Summary

Hello, I’m He Wang (王赫). At the moment, I am exploring the fascinating world of gravitational wave physics as a postdoctoral researcher at ICTP-AP. My academic voyage took root at Beijing Normal University, where I was honored with a Ph.D. in 2020.

Embarking on the academic path is both challenging and fulfilling. I am firmly set on this path, ready to forge ahead with steadfast determination, undeterred by any obstacles or setbacks that might come my way. The joy I find in disseminating the knowledge I have gathered so far is immeasurable, particularly in the realms of Gravitational-Wave (GW) data analysis and Machine Learning (ML) technology.

Through my blog, I hope to foster a vibrant space of learning and curiosity, offering insights in both Chinese and English. I am in the process of cultivating a rich repository of knowledge, with the hope that, in time, I will carve out a viewpoint that is distinctly my own.

Guided by the profound words of S. Chandrasekhar, who noted, “I have the urge to present my point of view ab initio, in a coherent account with order, form, and structure,” I am navigating the intricate corridors of the academic world. My aim is to remain resilient, sharing my journey and insights, unfazed by potential hurdles or hindrances.

I envision this platform as a living testament to my commitment and evolution in the academic domain, showcasing a relentless pursuit of knowledge, undaunted by any challenges that lie ahead.

My scientific work has followed a certain pattern motivated, principally, by a quest after perspectives.
我的科学研究工作遵循了某种模式,它的动因主要是寻找观点

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Experience

 
 
 
 
 
Developing machine learning techiques for space-based GW projects (LISA/Taiji)
 
 
 
 
 
Peng Cheng Lab (PCL)
Visiting Scholar
December 2021 – July 2022 ShenZhen

Responsibilities include:

  • Analysing denoising techniques on GW observational data
  • Modelling transformer-based model (BERT)
  • Deploying large-scale pre-trained AI model
 
 
 
 
 
Research on rapid detection and inference on gravitational wave signals with deep learning

Teaching

Gravitational Wave Data Exploration: A Practical Training in Programming and Analysis
《引力波数据探索:编程与分析实战训练营》
Machine learning and GW data analysis
《深度学习之 PyTorch 实战》
《Python 数据可视化与实战》
《大数据预处理》
《Python 程序设计》
《Python 数据挖掘工具》

Recent Publication

(2024). Rapid Parameter Estimation for Merging Massive Black Hole Binaries Using Continuous Normalizing Flows. arXiv:2407.07125 [gr-qc].

DOI

(2024). The Detection, Extraction and Parameter Estimation of Extreme-Mass-Ratio Inspirals with Deep Learning. arXiv.2311.18640.

PDF DOI

(2024). Search for exotic gravitational wave signals beyond general relativity using deep learning. arXiv:2410.20129 [gr-qc].

PDF DOI

Github Contribution

License

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