Jian Li
Professor
Works on approximation algorithms and stochastic optimization and on machine learning for tabular, time-series, and spatio-temporal data and finance.
Jian Li's lab at Tsinghua works on learning theory & optimization. 30 papers since 2023, 27 at top venues, mostly AAAI and IJCAI. 4 PhD students and 3 master's students. 30 alumni. Applications close .
At a glance
- papers, 2023–2026
- 8/ year
- at T1 venues
- 90%
- PhD students
- 4
- MS students
- 3
- alumni listed
- 30
Papers by yearfrom the lab homepage, 2023–2026
- 3 papers2026 · T1 3 · collecting
- 8 papers2025 · T1 6
- 6 papers2024 · T1 6
- 13 papers2023 · T1 12
T1 venuesOtherVenues: AAAI, IJCAI, ICLR, NeurIPS, ICML
Research focuspaper titles that use each topic's words
- Learning theory & optimization9 papers
- time-series1 paper
- stochastic optimization0 papers
- spatio-temporal data0 papers
- finance0 papers
Paper list
From the lab homepage.
20263 papers
- ICML (T1)AdaRoPE: Not All Attention Heads Should Rotate and Scale Equally
- AAAI (T1)Kronos: A Foundation Model for the Language of Financial Markets
- AAAI (T1)Navigating the Alpha Jungle: an LLM-Powered MCTS Framework for Formulaic Factor Mining
20258 papers
- FOCS (T1)Adaptivity Gaps for Stochastic Probing with Subadditive Functions
- SODA (T1)Coresets for clustering with general assignment constraints
- AAAI (T1)FactorGCL: A Hypergraph-Based Factor Model with Temporal Residual Contrastive Learning for Stock Returns Prediction
- ICLR (T1)Feature Averaging: An Implicit Bias of Gradient Descent Leading to Non-Robustness in Neural Networks
- ICALPNew Results on a General Class of Minimum Norm Optimization Problems
- SDMOpenFE++: Efficient Automated Feature Generation via Feature Interaction
- ICLR (T1)Rethinking Diffusion Posterior Sampling: From Conditional Score Estimator to Maximizing a Posterior
- NeurIPS (T1)Understanding LLM Behaviors via Compression: Data Generation, Knowledge Acquisition and Scaling Laws
20246 papers
- SIGMOD (T1)FeatureLTE: Learning to Estimate Feature Importance
- IJCAI (T1)IMM: An Imitative Reinforcement Learning Approach with Predictive Representation Learning for Automatic Market Making Hui Niu, Siyuan Li, Jiahao Zheng, Zhouchi Lin, Jian Li, Jian Guo, Bo An
- NeurIPS (T1)LoRA-GA: Low-Rank Adaptation with Gradient Approximation
- IJCAI (T1)MacMic: Executing Iceberg Orders via Hierarchical Reinforcement Learning Hui Niu, Siyuan Li, Jian Li
- STOC (T1)On Optimal Coreset Construction for (k,z)-Clustering
- IJCAI (T1)Trade When Opportunity Comes: Price Movement Forecasting via Locality-Aware Attention and Iterative Refinement Labeling
202313 papers
- AAAI (T1)AEC-GAN: Adversarial Error Correction GANs for Auto-Regressive Long Time-series Generation
- COLT (T1)Efficient Algorithms for Sparse Moment Problems without Separation
- SODA (T1)Generalized Unrelated Machine Scheduling Problem
- EMNLP (T1)Generative Table Pre-training Empowers Models for Tabular Prediction
- NeurIPS (T1)GLIME: General, Stable and Local LIME Explanation
- AAAI (T1)ImGCL: Revisiting Graph Contrastive Learning on Imbalanced Node Classification
- —Latent Consistency Models: Synthesizing High-Resolution Images with Few-step Inference
- CIKM (T1)MetaTrader: An reinforcement learning approach integrating diverse policies for portfolio optimization
- ICLR (T1)Not All Tasks Are Born Equal: Understanding Zero-Shot Generalization
- ICML (T1)OpenFE: Automated Feature Generation with Expert-level Performance
- AAAI (T1)Symphony in the Latent Space: Provably Integrating High-dimensional Techniques with Non-linear Machine Learning Models
- IJCAI (T1)Towards Generalizable Reinforcement Learning for Trade Execution
Where alumni went30 listed
Apply to TsinghuaFall 2027
Computer Science PhD (international applicants)
- Round
- Main
- Opens
- GRE
- See program page
- English
- Per school catalog
- Fee
- RMB 800
Not yet confirmed for this intake.
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