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Hello, I'm

Ziliang Shen(沈梓梁)

It's very nice to meet you!

"Love is the minimal unit of communism." — Alain Badiou

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About Me

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Education icon Education Background

Bachelor in Mathematics

Nanchang University

PhD in Statistics (in pursuing)

Shanghai University of Finance and Economics

I am a Ph.D. candidate in Statistics at Shanghai University of Finance and Economics. My research passion lies at the intersection of statistical and machine learning theories, with a specific focus on Reinforcement Learning in Finance, Differential Privacy, and Distributed Statistical Inference.

Outside of academics, I have a strong passion for literature, art, psychoanalysis, movies, and jazz music. It would be a great honor to be able to communicate with you academically and in terms of interests.

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Explore My

Experience

skill icon Skills

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R, Python

Experienced

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MATLAB, C, SAS

Intermediate

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Scala

Serve as a TA for relevant courses

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Rust

Learning !!!

Education icon Experience

Fibonacci Capital

Data Analysis      2024.04 - 2024.06

Shanghai Electric Solar Cell Target Detection Project

2024.06 - 2024.07

Shanghai GDP Nowcasting Project

2024.07 - 2024.09

Turing Fund Managment

Reinforcement Learning Quantitative Researcher      2025.03 - now

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Browse My Recent

Publication

Caixing Wang, Ziliang Shen*, (2024).     Distributed High-Dimensional Quantile Regression: Estimation Efficiency and Support Recovery.

Accepted by ICML 2024 Spotlight. [Paper] [Code]

Hanteng Ma, Ziliang Shen*, Xingdong Feng, Xin Liu.     Sparsity learning via structured functional factor augmentation.

Under Review. [Paper]

Caixing Wang, Ziliang Shen*, Shaoli Wang, Xingdong Feng.     Estimation and Inference on Distributed High-Dimensional Quantile Regression: Double-Smoothing and Debiasing.

Under Review.

Ziliang Shen*, Caixing Wang, Shaoli Wang, Yibo Yan.     High-Dimensional Differentially Private Quantile Regression: Distributed Estimation and Statistical Inference.

Under Review. [Paper]

Ziliang Shen*.     QR-DQN Meets Conditional Value-at-Risk: Towards More Robust Distributional Reinforcement Learning.

In Preperation

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Get in Touch

Please feel free to contact me anytime

muxin19980125@163.com