About Me
Yixin Ren (任一鑫)
Fourth-year PhD student at Fudan University
Email: yxren21@m.fudan.edu.cn
I am a PhD student in the Department of Computer Science at Fudan University, where I work under the supervision of Prof. Shuigeng Zhou. Previously, I completed my B.S. in Automation at University of Science and Technology of China.
I have interned at Alibaba and worked as a research assistant at the Chinese University of Hong Kong under Prof. Yufei Tao. Currently, I collaborate with Dr. Hao Zhang at Shenzhen Institutes of Advanced Technology (SIAT) and interned at Huawei Terminal Cloud Department.
My research focuses on causal discovery, statistical inference, and machine learning. I am open to collaboration opportunities, so feel free to reach out.
🔥 Research Interests
- Causal Discovery: Addressing practical challenges in discovering causal relationships.
- Statistical Inference: Developing kernel-based hypothesis testing methods.
- Machine Learning: Focusing on continual learning, recommendation systems, and generative modeling.
📝 Selected Publications
(* denotes equal contribution; full list available on Google Scholar or Publications)
Fast Causal Discovery by Approximate Kernel-based Generalized Score Functions with Linear Computational Complexity
Yixin Ren*, Haocheng Zhang*, Yewei Xia, Hao Zhang, Jihong Guan, Shuigeng Zhou.
KDD 2025 (Research Track)Efficiently Learning Significant Fourier Feature Pairs for Statistical Independence Testing
Yixin Ren, Yewei Xia, Hao Zhang, Jihong Guan, Shuigeng Zhou.
NeurIPS 2024Towards Effective Causal Partitioning by Edge Cutting of Adjoint Graph
Hao Zhang, Yixin Ren, Yewei Xia, Shuigeng Zhou, Jihong Guan.
IEEE TPAMILearning Adaptive Kernels for Statistical Independence Tests
Yixin Ren, Yewei Xia, Hao Zhang, Jihong Guan, Shuigeng Zhou.
AISTATS 2024Multi-Level Wavelet Mapping Correlation for Statistical Dependence Measurement
Yixin Ren, Hao Zhang, Yewei Xia, Jihong Guan, Shuigeng Zhou.
AAAI 2023Differentially Private Nonlinear Causal Discovery from Numerical Data
Hao Zhang, Yewei Xia, Yixin Ren, Jihong Guan, Shuigeng Zhou.
AAAI 2023Incremental Graph Classification by Class Prototype Construction and Augmentation
Yixin Ren, Li Ke, Dong Li, Hui Xue, Zhao Li, Shuigeng Zhou.
CIKM 2023 (Oral)Causal Discovery by Continuous Optimization with Conditional Independence Constraint
Yewei Xia, Hao Zhang, Yixin Ren, Jihong Guan, Shuigeng Zhou.
ICDM 2023 (Regular Paper, acceptance rate ~9.37%)
✍️ Academic Service
- Reviewer: ICML, NeurIPS, ICLR, AAAI, AISTATS
📐 Teaching Experience
- Teaching Assistant:
- 2023 Fudan Intensive Summer Course: Foundations of Causal Inference and Discovery
Instructor: Kun Zhang
Enrollment: 21 graduate students - 2021 Fudan Course: C++ Programming Course
Instructor: Yonghui Wu
- 2023 Fudan Intensive Summer Course: Foundations of Causal Inference and Discovery
🥇 Awards
- First Prize, Chinese Mathematics Competitions (CMC), First Place in Anhui Province Preliminary Round
🧩 Miscellaneous
- In my recent free time, I’ve developed an interest in learning about general relativity.
My childhood dream was to become a theoretical physicist, but due to life’s circumstances, it has remained a hobby. - I appreciate abstract art, particularly Picasso’s works, as well as the elegant simplicity of mathematical structures.
- I enjoy singing, especially songs by Jacky Cheung, Eason Chan, and more recently, Jian Li.
- Recently I’ve been interested in using suno ai for music generation.
Useful Links
- Generative Modeling by Estimating Gradients of the Data Distribution, by Yang Song
- Perspectives on diffusion, by Sander Dieleman
- Diffusion Models for Video Generation, by Lilian Weng
- The AI Revolution: The Road to Superintelligence, by Maarten Steinbuch
- Understanding LSTM Networks, by Christopher Olah
- The Unreasonable Effectiveness of Recurrent Neural Networks, by Andrej Karpathy
- Low Rank Methods, by Ethan N. Epperly