清华大学孵化、院士团队引领、10年工程化积累、深度理解物理AI Incubated at Tsinghua University, led by academician team, 10 years of engineering accumulation, deeply understanding Physical AI
清研精准成立于2018年，由清华大学孵化，工信部"专精特新"小巨人企业，致力于打造物理AI的工程化底座，依托近10年在自动驾驶领域的深厚产业积淀及工程化能力，以高壁垒垂类工业场景驱动，通过五维数据工程化管线沉淀状态—动作—结果数据资产，并以工业认知系统提升模型在跨工况、跨产线、跨本体条件下的泛化能力。 Founded in 2018 and incubated by Tsinghua University, Tsing Standard is a MIIT "Specialized, Refined, Differential, and Innovative" Little Giant enterprise. We are committed to building the engineering foundation for Physical AI, leveraging nearly 10 years of deep industrial accumulation and engineering capabilities in autonomous driving. Driven by high-barrier vertical industrial scenarios, we accumulate state-action-result data assets through a five-dimensional data engineering pipeline, and enhance model generalization across different conditions, production lines, and embodiments through industrial cognition systems.
打通数采、仿真、验证、迭代全链路，构建"一套底座，一个大脑，百个垂类场景"的数据飞轮与工业智能AGI的核心基础设施。目前，公司解决方案已落地全球30多个国家，在新能源整车、动力电池、储能、核心零部件、矿山、电网等核心赛道深度服务100余家头部企业。已获吉利、一汽、北汽、长城、陕汽、蔚来、壳牌（Shell）、百度、58同城、奇绩创坛等多家产业背景资本投资，并形成深度战略绑定。 By connecting the full chain of data capture, simulation, validation, and iteration, we build the data flywheel and core infrastructure for industrial intelligent AGI with "one foundation, one brain, and hundreds of vertical scenarios." Currently, our solutions have been deployed in over 30 countries worldwide, deeply serving more than 100 leading enterprises in core tracks including new energy vehicles, power batteries, energy storage, core components, mining, and power grids. We have received investments from multiple industrial capital including Geely, FAW, BAIC, Great Wall, Shaanxi Auto, NIO, Shell, Baidu, 58.com, and Miracle Plus, forming deep strategic partnerships.
团队兼具世界级科研能力与产业工程化落地经验。核心科研成员及合作团队长期深耕计算成像、智能显微、物理约束 AI 与生命科学观测等交叉方向，相关成果已发表于《Nature》正刊及 Nature Biotechnology、Nature Methods、Science Advances 等国际顶级期刊；同时，公司在工业测试、数据采集、工程交付和客户落地方面具备多年积累，能够将前沿科研能力转化为可部署、可复制的产业级解决方案。 Our team combines world-class research capabilities with industrial engineering and deployment experience. Core research members and collaborative teams have long been engaged in cross-disciplinary directions such as computational imaging, intelligent microscopy, physics-constrained AI, and life science observation. Related achievements have been published in Nature (main journal) and top international journals including Nature Biotechnology, Nature Methods, and Science Advances. Meanwhile, the company has accumulated years of experience in industrial testing, data capture, engineering delivery, and customer deployment, enabling the transformation of cutting-edge research capabilities into deployable and replicable industrial-grade solutions.
清研精准从真实工业现场出发，提供从数据采集、处理，到模型训练与部署的完整能力体系，让 AI 能力真正扎根于工业物理世界。Tsing Standard starts from real industrial sites, providing a complete capability system from data capture, processing, to model training and deployment — so AI capabilities genuinely take root in the industrial physical world.
近十年汽车测试测量、新能源检测验证、自动驾驶测试与仿真经验，深度理解工业现场的复杂性和工程化要求。Nearly a decade of experience in automotive testing, new energy validation and autonomous driving simulation — deeply understanding industrial site complexity and engineering requirements.
