Below you will find a list of courses offered by each research center at TBSI. Courses are co-taught by UC Berkeley and Tsinghua faculty members at the TBSI-Shenzhen campus.
Low Carbon Economics and Technologies
Instructors: Feiyu Kang, Max Shen, Hongbin Sun, Junqiao Wu
Overview: This course is an introduction to the applications of operations research techniques, e.g., probability, statistics, and optimization, to finance and financial engineering. No previous knowledge of finance is required. The course first reviews basic concepts of financial markets including risk, no-arbitrage pricing and option pricing, as well as core techniques in portfolio management such as mean-variance and VAR. The second part of the course will be a project on derivatives in the energy market. MATLAB and S-Plus will be used for computation.
ITS & High-Accuracy Positioning Technologies
Instructors: Lixin Miao, Kai Zhang
Overview: The course will introduce common knowledge and the latest development of high-accuracy positioning in ITS. The course will cover the architecture and technologies of highly accurate positioning, including Global Navigation Satellite System, Inertial Navigation, Map Matching, and Optimal State Estimation Theories. During the course, students will practice programming robot positioning to help them master the theories.
Advanced Managerial Economics
Instructors: Ying Kong
Overview: Managerial economics provides a systematic and logical analysis method for business decision-making . The management decisions not only affects day-to-day decisions, but also affects the economic force of long-term planning and decision-making and microeconomics in the practice of management. It is the bridge for communication theory of economics and business management decision-making for enterprise decision-making and management. It provides analysis tools and methods, and the theory is mainly around demand, proposed several production, cost, market and other factors. Students will learn how to analyze and compare the alternatives of management economics, and discover the most likely solutions for the enterprise target. In this decision process, the function of management economics is to provide related analysis tools and analysis methods.
Thermal Physics and Engineering
Instructor: Junqiao Wu
Overview: This course focuses on concepts and frontier research trends of low carbon economics and low carbon technologies, such as new energy, nanomaterials, environmental engineering, smart grid and intelligent transportation systems. Each professor will give a 3 hour lecture by means of introduction and discussion about the frontier technologies in the related fields.
Introduction of Smart Grid
Instructors: Hongbin Sun, Liming Wang, Wenchuan Wu, Qinglai Guo
Overview: The course introduces emerging and developing concepts in smart grid technologies. Students will understand the motivation, definition, features, key technologies and typical cases of smart grids. Primary topics in smart grids, including the source side (such as renewable energy sources and distributed generation), the grid side (such as advanced transmission grid, active distribution grid, micro grid), the demand side (such as electric vehicles, demand response, smart buildings), and information & communication technologies (such as energy management and cyber physical systems) will be presented.
Introduction to Financial Engineering
Instructor: Xin Guo
Overview: This course is an introduction to the applications of operations research techniques, e.g., probability, statistics, optimization, and financial engineering. No previous knowledge of finance is required. The course first reviews basic concepts of financial markets including risk, no-arbitrage pricing and option pricing, as well as core techniques in portfolio management such as mean-variance and VAR. The second part of the course will be a project on derivatives in the energy market. MATLAB and S-Plus will be used for computation.
Introduction to Stochastic Processes
Instructor: Xin Guo
Overview: The course begins with a basic review of probability concepts and will cover conditional probability and expectation, Markov chains, exponential distribution and Poisson processes. If time permits, renewal theory and continuous time Markov chain will be discussed. Knowledge of one semester of basic probability course is highly recommended.
Dynamics of Environmental Systems: Principles of Mass Transformation and Energy Flow
Instructors: Xihui Zhang, Hongying Hu, Guanxue Wu, Bing Li
Overview: The course will introduce common knowledge of mass transformation and energy flow in environmental systems, especially for the latest development in the fields of separation and purification, chemical treatment processes and biological treatment processes, as well as its inter-relations with the natural environment, massive energy production and dissipation. In addition, the control and management of environmental processes will be presented through the viewpoints of sustainability and low carbon concepts.
Data Science and Information Technology
Instructors: Wenwu Zhu, Connie Chang-Hasnain, Lin Zhang, Liwei Lin
Overview: This seminar-based course will cover the development and frontier of data science and information technology. The course will cover the topics including nanodevices, sensors and Microsystems, information theory, society cyber physical systems, and data analytics, application of big data, big data systems, relationship between data ethics and technology, data-driven design, etc.
Fundamentals of Applied Information Theory
Instructor: Lin Zhang
Overview: This course is based on three Shannon theorems in information theory and introduces the statistical method, information processing and theoretical issues involved in the information measurement. The course will help students to master the basic concepts of information theory, and understand the theory and methods of information processing, transmission, storage and compression. It is helpful for the in-depth understanding of some essential issues in information and communication engineering and improvement of the innovative thinking and analysis in practical problems.
Hot Topics in Computational Photography
Instructor: Qionghai Dai
Overview: Computational photography is a new interdisciplinary field emerging at the beginning of this century that combines digital signal processing, computer vision, graphics, and optics. This course is suitable for graduate students of different majors. This course contains 32 class hours in total. We will first introduce the history and basic theory of computational photography, and then discuss the research hot topics, including the field of view, resolution, dynamic range, spectral, and depth. Students will develop understanding for international hot topics and trends, learn research methodology in this field, and prepare for further research and development.
