徐北辰 Beichen Xu

RealRain · 二次元实体与出版 · AI4Science RealRain · Anime Goods & Publishing · AI4Science

徐北辰 Beichen Xu

非雨（ThisRainIsNotARealRain）创始人 / CEO。公司业务为二次元实体与商业化出版，以本体驱动的连续出版为核心方法。此前在 AI4Science 与计算机视觉方向从事研究与工程。 Founder / CEO of ThisRainIsNotARealRain. The company works in anime physical goods and commercial publishing, built on ontology-driven continuous publishing. Before this I worked in AI4Science and computer vision, in both research and engineering.

下载简历 Download CV 查看项目 View projects

位置Location

北京海淀Haidian, Beijing

方向Focus

二次元实体与出版 · AIGCAnime goods & publishing · AIGC

工作Role

创始人/CEOFounder/CEO

概览 Snapshot

方向Focus
二次元实体与商业化出版 · AIGC 系统 · 计算机视觉与多模态Anime goods & commercial publishing · AIGC systems · Computer vision & multimodal
状态Availability
开放合作 Open to collaborate
邮箱Email
beichenxu0249@gmail.com
电话Phone
+86 18260568009 +44 07410915752

关于About

我是非雨（ThisRainIsNotARealRain）的创始人兼 CEO。公司业务为二次元实体与商业化出版，以本体驱动的连续出版组织 IP 的开发节奏。此前的研究与工程背景在计算机视觉与多模态、AI4Science 与 Physics ML。 I’m the Founder and CEO of ThisRainIsNotARealRain. The company works in anime physical goods and commercial publishing, using ontology-driven continuous publishing to structure how an IP is developed. My research and engineering background is in computer vision and multimodal learning, AI4Science and physics ML.

教育Education

帝国理工学院 · MRes Imperial College London · MRes

Machine Learning and Big Data in the Physical Sciences（2023–2024，物理系） MRes in Machine Learning and Big Data in the Physical Sciences (2023–2024, Department of Physics)

  • 时间序列Time Series
  • 加速数据处理Accelerated Data Processing
  • FPGA
  • 宇宙学Cosmology

伯明翰大学 · BSc University of Birmingham · BSc

Physics（2020–2023，一等荣誉） BSc in Physics (2020–2023, First Class Honours)

  • 统计学Statistics
  • 相对论Relativity
  • 量子力学Quantum Mechanics
  • 线性代数Linear Algebra

项目Projects

AeroDiT（用于 RANS 的扩散 Transformer） AeroDiT (Diffusion Transformers for RANS)

将扩散模型与Transformer结合，用于 Reynolds-Averaged Navier–Stokes 空气动力学仿真（翼型流动）。 Diffusion Transformers for Reynolds-Averaged Navier–Stokes simulations of airfoil flows.

  • 扩散模型Diffusion
  • TransformerTransformers
  • 流体力学Fluid Dynamics

MRes 项目 · 引力波 WGAN MRes Project · Gravitational Wave WGAN

模拟多源引力波时序信号，训练 WGAN 以从信号中重建参数；使用 HPC 进行训练与可视化分析。 Simulated multi-source gravitational-wave time series and trained WGANs to reconstruct parameters; trained and analyzed on HPC.

  • PyTorch
  • PyTorch Lightning
  • 高性能计算HPC

多模态 GIS / 遥感训练流程 Multimodal GIS / Remote Sensing Pipelines

面向大规模地理遥感任务（道路提取、轨迹建模、卫星影像理解）构建 VL/多模态训练与评估流程，包含 LoRA 与全参微调实验。 Built vision–language / multimodal pipelines for large-scale GIS and remote sensing tasks (road extraction, trajectory modeling, satellite understanding), including LoRA and full fine-tuning experiments.

  • 视觉语言Vision–Language
  • LoRA
  • 多 GPUMulti-GPU

机器学习增强的贝叶斯推断（嵌套采样） ML-enhanced Bayesian Inference (Nested Sampling)

在宇宙学推断中结合嵌套采样与机器学习（masked aggressive flow），用于后验分布生成与参数估计；并参与维护开源 Python 包。 ML-enhanced Bayesian inference for cosmology: nested sampling + masked aggressive flow for posterior generation and parameter inference; contributed to an open-source Python package.

  • 贝叶斯Bayesian
  • 嵌套采样Nested Sampling
  • Python

经历Experience

  1. 创始人 / CEO · 非雨（AIGC 创业） Founder / CEO · ThisRainIsNotARealRain (AIGC startup)

    — 至今Present

    • 二次元实体：覆盖从设计落地到生产与履约的全部环节，以实际销量评估 IP 的商业潜力。 Anime physical goods: the full chain from product design through production and fulfillment, with actual sales assessing an IP’s commercial potential.
    • 商业化出版：经验证的 IP 推进至品牌授权，按品类与地区分别签约，构成公司主要收入。 Commercial publishing: validated IP moves into brand licensing, signed separately by category and region — the company’s primary revenue line.
    • 自研 RainStudio 与 RainHub，分别支撑内容开发与创作者社区、周边履约；设定与授权记录集中管理，新项目可直接复用。 Built RainStudio and RainHub in-house, covering content development and the creator community and merch fulfillment respectively, with settings and licensing records managed centrally for reuse across projects.

