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混合现实人-智能体协同内容创作方法研究
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Project Code项目编号 SFXJTU2614 Brief introduction of the three supervisors (e.g. key academic background, work experience, research area, etc.) 三校导师简介，包括但不限于学术背景、工作经历及研究领域等 主导师：李月博士（西交利物浦大学） 李月博士，西交利物浦大学人工智能与先进技术学院副教授，博士生导师，遗产·教娱·现实课题组（HER Lab）负责人。主要研究方向包括人机交互、扩展现实、虚拟/增强现实、教育技术与文化遗产。已在 IEEE TVCG、ACM ToCHI、IEEE VR、IEEE ISMAR、ACM CHI、ACM CSCW 等国际期刊和会议发表论文90余篇。主持国家自然科学基金青年项目、教育部协同育人项目、江苏省高校自然科学研究面上项目等，入选江苏省双创博士计划，并获评苏州市科教骨干人才。现任 IFIP TC13 中国国家代表及 SIGCHI 亚洲委员会成员。个人主页：https://imyueli.github.io/ 合作导师：俞凌云博士（西交利物浦大学） 俞凌云博士，西交利物浦大学人工智能与先进技术学院资深副教授、博士生导师。主要研究方向包括沉浸式可视化、扩展现实、人机交互与数据可视化。已发表可视化与人机交互相关论文100余篇，主持国家自然科学基金项目2项（面上项目1项、青年项目1项）。曾获IEEE VIS科学可视化十二年时间检验奖、ACM CHI最佳论文奖，并多次在领域顶级会议担任论文主席。个人主页：https://yulingyun.com/ 合作导师：张未展教授（西安交通大学） 张未展，西安交通大学计算机学院教授，博士生导师。陕西省中青年科技创新领军人才, CCF杰出会员，CCF网络与数据通信/互联网/分布式计算与系统专委会执委，CSIG智能图形/多媒体专委会专委。现任Cernet西安核心节点主任、西安交大-咪咕5G未来媒体与人工智能联合创新实验室主任、陕西省大数据知识工程重点实验室副主任。研究方向为大规模分布式智能系统构建，涉及网络多媒体、多模态大模型、混合现实人机交互与空间智能等相关领域。在TPAMI, TON, TMC, TPDS, TVCG, NeurIPS, ICML, CVPR, ICLR, ICCV, AAAI, MM, VR等发表论文100余篇，授权专利40余项。曾第一完成人获陕西省科技进步一等奖，第二完成人获国家科技进步二等奖、教育部、电子学会科技进步一等奖、主要完成人获陕西省技术发明一等奖、中国自动化学会科技进步特等奖等。个人主页： https://faculty.xjtu.edu.cn/zhangwzh123/ 合作导师：Heba Lakany博士（英国利物浦大学） Heba Lakany博士为英国利物浦大学电气工程与电子学系副教授，获爱丁堡大学机器人与人工智能博士学位。她聚焦辅助技术、脑机接口、机器人外骨骼及自主机器人研究，以改善行动障碍人群生活质量。她兼具创业与教学经验，曾任职多所英国高校，并创办了一家专注于开发先进脑机接口和机器人外骨骼技术的初创企业，致力于推动机器人研究的现实应用。 Principal supervisor: Dr Yue Li (XJTLU) Dr Yue Li is an Associate Professor at the Academy of Artificial Intelligience and Advanced Technology at Xi’an Jiaotong-Liverpool University, where she leads the Heritage, Edutainment, and Reality Laboratory (HER Lab). Her research focuses on human-computer interaction, extended reality, virtual/augmented reality, educational technology, and cultural heritage. She has published over 90 papers in leading journals and conferences, including IEEE TVCG, ACM ToCHI, IEEE VR, IEEE ISMAR, ACM CHI, and ACM CSCW. She has led several research grants, including the NSFC Young Scientists Fund, the Ministry of Education Industry-University Collaborative Education Program, and the Jiangsu Higher Education Natural Science Foundation. She also serves as the China Country Representative of IFIP TC13 and a member of the Asia SIGCHI Committee. Personal website:https://imyueli.github.io/ Co-supervisor: Dr Lingyun Yu (XJTLU) Dr Lingyun Yu is a Senior Associate Professor at the Academy of Artificial Intelligience and Advanced Technology at Xi’an Jiaotong-Liverpool University. Her research focuses on immersive visualization, extended reality, human-computer interaction, and data visualization. She has published over 100 papers in visualization and HCI, and has led two projects funded by the National Natural Science Foundation of China, including one General Program and one Young Scientists Fund project. She received the IEEE VIS Scientific Visualization Test of Time Award and an ACM CHI Best Paper Award, and has served as paper chair for leading conferences in the field. Personal website: https://yulingyun.com/ Co-supervisor: Prof Weizhan Zhang (XJTU) Weizhan Zhang, Professor and PhD Supervisor, School of Computer Science, Xi’an Jiaotong University. He serves as the Director of the CERNET Xi'an Core Node, the Director of the Xi'an Jiaotong University–Migu 5G Future