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

(2023). The Detection, Extraction and Parameter Estimation of Extreme-Mass-Ratio Inspirals with Deep Learning. arXiv:2311.18640 [gr-qc].

DOI

(2023). Probing the gravitational wave background from cosmic strings with Alternative LISA-TAIJI network. The European Physical Journal C 83, no. 11 (November 7, 2023) 1010.

DOI

(2023). Detecting Extreme-Mass-Ratio Inspirals for Space-Borne Detectors with Deep Learning. arXiv:2309.06694 [gr-qc].

DOI

Github Contribution

iphysresearch's Github chart

Herb’s github stats

License

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