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教育经历工作经历个人简介社会兼职国家自然科学基金委数理学部、信息学部通讯评议人 美国《Mathematical Reviews》评论员 研究方向目前研究方向:基础算法及其应用 招生类别:学术型硕士生、博士生 欢迎有兴趣从事基础研究的本科生、研究生与我联系,共同探讨! 目前指导学生: 2022级---尤文菁 (硕士生), 李鹏阳 (在职硕士生), 倪海峰 (在职硕士生) 2021级---陆嘉 (硕士生), 陈茜 (在职硕士生), 周俊仁 (在职硕士生) 2020级---梅敬宜 (硕士生), 南艺 (硕士生), 林景朗 (在职硕士生), 李想 (在职硕士生), 纪志成 (在职硕士生) 2019级---傅剑铃 (硕博连读生), 徐波 (在职硕士生), 刘舒妮 (在职硕士生), 常昊 (在职硕士生) 2018级---柳靖逍 (在职硕士生), 潘慧 (在职硕士生) 完成指导学生: 2021届---刘珂冰 (本科生, 去向: 公务员) 2020届---厉劲草 (硕士生, 去向: 银行工作), 梅敬宜 (本科生, 优秀学位论文, 去向: 本校读研) 2019届---黄承超 (硕博连读生, 优秀学位论文, 去向: 中科院博士后), 傅剑铃 (本科生, 优秀学位论文, 去向: 本校读研) 2017届---厉劲草 (本科生, 优秀学位论文, 去向: 本校读研) 2016届---吴凯宗 (本科生, 去向: 本校读研) 2015届---王思宁 (本科生, 优秀学位论文, 去向: 德国亚琛工大读研) 2014届---黄唯苇 (本科生, 优秀学位论文, 去向: 微软工作、美国卡内基梅隆大学读研), 黄承超 (本科生, 去向: 本校读研) 开授课程科研项目主持在研国家自然科学基金面上项目《量子马尔可夫模型上的符号验证方法及其扩展研究》2023.01--2026.12; 主持完成国家自然科学基金面上项目《实时环境下概率程序的符号验证方法及其参数化扩展》2019.01--2022.12, 国家自然科学青年项目《组合约束求解过程及其在程序验证中的应用》2015.01--2017.12, 教育部博士点基金《符号计算在概率模型检测中的应用研究》2014.01--2016.12, 和中国博士后科学基金各一项。 学术成果[0] J. Fu, C. Huang, Y. Li, J. Mei, M. Xu and L. Zhang (2023): Quantitative Controller Synthesis for Consumption Markov Decision Processes, Information Processing Letters, vol. 180, Article No. 106342. [1] M. Xu, J. Fu, J. Mei and Y. Deng (2022): An Algebraic Method to Fidelity-based Model Checking over Quantum Markov Chains, Theoretical Computer Science, vol. 935: 61-81. [2] M. Xu, J. Fu, J. Mei and Y. Deng (2022): Model Checking QCTL Plus on Quantum Markov Chains, Theoretical Computer Science, vol. 913: 43-72. [3] M. Xu, J. Mei, J. Guan and N. Yu (2021): Model Checking Quantum Continuous-Time Markov Chains, in Proceedings of the 32nd International Conference on Concurrency Theory (CONCUR 2021), LIPIcs, vol. 203, Article No. 13, pp. 1-17, Schloss Dagstuhl. [4] M. Xu, C. Huang and Y. Feng (2021): Measuring the Constrained Reachability in Quantum Markov Chains, Acta Informatica, vol. 58(6): 653-674. [5] Y. Sun, M. Xu and Y. Deng (2021): An Optimal Quantum Error-Correcting Procedure Using Quantifier Elimination, Quantum Information Processing, vol. 20, Article No. 170. [6] M. Xu and Y. Deng (2020): Time-bounded Termination Analysis for Probabilistic Programs with Delays, Information and Computation, vol. 275, Article No. 104634. [7] P. Wang, H. Fu, K. Chatterjee, Y. Deng and M. Xu (2020): Proving Expected Sensitivity of Probabilistic Programs with Randomized Variable-Dependent Termination Time, in Proceedings of the ACM on Programming Languages, vol. 4, issue POPL, Article No. 25, pp. 1-30, ACM. [8] C. Huang, M. Xu and Z. Li (2020): A Conflict-Driven Solving Procedure for Poly-Power Constraints, Journal of Automated Reasoning, vol. 64(1), 1-20. [9] C. Huang, J. Li, M. Xu and Z. Li (2018): Positive Root Isolation for Poly-Powers by Exclusion and Differentiation, Journal of Symbolic Computation, vol. 85, 148-169. [10] J. Li, C. Huang, M. Xu and Z. Li (2016): Positive Root Isolation for Poly-Powers, in Proc. 41st ISSAC, pp. 325-332, ACM. [11] M. Xu, L. Zhang, D. N. Jansen, H. Zhu and Z. Yang (2016): Multiphase Until Formulas over Markov Reward Models: An Algebraic Approach, Theoretical Computer Science, vol. 611, 116-135. [12] M. Xu, C. Huang, Z. Li and Z. Zeng (2016): Analyzing Ultimate Positivity for Solvable Systems, Theoretical Computer Science, vol. 609, part 2: 395-412. [13] M. Xu, Z. Li and L. Yang (2015): Quantifier Elimination for a Class of Exponential Polynomial Formulas, Journal of Symbolic Computation, vol. 68, part 1: 146-168. [14] M. Xu and Z. Li (2013): Symbolic Termination Analysis of Solvable Loops, Journal of Symbolic Computation, vol. 50: 28-49. [15] Y. Gao, M. Xu, N. Zhan and L. Zhang (2013): Model Checking Conditional CSL for Continuous-Time Markov Chains, Information Processing Letters, vol. 113(1-2): 44-50. 荣誉及奖励招生信息 |