Media and Artificial Intelligence Joint Innovation Laboratory, and the Deputy Director of the Shaanxi Provincial Key Laboratory of Big Data Knowledge Engineering. His research focuses on large-scale distributed intelligent systems, including networked multimedia, multimodal large models, mixed reality, human-computer interaction, and spatial intelligence. He has published over 100 papers in venues such as TPAMI, TON, TMC, TPDS, TVCG, NeurIPS, ICML, CVPR, ICLR, ICCV, AAAI, ACM Multimedia, and IEEE VR, and holds over 40 granted patents. Homepage: https://faculty.xjtu.edu.cn/zhangwzh123/ Co-supervisor: Dr Heba Lakany (UoL) Dr. Lakany is a Reader (Associate Professor) in the Department of Electrical Engineering and Electronics at the University of Liverpool, where she leads groundbreaking research in assistive technologies motivated by improving quality of life for people with mobility challenges. She has founded a startup developing cutting-edge brain-machine interface and robotic exoskeletons technologies, bringing a wealth of experience to translating research into real-world impact for vulnerable populations. Key aspect/summary of your research project项目简介 本项目旨在研究一种新颖的人机协同内容创作框架，以突破当前制约扩展现实（XR）高质量内容生产的技术障碍。尽管当前扩展现实技术能够提供沉浸式三维环境，初学者在复杂的内容制作流程、脚本设计和镜头调度方面仍面临诸多困难。因此，本项目拟通过开发一个由大语言模型（LLM）和数据驱动算法支持的多模态系统来弥合这一差距，使其能够自主生成具备情境感知能力、面向用户需求的内容脚本。该方法的核心是设计一种专门的具身智能体，支持隐式与显式交互；该智能体将作为协作伙伴，在 XR 空间中负责镜头构图与拍摄控制。通过探索新型交互技术与工作流程，本研究将评估视觉引导如何提升创作效率和内容质量，并为人机协同创作提供可靠的工具原型。 This research proposes a novel Human-Agent Collaborative Content Creation framework to address the technical barriers currently hindering high-quality production in Extended Reality (XR). While XR offers immersive 3D environments, novice users often struggle with complex content workflows, script design, and camera orchestration. This project aims to bridge this gap by developing a multimodal system driven by Large Language Models (LLMs) and data-driven algorithms to autonomously generate context-aware, demand-oriented content scripts. Central to the approach is the design of a specialized Embodied Intelligent Agent capable of both implicit and explicit interaction; this agent functions as a collaborative partner that manages shot framing and capture control within the XR space. By exploring novel interaction techniques and workflows, the study will evaluate how visualized guidance improves creation efficiency and content quality, offering robust tool prototypes for collaboration. Other preferred qualification and skill set of the candidate 对项目候选人的其他学术背景及技能要求 候选人应具有计算机科学或相关学科背景，具备良好的编程能力，并对人机交互、虚拟/增强现实、人工智能或相关方向有浓厚兴趣。候选人应具有科研热情、自主学习能力、研究主动性和较高的工作标准。具有相关科研经历，或在 IEEE VR、IEEE ISMAR、ACM CHI 等高水平会议方向有项目经验和论文发表者优先。 Candidates should have a background in computer science or a related discipline, strong programming skills, and a keen interest in human-computer interaction, virtual/augmented reality, artificial intelligence, or related areas. They should demonstrate strong motivation, self-learning ability, research initiative, and high standards of work. Candidates with relevant research experience and publications in leading venues such as IEEE VR, IEEE ISMAR, and ACM CHI are preferred. 有意者请将个人简历及其他有助于申请的材料发送至 yue.li@xjtlu.edu.cn . 注:不用跟帖，直接发邮件就行，主题请注明博士申请 |
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2026-09-02 14:14:05, 58.45 K
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