Mathematics / machine learning / scientific systems 数学 / 机器学习 / 科学系统

Grant Boquet Grant Boquet

Mathematician and machine-learning engineer building AI systems for environmental protection, science, geoscience, and other public-interest applications. 数学背景的机器学习工程师，构建面向环境保护、科学、地球科学与其他公共价值应用的 AI 系统。

  • Current 当前 Senior Research Fellow at Zhejiang Lab; Visiting Professor at Zhejiang University; CTO of Imbrial AI. 浙江实验室高级研究专家；浙江大学访问教授；Imbrial AI CTO。
  • Focus 方向 Environmental protection, Open Science, GeoGPT, evidence workflows, and compact deployment. 环境保护、开放科学、GeoGPT、证据工作流与紧凑部署。
  • Base 所在地 Hangzhou, China. 中国杭州。
Grant Boquet
Research and engineering across models, data, and deployed systems. 围绕模型、数据与可部署系统的研究和工程。

Profile 简介

I work on AI systems for environmental protection, science, and other public-interest applications, especially when the inputs are messy and the outputs need to be traceable, reusable, and useful for Open Science.

我的工作关注面向环境保护、科学和其他公共价值应用的 AI 系统，尤其是输入混杂、输出需要可追踪、 可复用并服务于开放科学的场景。

Earlier work included sonar and signal processing for underwater vehicles, then applied machine learning at Lawrence Livermore National Laboratory. Current roles include GeoGPT and scientific AI at Zhejiang Lab, a visiting professorship at Zhejiang University, and Imbrial, where I work on custom AI systems built around evidence, tools, and user context.

早期工作包括水下无人系统的声纳与信号处理，之后在 Lawrence Livermore National Laboratory 从事应用机器学习。 现在的角色包括浙江实验室的 GeoGPT 与科学智能工作、浙江大学访问教授、Imbrial， 以及围绕证据、工具和用户上下文构建的定制 AI 系统。

Background 经历

Virginia Tech mathematics, Metron, LLNL, Zhejiang Lab, and Imbrial.

从 Virginia Tech 数学，到 Metron、LLNL、浙江实验室与 Imbrial。

Projects 项目

Knifefish, pysparkplug for heterogeneous data, GeoGPT, and scientific AI systems.

Knifefish、面向异构数据的 pysparkplug、GeoGPT 与科学智能系统。

Talks 报告

GeoGPT standards, OneStrata, and AI workflows for science.

关于 GeoAI 标准、地层学与科学智能的技术报告。

Public links 部分公开链接