Join加入我们
Open opportunities for undergraduates, graduate students, collaborators, clinical and educational partners, and industry deployment scenarios.面向本科生、研究生、合作伙伴和产业场景开放合作。
Join a Platform Where Strong Students and Serious Partners Can Build加入一个能让优秀学生与重要伙伴真正做成事的平台
MAC-Lab welcomes undergraduates, master's students, academic PhD students, engineering doctoral students, and collaborators interested in natural language processing, human-computer interaction, affective computing, ubiquitous psychological computing, embodied emotional intelligence, and deployable AI systems. The lab values high-quality publications, but its training and collaboration model also emphasizes engineering systems, field validation, technology transfer, and long-term capability building.MAC-Lab 面向本科生、硕士研究生、学术博士、工程博士及各类合作伙伴开放。我们长期聚焦自然语言处理、人机交互、情感计算、普适心理计算和具身情感智能。团队重视高水平论文，但培养与合作模式同样强调工程系统、场景验证、成果转化和长期能力沉淀。
- Undergraduates who want to join research projects, innovation competitions, and platform development early希望尽早参与科研项目、创新竞赛和平台研发的本科生
- Master's students, academic PhD students, and engineering doctoral students in computer science, electronic information, software engineering, artificial intelligence, and related fields计算机、电子信息、软件工程、人工智能等方向的硕士、学术博士与工程博士
- Cross-disciplinary partners in psychology, medicine, education, human factors, public health, and mental-health services心理学、医学健康、教育、人因工程、公共卫生与心理服务等交叉方向伙伴
- Research directions in emotional LLMs, empathetic dialogue, non-contact psychological assessment, smart intervention, and AI agents大模型情感感知、情感支持对话、非接触心理评测、智能干预与 AI Agent 研究
- Science communication around AI, mental health, digital humans, companion robots, and human-machine coexistence小红书、科普、课程与公众内容共创，让 AI 心理计算被更多人理解
Academic Lineage学术传承与方向底色
Rooted in Chinese NLP and AI大连理工：自然语言处理与人工智能根基
Professor Xiao Sun received doctoral training at Dalian University of Technology under Professor Huang Degen and CAS Academician Gao Qingshi, building a strong foundation in natural language processing, machine translation, and intelligent systems.孙晓教授在大连理工大学攻读博士期间，师从黄德根教授和中国科学院院士高庆狮先生，形成了自然语言处理、机器翻译和智能系统方向的扎实学术根基。
Connected to international affective computing日本德岛：接入国际情感计算脉络
His doctoral training in Japan was supervised by Professor Fuji Ren, a Japan Engineering Academy member and internationally influential scholar in affective computing and intelligent information processing.在日本国立德岛大学攻读博士期间，孙晓教授师从日本工程院院士任福继教授，接入了情感计算与智能信息处理领域具有国际影响力的学术脉络。
From academic roots to new frameworks从学术源流到自有框架
MAC-Lab extends this dual training into a distinct route: NLP, human-computer interaction, multimedia affective computing, ubiquitous psychological computing, and embodied emotional intelligence.MAC-Lab 在中日双博士训练和跨学科学术源流基础上，从自然语言处理、人机交互和多模态情感计算出发，进一步延伸到普适心理计算和具身情感智能。
Admissions Tracks招生与加入路径
For Undergraduate Students面向本科生
You can start from coding, reading papers, datasets, demos, and competition projects, then grow toward papers, patents, software systems, and long-term research topics.可以从编程、读论文、数据集、原型演示和竞赛项目开始，逐步走向论文、专利、软著、系统平台和长期研究题目。
For Master's Students面向硕士研究生
You will be encouraged to combine solid research training with system development, competitions, patents, and application scenarios.鼓励把扎实科研训练与系统开发、学科竞赛、专利软著和真实应用场景结合起来。
For Academic PhD Students面向学术博士
