Research

* Equal contributions.

• ψDAG: Projected Stochastic Approximation Iteration for DAG Structure Learning
  Klea Ziu, Slavomír Hanzely, Loka Li, Kun Zhang, Martin Takáč, Dmitry Kamzolov
  arXiv, 2024.
• Gene Regulatory Network Inference in the Presence of Selection Bias and Latent Confounders
  Gongxu Luo, Haoyue Dai, Boyang Sun, Loka Li, Biwei Huang, Petar Stojanov, Kun Zhang
  arXiv, 2024.
• Causal Representation Learning from Multimodal Biological Observations
  Yuewen Sun, Lingjing Kong, Guangyi Chen, Loka Li, Gongxu Luo, Zijian Li, Yixuan Zhang, Yujia Zheng, Mengyue Yang, Petar Stojanov, Eran Segal, Eric Xing, Kun Zhang.
  International Conference on Learning Representations (ICLR), 2025.

• Confidence Matters: Revisiting Intrinsic Self-Correction Capabilities of Large Language Models
  Loka Li*, Zhenhao Chen*, Guangyi Chen*, Yixuan Zhang, Yusheng Su, Eric Xing, Kun Zhang.
  arXiv, 2024.

• On Causal Discovery in the Presence of Deterministic Relations
  Loka Li*, Haoyue Dai*, Hanin Ghothani, Biwei Huang, Jiji Zhang, Shahar Harel, Isaac Bentwich, Guangyi Chen, Kun Zhang.
  Conference on Neural Information Processing Systems (NeurIPS), 2024.

• Federated Causal Discovery from Heterogeneous Data
  Loka Li, Ignavier Ng, Gongxu Luo, Biwei Huang, Guangyi Chen, Tongliang Liu, Bin Gu, Kun Zhang.
  International Conference on Learning Representations (ICLR), 2024.

• Learning to Optimize Permutation Flow Shop Scheduling via Graph-based Imitation Learning
  Loka Li, Siyuan Liang, Zihao Zhu, Chris Ding, Hongyuan Zha, Baoyuan Wu.
  AAAI Conference on Artificial Intelligence (AAAI), 2024.

Service

- Serving as a reviewer for conferences and journals, including:

• International Conference on Machine Learning (ICML)
• Conference on Neural Information Processing Systems (NeurIPS)
• International Conference on Learning Representations (ICLR)
• International Conference on Artificial Intelligence and Statistics (AISTATS)
• International Conference on Data Mining (ICDM)
• IEEE Transactions on Neural Networks and Learning Systems (TNNLS).

- Serving as a teaching assistant for the courses, including:

• 2024/2025 Spring: ML808-Advanced Topics in Causality and Machine Learning. (Instructor: Prof. Jin Tian.)
• 2024/2025 Fall: ML801-Foundations and Advanced Topics in Machine Learning. (Instructor: Prof. Tongliang Liu.)
• 2023/2024 Spring: ML802-Advanced Machine Learning. (Instructor: Prof. Tongliang Liu.)
• 2023/2024 Fall: ML803-Advanced Probabilistic and Statistical Inference. (Instructor: Prof. Kun Zhang.)

Fun

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