Scholar
Jun Wang
Google Scholar ID: BgPTZ4MAAAAJ
PhD Candidate, Washington University in St. Louis
Citations & Impact
Citations
124
H-index
5
i10-index
3
Publications
10
Co-authors
0
Publications
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- - CoFineLLM: Conformal Finetuning of Large Language Models for Language-Instructed Robot Planning
- - Conformal Temporal Logic Planning using Large Language Models
- - ConformalNL2LTL: Translating Natural Language Instructions into Temporal Logic Formulas with Conformal Correctness Guarantees
- - Plug-and-Play Physics-informed Learning using Uncertainty Quantified Port-Hamiltonian Models
- - Mission-driven Exploration for Accelerated Deep Reinforcement Learning with Temporal Logic Task Specifications
- - Probabilistically Correct Language-based Multi-Robot Planning using Conformal Prediction
- - Sample-Efficient Reinforcement Learning with Temporal Logic Objectives: Leveraging the Task Specification to Guide Exploration
- - Safeguarded Progress in Reinforcement Learning: Safe Bayesian Exploration for Control Policy Synthesis
Research Experience
- - Spent 9 months as a research intern at Schlumberger prior to doctoral studies.
Education
- - Ph.D. candidate in Electrical Engineering at Washington University in St. Louis, advised by Prof. Yiannis Kantaros, currently an MLE intern at EvenUp for Fall 2025.
- - MSE in Robotics from the GRASP Lab at the University of Pennsylvania, advised by Prof. George Pappas, 2021.
- - BEng in Software Engineering from Sun Yat-Sen University, 2019.
Background
- Research interests include developing safe and scalable multi-robot systems by combining formal methods, conformal prediction, large language models (LLMs), and reinforcement learning (RL). Particularly interested in: Language-based task planning with LLMs and VLMs, uncertainty-aware planning via conformal prediction, temporal-logic-guided reinforcement learning, and safe and efficient multi-robot coordination.
Co-authors