QING Jixiang
Hi there! I am a Lecturer (Assistant Professor) at MARS (Mathematics for AI in Real-world Systems) Lancaster University.
I was previously a postdoc at Computational Optimisation Group at Imperial College London, UK. I completed my Ph.D. in SUMO lab at Ghent University, Belgium, and my undergraduate and Master's degrees in Aerospace Engineering at Northwestern Polytechnical University, China.
Research Interests: Machine Learning · Sequential Decision Making · AI4X
2026
Our paper "BoGrape: Bayesian optimization over graphs with shortest-path encoded" has been accepted at ICLR 2026!2025
Our paper "The Catechol Benchmark: Time-series Solvent Selection Data for Few-shot Machine Learning" has been accepted at NeurIPS 2025 (DB Track)!2025
I am honored to be invited to participate in the Dagstuhl Seminar: "Bayesian Optimisation"2025
MARS funded PhD programmes for home students in 2026 are open - check out here for work together opportunities2025
Joined Lancaster University MARS as a Lecturer, October 2025
Teaching:
• 2026 - MATH457 Computational Intensive Methods (MCMC, Particle Filter)
• 2026 - MATH457 Computational Intensive Methods (MCMC, Particle Filter)
Reviewing:
• Conferences: ICML, NeurIPS, ICLR, AISTATS, AAAI, etc.
• Journals: TMLR, MLJ, TEVC, etc.
• Conferences: ICML, NeurIPS, ICLR, AISTATS, AAAI, etc.
• Journals: TMLR, MLJ, TEVC, etc.
2025
"Enable Optimal Acquisition Function Search in Constrained Graph Space"Workshop on Gaussian Processes for Decision Making, Manchester
2024
"Multi-objective Bayesian Optimization"Bayesian Optimization Summer School, Imperial College London, London
2023
"{PF}²ES: Parallel Feasible Pareto Frontier Entropy Search for Multi-Objective Bayesian Optimization Under Unknown Constraints"Computational and Biological Learning Lab (CBL), Cambridge University
2023
"Robust Bayesian optimization under input uncertainty"Workshop on Uncertainty in Machine Learning, Ghent