Xijun Li
Assistant Professor
Works on data-driven learning-to-optimize methods, including machine learning for combinatorial optimization solvers and EDA.
Xijun Li's lab at SJTU works on learning theory & optimization. 20 papers since 2023, 20 at top venues, mostly ICLR and NeurIPS. 4 PhD students and 7 master's students. 1 alumnus. Applications close .
At a glance
- papers, 2023–2026
- 5/ year
- at T1 venues
- 100%
- PhD students
- 4
- MS students
- 7
- alumni listed
- 1
Papers by yearfrom the lab homepage, 2023–2026
- 2 papers2026 · T1 2 · collecting
- 6 papers2025 · T1 6
- 7 papers2024 · T1 7
- 5 papers2023 · T1 5
T1 venuesOtherVenues: ICLR, NeurIPS, ICML, TPAMI, DAC
Research focuspaper titles that use each topic's words
- Learning theory & optimization9 papers
- combinatorial5 papers
- combinatorial optimization4 papers
- solvers3 papers
- data-driven0 papers
Paper list
From the lab homepage.
20262 papers
20256 papers
- TPAMI (T1)Accelerate Presolve in Large-Scale Linear Programming via Reinforcement Learning (opens in a new tab)
- ICLR (T1)Apollo-MILP: An Alternating Prediction-Correction Neural Solving Framework for Mixed-Integer Linear Programming (opens in a new tab)
- ICLR (T1)Differentiable Integer Linear Programming (opens in a new tab)
- NeurIPS (T1)Dynamic Configuration for Cutting Plane Separators via Reinforcement Learning on Incremental Graph (opens in a new tab)
- NeurIPS (T1)Multimodal Generation Made Efficient with Speculative Diffusion and Speculative Verification (opens in a new tab)
- NeurIPS (T1)STRCMP: Integrating Graph Structural Priors with Language Models for Combinatorial Optimization (opens in a new tab)
20247 papers
- ICML (T1)A Circuit Domain Generalization Framework for Efficient Logic Synthesis in Chip Design (opens in a new tab)
- ICDE (T1)Joint Directory, File and IO Trace Feature Extraction and Feature-based Trace Regeneration for Enterprise Storage Systems (opens in a new tab)
- ICLR (T1)L2P-MIP: Learning to Presolve for Mixed Integer Programming (opens in a new tab)
- TPAMI (T1)Learning to Cut via Hierarchical Sequence/Set Model for Efficient Mixed-Integer Programming (opens in a new tab)
- NeurIPS (T1)MILP-StuDio: MILP Instance Generation via Block Structure Decomposition (opens in a new tab)
- ICLR (T1)Rethinking Branching on Exact Combinatorial Optimization Solver: The First Deep Symbolic Discovery Framework (opens in a new tab)
- ICML (T1)Towards General Algorithm Discovery for Combinatorial Optimization: Learning Symbolic Branching Policy from Bipartite Graph (opens in a new tab)
20235 papers
- NeurIPS (T1)A Deep Instance Generative Framework for MILP Solvers Under Limited Data Availability (opens in a new tab)
- KDD (T1)HardSATGEN: Understanding the Difficulty of Hard SAT Formula Generation and A Strong Structure-Hardness-Aware Baseline (opens in a new tab)
- DAC (T1)Layout Decomposition via Boolean Satisfiability (opens in a new tab)
- ICLR (T1)Learning Cut Selection for Mixed-Integer Linear Programming via Hierarchical Sequence Model (opens in a new tab)
- ICLR (T1)ROCO: A General Framework for Evaluating Robustness of Combinatorial Optimization Solvers on Graphs (opens in a new tab)
Where alumni went1 listed
Apply to SJTUFall 2027
Computer Science PhD (international applicants)
- Round
- Self-funded
- Opens
- —
- GRE
- See program page
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
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Data
Checked against the lab homepage.
- Collected
- Verified
- Papers
- The lab homepage
- Members
- Lab homepage
- Alumni
- Lab homepage
Tiers are venue classifications, not lab rankings.
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