You will work on deeper scientific questions in affective NLP, multimodal modeling, psychological computing, embodied emotional intelligence, and AI agents.面向情感 NLP、多模态建模、心理计算、具身情感智能和 AI Agent 等方向，凝练更深入的科学问题。
For Engineering Doctoral Students面向工程博士
You will connect high-level research with major engineering scenarios, national-demand projects, industrial systems, and deployable platforms.面向重大工程场景、国家需求项目、产业系统和可部署平台，把高水平研究与工程落地结合起来。
Why This Platform Is Different为什么这个平台不一样
Students enter research questions with real funding and scenarios学生进入有项目、有场景的真问题
National and provincial projects on affective LLMs, non-contact psychological sensing, healthy living, autism support, and special scenarios provide concrete research tracks for students at different levels.大模型情感感知、非接触心理感知、健康人居、儿童孤独症辅助诊断和特殊场景等项目，为不同阶段学生提供真实研究入口。
From undergraduate contests to national innovation stages从本科竞赛走向国家级创新舞台
Students have been guided in Internet+ style innovation, China International College Students' Innovation Competition, robotics, IoT, digital media, smart transportation, and AI application contests.团队指导学生参加中国国际大学生创新大赛、互联网+ 类创新创业、机器人、物联网、数字媒体、交通科技和人工智能应用等赛事。
Good projects are expected to keep growing after the medal好项目不会止步于获奖
Promising student work can continue into papers, software systems, patents, demos, datasets, and deployable modules inside the lab's long-term platforms.有潜力的学生项目会继续打磨成论文、软著、专利、演示系统、数据集和实验室长期平台中的可复用模块。
Research is trained against users, products, and public value科研要经得起用户、产品和社会价值检验
Psychological monitoring devices, mind-body assessment systems, intervention cabins, smart cockpits, and public-health scenarios help students and partners understand how algorithms become usable capability.心理监护设备、身心评测一体机、心身干预座舱、智能座舱和公共健康场景，让学生和合作伙伴理解算法如何真正变成可用能力。
For Industry and Public-Sector Partners面向产业与公共场景合作伙伴
MAC-Lab is suitable for partners whose problems cannot be solved by buying an off-the-shelf emotion-recognition model. If your scene involves human state, affect, stress, cognitive load, fatigue, motivation, role fitness, safety, health, service quality, or human performance, the real task is usually a full route: define the problem, sense the right signals, model the state, evaluate risk or capability, design support, and deploy the system responsibly.MAC-Lab 适合那些不能靠购买一个通用情绪识别模型解决问题的合作伙伴。只要你的场景涉及人的状态、情绪、压力、认知负荷、疲劳、动机、岗位适配、安全、健康、服务质量或身心效能，真正要做的通常是一整条路线：定义问题、选择信号、建模状态、评价风险或能力、设计支持方式，并负责任地部署系统。
Turn a scene pain point into a solvable route把场景痛点变成可解决路线
Many AI + psychology projects fail before modeling begins because the task boundary, user role, signal source, evaluation target, and intervention goal are not defined together. This is where MAC-Lab can add value early.很多 AI + 心理项目还没建模就已经出问题，因为任务边界、用户角色、信号来源、评价目标和干预目标没有一起定义清楚。MAC-Lab 可以在合作早期把问题定义扎实。
Design models, methods, devices, and workflows together把模型、方法、设备和流程一起设计
Psychological computing rarely depends on one model alone. It needs multimodal sensing, affective NLP, behavior modeling, human-computer interaction, assessment protocols, and deployment-aware engineering.心理计算很少靠单一模型解决。它需要多模态感知、情感 NLP、行为建模、人机交互、评测流程和面向部署的工程实现一起配合。
Move from prototype to field-tested capability从原型走向现场验证能力
The lab has repeatedly worked through field validation, hardware-software integration, scenario adaptation, user feedback, standards awareness, technology transfer, and platform operation.团队已经反复经历场景验证、软硬件集成、现场适配、用户反馈、标准意识、成果转化和平台运行等环节，理解从“能跑”到“可用”之间的真实难点。
