Jiong Yang

Portrait

I am a PhD student at School of Computing, National University of Singapore advised by Kuldeep S. Meel.

My research interests center on SAT solving and model counting, with a particular focus on hashing-based approximate model counting algorithms and SAT solving heterogeneous constraints such as the PB-XOR formula.

I am dedicated to advancing the integration of probabilistic and logical reasoning. To this end, on the one hand, I employ causal reasoning to gain a deeper understanding of how SAT solvers work and leverage machine learning to enhance SAT-solving performance. On the other hand, I utilize SAT solvers and model counters to verify the properties of binarized neural networks.

Before joining Meel Group, I received a BEng in Computer Science from Xi'an Jiaotong University in 2020.

Please find more details in my CV.

     

Publications

Explaining SAT Solving Using Causal Reasoning
Jiong Yang, Arijit Shaw, Teodora Baluta, Mate Soos, and Kuldeep S. Meel.
International Conference on Theory and Applications of Satisfiability Testing (SAT 2023)

Rounding Meets Approximate Model Counting
Jiong Yang and Kuldeep S. Meel.
International Conference on Computer Aided Verification (CAV 2023)
Distinguished Paper Award

Projected Model Counting: Beyond Independent Support
Jiong Yang, Supratik Chakraborty, and Kuldeep S. Meel.
International Symposium on Automated Technology for Verification and Analysis (ATVA 2022)

Engineering an Efficient PB-XOR Solver
Jiong Yang and Kuldeep S. Meel.
International Conference on Principles and Practice of Constraint Programming (CP 2021)

Learning Formatting Style Transfer and Structure Extraction for Spreadsheet Tables with a Hybrid Neural Network Architecture
Haoyu Dong, Jiong Yang, Shi Han, and Dongmei Zhang.
International Conference on Information and Knowledge Management (CIKM 2020)