster presentation for KAIST PL seminar (Host: Sukyoung Ryu)
• This project was accepted to CCS 2022. However, I did not participate in the later process.
• Skill: Python, C, C++, Pytorch, PL, ML

KAIST CDSN LabDaejeon, Republic of Korea

Research InternJan. 2021 - June. 2021

Advisor: Sumin Han, Dongman Lee

• Participated in predicting traffic flow through spatio-temporal neural networks.
• Submitted "Spatio-Temporal Attention based Conditional Traffic Flow Prediction in Urban Areas" to ECML-PKDD 2021
• Publishd "Analysis of impact on Seoul traffic congestion by Land Use using travel speed and POI" in KSC 2021
• Skill: Python, Pytorch, Pandas, spatio-temporal prediction