Hai Xia

I am a PhD student in the Doctoral College Logics for Computer Science at TU Wien (LogiCS@TUWien) that is co-funded by the EC H2020 Marie Skłodowska-Curie COFUND, within the Algorithms and Complexity group under the supervision of Prof. Stefan Szeider. My research interests are satisfiability, heuristic search, algorithm selection, parameterized complexity and evolutionary optimization.

 

Publications

Here is my DBLP entry. (* corresponding author)

Carlos Ansótegui, Vaidyanathan Peruvemba Ramaswamy, Stefan Szeider, Hai Xia*, Uncovering and Verifying Optimal Community Structure in Complex Networks: A MaxSAT Approach, International Conference on Computational Science (ICCS), 2025.

Vaidyanathan Peruvemba Ramaswamy, Stefan Szeider, Hai Xia*, The Power of Collaboration: Learning Large Bayesian Networks at Scale, IEEE International Conference on Tools with Artificial Intelligence (ICTAI), 2024. [oral, supplementary file]

Vaidyanathan Peruvemba Ramaswamy, Stefan Szeider, Hai Xia*, Enhancing MaxSAT-Based Bayesian Network Learning with Real-Time Tuning, AAAI Conference on Artificial Intelligence Workshop on Learnable Optimization (AAAI Workshop on LEANOPT), 2024. [poster]

Hai Xia, Stefan Szeider, SAT-Based Tree Decomposition with Iterative Cascading Policy Selection, AAAI Conference on Artificial Intelligence (AAAI), 2024. [oral, poster, supplementary file]

Hai Xia, Changhe Li*, Qingshan Tan, Sanyou Zeng, Shengxiang Yang, Learning to Search Promising Regions by Space Partitioning for Evolutionary Methods, Swarm and Evolutionary Computation (SWEVO), 2024. [source code, supplementary file]

Hai Xia, Changhe Li*, Sanyou Zeng, Qingshan Tan, Shengxiang Yang, Learning to Search Promising Regions by a Monte-Carlo Tree Model, IEEE Congress on Evolutionary Computation (CEC), 2022. [oral, source code]

Hai Xia, Changhe Li*, Sanyou Zeng, Qingshan Tan, Shengxiang Yang, A Reinforcement-Learning-Based Evolutionary Algorithm using Solution Space Clustering for Multimodal Optimization Problems, IEEE Congress on Evolutionary Computation (CEC), 2021. [oral, source code]

Qingshan Tan, Changhe Li*, Hai Xia, Sanyou Zeng,  Shengxiang Yang, A Novel Scalable Framework for Constructing Dynamic Multi-objective Optimization Problems, IEEE Congress on Evolutionary Computation (CEC), 2021. [oral, source code]

Competitions

2nd Place with Mai Peng and Changhe Li in “Competition on Seeking Multiple Optima in Dynamic Environment” of IEEE WCCI 2022, Jul. 2022