项目内容包括生物传感理论、蛋白质折叠过程、单分子检测技术、荧光光谱应用、非标记检测技术等。学生将通过项目了解生物传感器的类型和运作机制，掌握单分子生物传感器等前沿生物传感技术，在项目结束时提交项目报告，进行成果展示。 个性化研究课题参考： 光学传感方法的构建及其在环境检测中的应用 纳米复合材料光电化学传感应用研究 纸基折叠电池的制备与化学传感应用 新型光化学传感分子的设计合成与分子识别研究 This project includes the knowledge of biosensing theory, protein folding process, single-molecule detection technology, fluorescence spectroscopy application, non-label detection technology, etc. Students will learn about the types and operating mechanisms of biosensors, cutting-edge biosensing technologies such as single-molecule biosensors, and submit a reasearch report at the end of the project to show their results. Suggested Future Research Fields: The construction of optical sensing method and its application in environmental detection Research on application of nanocomposite photoelectrochemical sensing Preparation and chemical sensing application of paper-based folding battery Design, synthesis and molecular recognition of new type photochemical sensor molecules
Prof. Joshua received his Ph.D. on the development of single-molecule detection within microfluidic systems at Imperial College London in 2003. He then performed postdoctoral research in nanobiotechnology at Cornell University within the School of Applied and Engineering Physics. In July 2006 he joined Imperial College London within the Department of Chemistry and Institute of Biomedical Engineering as a lecturer. Joshua is currently a Professor in the Department of Chemistry and 2011 he was awarded a prestigious ERC Starting Grant on “Nanoporous Membranes for High Throughput Rare Event Bioanalysis” and in 2016 he was awarded an ERC Consolidator Grant related to the development of selective single-molecule biosensors. Joshua导师现任帝国理工学院化学系生物传感与分析科学终身正教授、东京理工学院客座教授，是英国皇家化学学会会员，欧洲研究理事会（ERC）巩固者奖获得者（奖励杰出独立科研人员）、欧洲研究理事会（ERC）启动基金获得者（奖励职业生涯早期杰出学者）。Joshua导师现已发表百余篇学术论文，受邀参加近百次学术演讲。他带领学生创立“Edel group”，研究领域涵盖化学、化学生物学、物理学和医学，致力于研究和开发灵敏度高、轻量化的新型传感器。
生物传感概论：生物传感器历史、医学传感器技术革新驱动力、传感器基本工作原理、微流控传感器Introduction to biosensing. History of biosensors, motivation for improving sensor technology in medicine, typical operating principles, challenges, and microfluidic sensors.
蛋白质折叠：蛋白质折叠在生物和医学的重要意义、蛋白质最新研究工具Introduction to protein folding. Topics in this week cover why studying protein folding is important in biology and medicine, and state of the art tools used to study proteins.
单分子检测方法：单分子检测方法在诊断和医学传感器使用中的重要作用Introduction to single molecule detection. Importance of studying single molecules will be discussed especially in the context of sensors in diagnostics and medicine.
荧光光谱应用：荧光探针和生物医学传感器Applications of fluorescence spectroscopy. Fluorescent probes and sensors for biomedical applications.
非标记检测技术：基因组测序工具及医学诊断和筛选疾病中的相似技术Label free detection strategies. Tools for DNA sequencing will be discussed along with using similar technology for diagnostics and screening of diseases.
项目回顾与成果展示Program Review and Presentation
论文辅导 Project Deliverables Tutoring
工程
黑碳的环境老化与环境氧化
同济大学 环境科学与工程学院 教授 博导 美国加州大学洛杉矶分校 访问学者 研究方向： 1. 环境污染与修复 2. 土壤环境学 3. 纳米环境学 主讲课程： 环境污染修复学，环境地学 已在专业核心学术刊物及国内外会议发表论文30余篇，申请国家专利6项，其中已授权4项。主持国家自然科学基金项目6项、浙江省自然科学基金1项，参与国家自然科学重点基金、国家重点研发计划项目课题、教育部科技创新工程重大培育项目、上海市科委社会发展项目4项。担任《农业资源与环境学报》编委、ES&T等二十余种SCI刊物审稿人，国家自然科学基金项目通讯评审专家、国家重点研发项目视频答辩评审专家。
工程
自动化与控制理论专题：机器人设计与应用研究【大学组】
Nader导师于1988年加入佐治亚理工学院，现任George W. Woodruff机械工程学院终身教授及机器人博士项目主任，Nader教授在加州大学伯克利分校取得硕士及博士学位，早期研究工作是在机器人和自动化领域。他在这一领域的主要贡献是开发了一类用于非线性机械系统的自适应和学习控制器，包括机器人操纵器，它使机器人像人类一样能够通过实践来学习重复的任务，且不需要精确的模型。后来工业生产证明，实现这种学习控制器可以在不显著增加成本或复杂性的情况下显著提高工业机器人的性能，并有潜力提高自动化制造系统的准确性、自主性和生产率。除了机器人技术，导师还曾开发了一种类似的学习控制器，用于调节复印机感光器的速度，这是施乐公司赞助的一个项目的一部分。 Dr. Nader's early research work was in the field of robotics and automation. His major contribution to this field was the development of a class of adaptive and learning controllers for nonlinear mechanical systems including robotic manipulators. This work, which evolved from his doctoral research, enables a robot to learn a repetitive task through practice, much like a human being, and without requiring a precise model. He later demonstrated that implementing this learning controller can significantly improve the performance of industrial robots without significantly increasing their cost or complexity, and has the potential to improve the accuracy, autonomy, and productivity of automated manufacturing systems. In addition to robotics, he developed a similar learning controller for speed regulation of copier photoreceptors as part of a project sponsored by the Xerox Corporation. Dr. Sadegh began at Tech in 1988 as an Assistant Professor.
自然科学
应用数学前沿研究【高中组】
Prof. Alberto is a Senior Faculty Scientist in the Mathematics Group at LBNL. He also holds a full-time position in the Mathematics Department at UC Berkeley. Before joining LBNL in 1976, Grünbaum taught at the Courant Institute in NYU, was a research scientist at the IBM Research Center in Yorktown Heights, NY and then joined the Applied Mathematics Department at Caltech before moving to Berkeley in 1974. He has served as director of the Center for Pure and Applied Mathematics and then Chairman of the UC Berkeley Mathematics Department from 1989--1992. He has been published extensively in the area of imaging, and his recent research interests include the study of Quantum Walks and its applications to different areas of science and technology. Alberto导师是加州大学伯克利分校应用数学终身正教授，在加州大学伯克利分校讲授线性代数等课程，曾任加州大学伯克利分校数学系主任、曾任英国物理研究所出版刊物Inverse Problems主编，曾在纽约大学柯朗数学研究所（Courant Institute；全球Top1应用数学研究中心）、IBM全球研究中心、劳伦斯伯克利国家实验室（Lawrence Berkeley Lab；美国最杰出的国家实验室之一）进行教学或研究工作。Alberto导师的研究聚焦应用数学与数学分析，多次应邀至世界各地知名学府发表主旨演讲。