  2. AI 算法工程师 · MapTech（北京） AI Algorithm Engineer · MapTech (Beijing)

    —

    • 计算机视觉/视觉语言方向：构建 VL 与多模态学习流程，面向 GIS 与遥感任务（道路提取、轨迹建模、卫星影像理解）。Computer vision & vision–language: built VL/multimodal pipelines for GIS and remote sensing (road extraction, trajectory modeling, satellite understanding).
    • 主导全参微调与 LoRA 轻量适配实验（如 Qwen-VL），提升跨区域/跨模态数据集效率。Led full fine-tuning and LoRA adaptation experiments (e.g., Qwen-VL) to improve efficiency across heterogeneous geospatial datasets.
    • 设计地理特征 tokenization 与融合策略（patch、轨迹 embedding、hint maps），支撑分割与推理任务。Designed geospatial feature tokenization and fusion (image patches, trajectory embeddings, hint maps) for segmentation and reasoning.
    • 搭建可复现的多GPU训练/评估工作流，优化数据标注对齐与 benchmarking。Built reproducible multi-GPU training/evaluation workflows and improved curation, alignment, and benchmarking.
    • 与产品/工程团队合作，将研究原型落地为生产 pipeline 组件。Collaborated with product/engineering to translate prototypes into deployable components.

  3. AI 算法研究员 · Science42.tech（北京） AI Algorithm Researcher · Science42.tech (Beijing)

    • 研究 Transformers / Diffusion / GNN 在流体、医学与能源等科学场景的应用。Researched Transformers/Diffusion/GNNs for scientific domains including fluids, biomedicine, and energy systems.
    • 与清华大学、西湖大学、IMEC（比利时）等团队保持学术合作与交流。Maintained close collaborations with Tsinghua, Westlake University, and IMEC (Belgium) through joint studies and exchanges.
    • 开发 physics-informed AI 模型并推动高质量论文产出（投稿至《Physics of Fluids》等）。Developed physics-informed AI models and contributed to high-quality publications (e.g., submissions to Physics of Fluids).
    • 与跨学科团队协作研究代码与流程，并指导实习生完成科研与技术任务。Worked with interdisciplinary teams on research pipelines and mentored interns on technical/research tasks.

  4. 暑期实习 · Kavli Institute of Cosmology（剑桥） Summer Intern · Kavli Institute of Cosmology (Cambridge)

    • 研究 ML 增强的 Bayesian inference：使用 nested sampling 训练宇宙学数据，并用 masked aggressive flow 生成后验。Worked on ML-enhanced Bayesian inference for cosmology: nested sampling + masked aggressive flow for posterior generation.
    • 参与开源 Python 包 “margarine” 的贡献与协作。Contributed to the “margarine” Python package on GitHub.

  5. 暑期实习 · 紫金山天文台（南京） Summer Intern · Purple Mountain Observatory (Nanjing)

    • 对 GRB 现象做系统性综述；用 Python 对 Swift GRB 数据进行拟合与分析。Reviewed GRB literature and analyzed Swift GRB data with Python (fitting and statistical analysis).
    • 使用统计方法改进参数估计，熟悉 iminuit 的最小化与误差分析流程。Applied statistical methods for parameter estimation; used iminuit for minimization and uncertainty analysis.

摘要Highlights

  • 方向：二次元实体与商业化出版 / AIGC 系统 / 计算机视觉与多模态 Focus: anime goods & commercial publishing / AIGC systems / computer vision & multimodal
  • 能力：模型研发、数据融合、可复现训练与评估、多GPU工作流 Strengths: modeling, data fusion, reproducible training & evaluation, multi-GPU workflows
  • 合作：跨学科协作，把原型推进到可交付组件 Collaboration: cross-functional work from prototype to deployable components
  • TransformerTransformers
  • 扩散模型Diffusion
  • 图神经网络GNN
  • LoRA
  • PyTorch

论文Publications

  1. “An expanding balloon: a small universe.”

    Xu, Beichen; Su, Jun; Wang, Weiguo · Physics Education 53.6 (2018): 065005. Xu, Beichen; Su, Jun; Wang, Weiguo · Physics Education 53.6 (2018): 065005.

  2. “AeroDiT: Diffusion Transformers for Reynolds-Averaged Navier-Stokes Simulations of Airfoil Flows”

    Beichen Xu, Yuhao Ma, Biyue Pan, Hao Zheng, Zhibo Dai, Chunyang Wang, Hui Xiang, Dixia Fan

技能Skills

编程 / 框架Programming

  • Python, C++, Mathematica, SQL
  • PyTorch, TensorFlow

工程工具Tooling

  • Linux / Unix / Bash / vim
  • git / LaTeX / Docker

语言与奖项Languages & Awards

语言Languages

  • 中文：母语Chinese: Native
  • 英文：流利（口语与写作）English: Fluent (spoken and written)
  • 日语：N3（中级）Japanese: Intermediate (JLPT N3)

奖项Awards

  • 2018 · 未来科学家大奖（银奖）2018 · Award Program for Future Scientists — Silver medal
  • 2019 · 江苏省物理奥赛一等奖2019 · Physics Olympiad (Jiangsu, China) — First prize
  • 2020 · 南通市长科技创新奖2020 · Nantong Mayor’s Award for Science & Technology Innovation