wyf-accept / my-resume

汪一帆的个人简历

Hi，这里是我的个人简历页面！我会及时将最新的个人经历更新到这个仓库中。这个项目借用了 sb2nov/resume 作为模板。

中文详细简历请参见：

汪一帆.pdf

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Personal Resume of Yifan Wang (PlanD)

Hello, welcome to my personal resume page! I will consistently update my latest personal experiences in this repository. This project is based on the template by sb2nov/resume.

For a detailed English version of my resume, please refer to:

YifanWang.pdf

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个人经历及成长历程

如果你认为简历过于冗长，也可以在这里看看我的个人简介。

我本科和研究生均在清华大学就读，跨度为 2017 年至 2024 年。我从 2019 年开始决定做一名程序员，这些年我也探索了非常多的方向。

• 编程技能: 我擅长多种编程语言，精通 Python，熟悉 C++, NodeJS/Typescript, Rust 等。我使用这些语言解决算法问题，并在项目开发中保持简洁而清晰的代码风格。除此之外，我很擅长学习并上手一门新的编程语言。

• 数据科学: 我的主业一度是数据科学。我曾从完整选修过从传统机器学习到大型语言模型的全部课程，中间做过的小项目涵盖了 CV, NLP 的各个领域；也曾从数据爬取、清洗、分析到建立索引和数据库、搭建网页，跑通过完整的传统互联网项目流程。

• 论文发表: 2021 年，我和朋友合作发表了论文 Back to Reality，刊登在 CVPR 2022 上。但由于一些学术纠纷的原因，我在投稿的最终阶段只拿到了二作。此处是Github代码链接: wyf-ACCEPT/BackToReality。也是这个时候开始，我决定不再做学术研究。

• Web3 技能: 2021 年末，我开始做区块链相关的事情。我在 Dune, Footprint, Sentio 上都做过链上数据分析，还曾被邀请做过几次相关的 AMA；我用投研所学的知识在 Mirror, Medium, Techflow 上均发表了不少文章；在 IVC 做投研的时候，我产出了 40+ 篇投研报告；此外，我还曾作为核心成员参与开发了 WTF-Solidity 项目。

• 合约开发: 从 2022 年中旬开始，因为对合约开发感兴趣，我以此学会了 Solidity, Move, Rust 等多种合约开发语言，并完全独立地给跨链桥 MesonFi 开发了 4 份链上合约，包括 Algorand合约、Aptos合约、Sui合约 和 Solana-Rust合约。这件事上我学到了非常多，前后一共花费了一年以上的时间 (大致 2022.7~2023.9)。

• ZKML: 我也曾想过如何将我前几年所学的数据科学与 Web3 结合起来。所幸，我发现了 ZKML 这个领域，简单来说是用零知识证明来验证机器学习模型的完整性。于是，我将硕士的研究课题改为了该领域——为此我补习了很多密码学、抽象代数的底层数学知识，并对着 ZK-Snark Groth16 原理的相关文章死磕过很多遍。

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Personal story/experience in one page

If you find the resume is too lengthy, you can also take a look at my personal introduction here.

I pursued both my undergraduate and graduate studies at Tsinghua University, spanning from 2017 to 2024. Starting from 2019, I decided to become a programmer, exploring various directions over these years.

• Programming Skills: I excel in multiple programming languages, particularly proficient in Python and familiar with C++, NodeJS/Typescript, Rust, and more. I use these languages to tackle algorithmic problems and maintain a concise and clear coding style in project development. Furthermore, I am adept at quickly learning and picking up new programming languages.

• Data Science: Data science was once my major focus. I have taken a range of courses covering traditional machine learning to large-scale language models, undertaking small projects in various fields of computer vision and natural language processing. I've also gone through the entire process of traditional internet project flow, from data scraping, cleaning, analysis, to setting up indexes, databases, and web development.

• Published Papers: In 2021, a friend and I collaborated on a paper titled Back to Reality, which was published in CVPR 2022. Due to some academic disputes, I ended up being a second author in the final submission stage. The GitHub repository for this work can be found at wyf-ACCEPT/BackToReality. It was during this time that I decided to transition away from academic research.

• Web3 Skills: Towards the end of 2021, I began working on blockchain-related projects. I've conducted on-chain data analysis on platforms such as Dune, Footprint, and Sentio. I've participated in several related Ask-Me-Anything (AMA) sessions. Applying my research skills, I authored numerous articles on platforms like Mirror, Medium, and Techflow. During my investment research role at IVC, I produced over 40 investment research reports. Moreover, I contributed as a core member in the development of the WTF-Solidity project.

• Smart Contract Development: Starting from mid-2022, my interest in smart contract development led me to learn Solidity, Move, Rust, and other contract-oriented programming languages. I independently developed four on-chain contracts for the cross-chain bridge MesonFi, including the Algorand contract, Aptos contract, Sui contract, and Solana-Rust contract. Throughout this journey, I gained extensive knowledge, dedicating more than a year (approximately from July 2022 to September 2023).

• ZKML: I also contemplated how to integrate my prior data science knowledge with Web3. Fortunately, I discovered the field of Zero-Knowledge Machine Learning (ZKML), which focuses on using zero-knowledge proofs to validate the integrity of machine learning models. Consequently, I shifted my master's research topic to this field. This decision led me to study foundational mathematics in cryptography and abstract algebra, deeply engaging with the principles of ZK-Snark Groth16.