Scholar
Chuanbo Hua
Google Scholar ID: fjKA5gYAAAAJ
Postdoctoral Researcher @ KAIST
Citations & Impact
Citations
383
H-index
9
i10-index
8
Publications
20
Co-authors
31
list available
Contact
Publications
Resume (English only)
Academic Achievements
- - Paper "PARCO: Learning Parallel Autoregressive Policies for Efficient Multi-agent Combinatorial Optimization" accepted at NeurIPS 2025 (Poster).
- - Paper "RRNCO: Neural Combinatorial Optimization for Real-world Routing" accepted at NeurIPS 2025 Workshop (Poster).
- - Paper "PILLM: Physics-Informed Large Language Models for HVAC Anomaly Detection with Autonomous Rule Generation" accepted at NeurIPS 2025 Workshop (Oral).
- - Paper "Routefinder: Towards Foundation Models for Vehicle Routing Problems" accepted at TMLR.
- - Paper "RL4CO: an Extensive Reinforcement Learning for Combinatorial Optimization Benchmark." accepted at KDD Dataset & Benchmark Track (Oral).
- - Paper "TrajEvo: Designing Trajectory Prediction Heuristics via LLM-driven Evolution" accepted at ICML 2025 Workshop (Poster).
- - Paper "BuildEvo: Designing Building Energy Consumption Forecasting Heuristics via LLM-driven Evolution" accepted at ICML 2025 Workshop (Poster).
- - Paper "CAMP: Collaborative Attention Model with Profiles for Vehicle Routing Problems" accepted at AAMAS 2025 (Oral).
- - Paper "Accelerating Chiplet Placement & Routing Optimization with Machine Learning" accepted at DesignCon 2025 (Best Paper).
- - Paper "AoP-SAM: Automation of Prompts for Efficient Segmentation" accepted at AAAI 2025 (Poster).
- - Paper "Deep learning-based coagulant dosage prediction for extreme events leveraging large-scale data" accepted at JWPE (IF: 7).
- - Paper "RouteFinder: Towards Foundation Models for Vehicle Routing Problems" accepted at ICML 2024 Workshop (Oral).
- - Paper "HiMAP: Learning Heuristics-Informed Policies for Large-Scale Multi-Agent Pathfinding" accepted at AAMAS 2024 (Poster).
Research Experience
- - Postdoctoral fellow in the InnoCore PRISM-AI project (since September 2025)
- - Conducts research at the Systems Intelligence Laboratory (SILab) at KAIST
Education
- Information not provided
Background
- - Research interests: reinforcement learning, combination optimization, LLM for algorithm design.
- - Postdoctoral fellow at Korea Advanced Institute of Science & Technology (KAIST), supervised by Prof. Jinkyoo Park.
- - Co-founder of the AI4CO open source group and works closely with the DiffEqML open source group.
- - Primary research focus is the development of reinforcement learning (RL) algorithms for combinatorial optimization (CO) problems and created the RL4CO open-source benchmark.
Miscellany
- Information not provided