Next-Generation of Internet and Web
Instructors: Yong Jiang, Jianping Wu
Overview: The objective of the course is to give an introduction to a new cross-disciplinary field, Web Science, so that the students can achieve the following goals: 1. To gain a better understanding of the Internet/Web and people on it; 2. To engineer the future of the Internet/Web via new emerging technologies; 3. To guarantee its social benefits including economic, legal and governmental considerations. Lectures include Web Science overview, Web modeling, social network, web mining, Semantic Web framework and technologies, wikinomics, privacy protection, and Gov 2.0.
Foundations for Big Data Analytics
Instructors: Wenwu Zhu, Jean Walrand, Kaiping Peng, Zhi Wang
Overview: Commerce and research are being transformed by data-driven discovery and prediction. Skills required for data analytics at massive levels – scalable data management on and off the cloud, parallel algorithms, statistical modeling, and proficiency with a complex ecosystem of tools and platforms – span a variety of disciplines and are not easy to obtain through conventional curricula. The course will be focused on the basis of statistics, data analytics, big-data systems and big-data applications.
Instructors: Xiaohao Wang, Liwei Lin, Ying Dong
Overview: The class hours will be assigned to lectures, seminars, flipped classrooms and lab experiments. The purpose of this course is to enable the students to fully understand the working principles and realization method of microsensors, so as to acquire the basic knowledge and ability for the research, development and application of microsensors. In the beginning, the relative theories of microsensors will be introduced in the form of lectures, including the mechanical properties of the microstructures and the principles of signal detection. Using several typical microsensors as examples through case studies, seminar discussions, flipped classrooms and lab experiments, the complete process of the design, fabrication, packaging and performance testing of microsensors can be practiced by the students.
Nanoscale Fabrication and Optoelectronic Devices
Instructor: Connie Chang-Hasnain
Overview: Two hours of lecture and one hour of discussion per week. This course discusses various top-down and bottom-up approaches to synthesizing and processing nanostructured materials. The topics include fundamentals of self assembly, nano-imprint lithography, electron beam lithography, nanowire and nanotube synthesis, quantum dot synthesis (strain patterned and colloidal), postsynthesis modification (oxidation, doping, diffusion, surface interactions, and etching techniques). In addition, techniques to bridging length scales such as heterogeneous integration will be discussed. We will discuss new electronic, optical, thermal, mechanical, and chemical properties brought forth by the very small sizes.
Introduction to Computer-Aided Tissue Engineering
Instructors: Wei Sun, Shengli Mi
Overview: Introduction to Computer-Aided Tissue Engineering (CATE) is designed for graduate and senior undergraduate students in engineering and bioengineering majors who are interested in acquiring the knowledge and skills in utilizing computer-aided technologies for tissue engineering applications. The course will introduce: 1) engineering and bioengineering aspects of tissue regeneration; 2) basics of computer-aided design, computer-aided engineering, and computer-aided manufacturing (CAD/CAM/CAE); 3) knowledge on the use of integrated CAD/CAE/CAM technology in tissue engineering applications; and 4) hands-on experience using enabling CAD, medical imaging processing and three-dimensional reconstruction software, and 3D Printing technology for tissue scaffold design, modeling, simulation, and freeform fabrication.
Instructors: Yongzhang Luo
Overview： Angiogenesis mainly refers to the physiological process through which new blood vessels form from pre-existing vessels. Angiogenesis is a crucial step in tumor progression. In addition, it also plays an important role in macular degeneration and other diseases. Tumor angiogenesis mechanism is currently a hot field in tumor biology. Inhibition of tumor angiogenesis has become an important means of treating cancer. This course mainly focuses on the following aspects: (1) angiogenesis conditions and processes; (2) a variety of factors which induce angiogenesis and their molecular mechanisms; (3) angiogenesis function in human diseases; (4) the mechanism of angiogenesis inhibitors and their applications in the treatment of cancer.
Introduction of Biophotonics
Instructors: Hui Ma, Gerard Marriott, Luke Lee, Seung Wuk Lee
Overview: Introduction of biophotonics is a multidisciplinary course which can serve as a mandatory core course for graduate students in life sciences, or an elective course for those from other related majors such information technology and manufacturing. The course includes brief introductions to the basic physics for photon-matter interactions and the corresponding physics observables, different biophotonics sensing and imaging techniques that retrieve these observables and disentangle the encoded information on the structure and dynamics of the biological system, and typical applications of these techniques in both biomedical and other related fields. The course includes laboratory practice that allows the students to know essential hardware modules and data processing techniques of biophotonics imaging and sensing apparatus, such as light sources, optical components, detectors, data processor and displays. The students will be prepared to incorporate into their own work the latest technological advances in optics and related fields, such as cloud computing and big data.
Design and Application of Detection and Imaging Platforms for Disease Monitoring and Diagnosis
Instructors: Yongzhang Luo, Hui Ma, Gerard Marriott, Ting Xu
Overview: The seminars introduce students to cutting edge research and technology in the field of cancer diagnostics and Theranostics, including principles and concepts in cancer biology, the origin and discovery of cancer biomarkers, the principles and practices of biomarker detection (optical, PET, MRI), the design of drug targeting and delivery vehicles and their applications in the detection, diagnosis and treatment of human cancer.