Build assets that partners can keep using沉淀合作方能继续使用的资产
A good collaboration should produce papers when appropriate, but also reusable modules, patents, datasets, evaluation protocols, student talent, software-hardware platforms, and a clearer product direction.好的合作可以产出论文，但不应止于论文；还应沉淀可复用模块、专利、数据、评测流程、学生人才、软硬件平台和更清晰的产品方向。
Bring a real scene, not a polished brief带着真实场景来，而不必先写完美需求书
A collaboration can start from a site visit, pain-point diagnosis, pilot dataset, technical feasibility study, algorithm module, or prototype system.合作可以从现场调研、痛点诊断、试点数据、技术可行性分析、算法模块或原型系统开始。
Methods, algorithms, platforms, and validation方法、算法、平台与验证一起交付
Possible outputs include multimodal models, human-factor assessment methods, dashboards, sensing terminals, intervention devices, digital-human interfaces, and field evaluation reports.可能产出包括多模态模型、人因评价方法、管理看板、感知终端、干预设备、数字人界面和现场评估报告。
Long-cycle problems where affect and human factors matter适合情感与人因真正重要的长期问题
The lab is especially suited to scenarios where scientific credibility, engineering maturity, product definition, responsible deployment, and industry impact must be developed together.尤其适合那些需要同时发展科学可信度、工程成熟度、产品定义、负责任部署和产业价值的长期问题。
Research, Engineering, and Deployment in One Route把科研、工程与场景落地放在同一条路线中
The lab combines IEEE/ACM-level publications, national research programs, defense and public-safety oriented projects, technology transfer, intelligent psychological products, smart cockpit systems, and embodied emotional interaction platforms. Students and partners can see how research questions become validated systems and reusable capability.团队同时拥有 IEEE/ACM 等高水平论文、国家级科研任务、国防与公共安全导向项目、专利成果转化、智能心理产品、智能座舱系统和具身情感交互平台。学生和合作伙伴在这里看到的是科研问题如何进一步变成可验证系统和可复用能力。
A Broad Training and Collaboration Network联合培养与开放合作生态
MAC-Lab grows through joint graduate training with the National University of Defense Technology and sustained exchange with universities such as USTC, UESTC, Tsinghua University, HIT, ECNU, BNU, Dalian University of Technology, Tongji University, Southeast University, regional academic partners, major technology companies, and national-demand application scenarios. The collaboration network gives students access to broader questions, stronger peer communities, and real platforms where research can be tested.MAC-Lab 与国防科技大学开展研究生联合培养，并与中国科学技术大学、电子科技大学、清华大学、哈尔滨工业大学、华东师范大学、北京师范大学、大连理工大学、同济大学、东南大学以及省内高校与区域平台保持合作交流，同时连接头部科技企业和国家重大需求场景。学生在这里接触的不只是单一课题，而是更广阔的问题、更强的同行社区和能够验证研究价值的真实平台。
For Academic Collaborators面向学术合作
We welcome collaboration on multimodal affect recognition, psychological computing datasets, clinical and educational validation, embodied emotional agents, and responsible AI for mental health.欢迎围绕多模态情绪识别、心理计算数据集、临床与教育验证、具身情感智能体、心理健康负责任 AI 等方向开展合作。
For Industry Partners面向企业合作
Potential deployment scenarios include smart cockpits, healthy living environments, intelligent mental-care services, digital human interaction, education, and human-performance support.可合作场景包括智能座舱、健康人居、智能心理服务、数字人交互、教育心理与身心效能提升。
For National-Demand Scenarios面向重大需求场景
The lab welcomes serious scenarios where psychological computing, affective interaction, and embodied intelligence can serve safety, health, training, and human performance.欢迎在安全、健康、训练、人因效能和重大装备相关场景中探索心理计算、情感交互与具身智能的真实价值。