Fuqi Jia   (贾富琦) State Key Laboratory of Computer Science Institute of Software, Chinese Academy of Sciences #4 South Fourth St., Zhong Guan Cun Beijing, China 100190 Email: jiafq@ios.ac.cn [Google Scholar] [DBLP] [GitHub]

Short Bio

I am currently a PhD student in Computer Science and Technology at the University of Chinese Academy of Sciences (UCAS) and doing my research at State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, under the supervision of Prof. Jian Zhang. From 2024 to 2025, I servied as a visiting PhD student at Stanford University, supervised by Clark Barrett. Before that, I received my B.S. degree in Computer Science and Technology from Jilin University (JLU) in 2020.

My research interests include the theory, algorithm and application of automated reasoning, constraint solving and optimization, as well as the integration of symbolic reasoning and machine learning.

Education

Recent News

• [2024.07] One full paper is accepted by SAIV 2024.
• [2023.11] One full paper is accepted by PRICAI 2023.
• [2023.09] One full paper is accepted by NeurIPS 2023.
• [2023.07] Our paper received the ACM SIGSOFT Distinguished Paper Award at ISSTA 2023.

Publications

(* indicates equal contribution)

• Parallel Verification for δ-Equivalence of Neural Network Quantization
  Pei Huang, Yuting Yang, Haoze Wu, Ieva Daukantas, Min Wu, Fuqi Jia, Clark Barrett
  International Symposium on AI Verification (SAIV), 2024
  
• Investigating the Existence of Holey Latin Squares via Satisfiability Testing
  Minghao Liu, Rui Han, Fuqi Jia, Pei Huang, Feifei Ma, Hantao Zhang, Jian Zhang
  Pacific Rim International Conference on Artificial Intelligence (PRICAI), 2023
  
• Suggesting Variable Order for Cylindrical Algebraic Decomposition via Reinforcement Learning
  Fuqi Jia*, Yuhang Dong*, Minghao Liu, Pei Huang, Feifei Ma, Jian Zhang
  Conference on Neural Information Processing Systems (NeurIPS), 2023
  
• Improving Bit-Blasting for Nonlinear Integer Constraints
  Fuqi Jia, Rui Han, Pei Huang, Minghao Liu, Feifei Ma, Jian Zhang
  ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA), 2023
  🏅 ACM SIGSOFT Distinguished Paper Award
  
• PSMT: Satisfiability Modulo Theories Meets Probability Distribution
  Fuqi Jia*, Rui Han*, Xutong Ma, Baoquan Cui, Minghao Liu, Pei Huang, Feifei Ma, Jian Zhang
  IEEE/ACM International Conference on Automated Software Engineering (ASE, NIER Track), 2023
  
• NRAgo: Solving SMT(NRA) Formulas with Gradient-based Optimization
  Minghao Liu*, Kunhang Lv*, Pei Huang, Rui Han, Fuqi Jia, Yu Zhang, Feifei Ma, Jian Zhang
  IEEE/ACM International Conference on Automated Software Engineering (ASE, Tool Demo Track), 2023
  
• Can Graph Neural Networks Learn to Solve the MaxSAT Problem?
  Minghao Liu, Pei Huang, Fuqi Jia, Fan Zhang, Yuchen Sun, Shaowei Cai, Feifei Ma, Jian Zhang
  AAAI Conference on Artificial Intelligence (AAAI), Student Abstract and Poster Program, 2023
  🏅 Best Student Abstract Honorable Mention Award
  
• ε-weakened Robustness of Deep Neural Networks
  Pei Huang*, Yuting Yang*, Minghao Liu, Fuqi Jia, Feifei Ma, Jian Zhang
  ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA), 2022
  
• Word Level Robustness Enhancement: Fight Perturbation with Perturbation
  Pei Huang*, Yuting Yang*, Fuqi Jia, Minghao Liu, FeiFei Ma, Jian Zhang
  AAAI Conference on Artificial Intelligence (AAAI), 2022
  

Selected Awards & Scholarships

• Outstanding Doctoral Student, Chinasoft 2023, 2023.11.
• National Scholarship of China, 2023.10.
• First Prize Scholarship of UCAS, 2023.10.
• SMT Competition, QF_NIA Single Query / Model Validation Track, 2nd Place (Main Author), 2023.08.
• ACM SIGSOFT Distinguished Paper Award, ISSTA 2023, 2023.07.

Presentations

• Conference Talk Improving Bit-Blasting for Nonlinear Integer Constraints, ISSTA 2023, Virtual Event.
• Conference Talk PSMT: Satisfiability Modulo Theories Meets Probability Distribution, ASE 2023, Luxembourg.
• Conference Talk NRAgo: Solving SMT(NRA) Formulas with Gradient-based Optimization, ASE 2023, Luxembourg.
• Seminar Talk Satisfiability and Deep Learning, Applied Mathematics Seminar for Youth, Peking University, Beijing, China.
• Seminar Talk Solving Reasoning Problems with Neuro-Symbolic Methods, Dagstuhl Seminar 23471, Dagstuhl, Germany.
• Seminar Talk Improving SMT Solving via Incorporating More Techniques, Dagstuhl Seminar 23471, Dagstuhl, Germany.
• Conference Talk A Theory-Agnostic SMT Sampling Framework (Poster), FMCAD 2024, Prague, Czech Republic.