中国工程院院士、清华大学李克强教授作为公司首席科学家，清华大学助理教授、特别研究员卢志作为合作科学家，带领来自清华大学、斯坦福大学、浙江大学、北京航空航天大学等多位科研人员在具身智能、计算成像、认知计算提供科学指导。Professor Li Keqiang (Academician of Chinese Academy of Engineering, Tsinghua University) as Chief Scientist, Asst. Prof. Lu Zhi (Tsinghua University) as Collaborative Scientist, leading researchers from Tsinghua, Stanford, Zhejiang University, Beihang University and more in embodied AI, computational imaging and cognitive computing.
已在动力电池、整车总装、矿山巡检、电网巡检等场景完成数据闭环验证，具备真实工业现场交付能力。Validated data loops in battery PACK, vehicle assembly, mining inspection and grid inspection — proven real industrial site delivery capability.
与超100家大型制造业企业客户构建生态，覆盖汽车主机厂、新能源、能源化工、低空经济、工程机械、智能制造等多个领域，共同推动工业AI在真实场景落地。Building ecosystem with 100+ large manufacturing enterprises, covering automotive OEMs, new energy, energy & chemicals, low-altitude economy, construction machinery, intelligent manufacturing and more — jointly advancing industrial AI in real scenarios.
清研精准具有7家汽车产业背景股东，2家制造业央企股东，1家全球能源巨头股东，1家互联网龙头企业股东，1家本地生活龙头企业股东，以及多家AI投资基金股东。7 automotive industry shareholders, 2 state-owned manufacturing enterprise shareholders, 1 global energy giant shareholder, 1 internet leader shareholder, 1 local services leader shareholder, and multiple AI investment fund shareholders.
清研精准联合工信部下属工信装备研究院，多家汽车、电池、具身智能等行业组织及协会，共同制定多项行业及团体标准，并联合国家动力电池创新中心构建具身智能-动力电池产业生态。Partnering with MIIT Equipment Research Institute, automotive, battery and embodied AI industry organizations to jointly develop multiple industry and group standards, and building embodied AI-battery industry ecosystem with National Power Battery Innovation Center.
清研精准过去 8 年深耕汽车、新能源、工业检测与测试验证场景，形成了稳定的客户基础与工程交付能力。在工业 AI 时代，我们将真实工业场景中积累的工程能力与数据资产，转化为可复用、可迁移的 AI 基础设施，服务更广泛的工业场景。Tsing Standard has spent 8 years in automotive, new energy, industrial inspection and testing — building a stable customer base and engineering delivery capability. In the industrial AI era, we transform the engineering capabilities and data assets accumulated in real industrial scenarios into reusable, transferable AI infrastructure, serving broader industrial applications.
从汽车测试到工业 AI，持续深耕工业现场From automotive testing to industrial AI, continuously deepening industrial site expertise
已进入国内几乎全部汽车主机厂，真实项目验证Entered nearly all domestic auto OEMs, validated by real projects
覆盖整车 / 电池 / 检测 / 科技平台Covering OEM / Battery / Testing / Tech platforms
覆盖汽车/零部件/新能源制造，矿下作业，电力巡检等Covering automotive/parts/new energy manufacturing, mining operations, power inspection, etc.
为机器人时代提供数据、技能、评测和工业智能能力。Providing data, skills, evaluation and industrial intelligence capabilities for the robotics era.
FOUNDER & CHAIRMAN · DONG HAN
清华大学车辆与运载学院博士，师从李克强院士（中国工程院院士）。曾任清华大学苏州汽车研究院感知检测中心主任，参与国家 863 电动汽车重大专项。PhD from Tsinghua University School of Vehicle and Mobility, supervised by Academician Li Keqiang (Chinese Academy of Engineering). Former Director of Perception & Detection Center at Tsinghua Suzhou Automotive Research Institute. Participated in National 863 Electric Vehicle Major Project.
2018年创立清研精准，8年深耕工业物理AI领域，带领团队从新能源行业出发，构建工业AI基础设施，服务国内主要工业企业。Founded Tsing Standard in 2018, 8 years in industrial Physical AI, led team from new energy sector to build industrial AI infrastructure, serving major domestic industrial enterprises.
工业 物理AI 需要的不是"更多数据拟合"，而是"更好的物理状态重建与泛化约束"。清华青年教授在高维动态观测、计算成像、物理驱动重建和自监督鲁棒学习方面的研究，为公司构建"仿生约束层"提供方法论支撑。Industrial Physical AI needs not "more data fitting" but "better physical state reconstruction and generalization constraints." Research in high-dimensional dynamic observation, computational imaging, physics-driven reconstruction and self-supervised robust learning provides methodological support for our bio-inspired constraint layer.
公司的核心团队汇聚了来自海内外顶级高校/AI实验室的学者，以及多家汽车及新能源企业的工程化骨干，共同打造物理AI的工程化底座。The core team brings together scholars from top universities and AI labs worldwide, along with engineering experts from automotive and new energy enterprises, jointly building the engineering foundation for Physical AI.
核心团队成员包括多篇发表在《Science》、《Nature》的第一作者、第二作者，国际顶级人工智能实验室的专家，国际顶级机器人公司的研发及业务负责人，以及汽车行业头部公司的工程化骨干。Core team members include first and second authors of Science and Nature publications, experts from top international AI labs, R&D and business leaders from leading robotics companies, and engineering experts from top automotive companies.
创始团队来自清华大学、中科院及头部整车企业，具备汽车测试测量、新能源检测验证、自动驾驶测试与仿真的深厚工程化经验。Founding team from Tsinghua, CAS and leading automotive enterprises — with deep engineering experience in automotive testing, new energy validation and autonomous driving simulation.
世界模型、多模态学习、VLA、强化学习、自监督学习方向的算法工程师和研究员，来自清华、北大、中科院、CMU、Stanford 等。Algorithm engineers and researchers in world models, multimodal learning, VLA, RL and self-supervised learning — from Tsinghua, PKU, CAS, CMU, Stanford, etc.
机器人控制、遥操作系统、传感器融合、嵌入式系统方向的工程师，具备 EGO+UMI 工具链和 Cross-Embodiment 平台开发经验。Engineers in robot control, teleoperation, sensor fusion and embedded systems — with EGO+UMI toolchain and Cross-Embodiment platform development experience.
数据工程、标注平台、仿真评测、Cross-Embodiment 平台方向的产品经理和工程师，负责数据资产化和平台服务。Product managers and engineers in data engineering, labeling platforms, simulation-evaluation and Cross-Embodiment platform — responsible for data assetization and platform services.
新能源、汽车制造、工业现场交付、测试验证方向的解决方案专家和交付经理，负责真实工业现场的工程化落地。Solution experts and delivery managers in new energy, automotive manufacturing, industrial site delivery and testing-validation — responsible for engineering implementation in real industrial sites.
清华大学卢志助理教授，在计算成像、认知计算和具身智能方向提供科学指导，为工业认知系统提供方法论支撑。Tsinghua Asst. Prof. Lu Zhi provides scientific guidance in computational imaging, cognitive computing and embodied intelligence for industrial cognition system methodology.
覆盖汽车、新能源、能源等多个行业，与行业伙伴共同推动工业 AI 在真实场景中的落地与标准建设。Spanning automotive, new energy and energy industries — jointly advancing industrial AI deployment and standard-building in real scenarios with our industry partners.
清研精准欢迎各行业伙伴一起探索工业 AI 的无限可能。Tsing Standard welcomes partners across industries to explore the unlimited possibilities of industrial AI together.
联系我们Contact Us →深入了解 物理AI 闭环、Cross-Embodiment 和职位机会。Dive deeper into Physical AI loop, Cross-Embodiment and career opportunities.