1. Overviews of wireless communication systems 2. Modular communication systems and protocol design 3. Eexperiment and algorithm development in IEEE 802.15.4 platform 4. Network and MAC protocol designs for personal and local area networks 5. Mathematical modeling for communication systems and protocols 4. Physical and MAC protocol designs for mobile and wide area networks 7. Cross layer design and optimization for emerging wireless communication systems This course aims at in-depth discussion of wireless communication systems and their protocols. We will focus on the design rationales of communication protocols, the overall network architectures and performance evaluation of complicated wireless systems so that students will be capable of designing next-generation communications systems through rigorous simulation and mathematical analysis. In addition, we will for the first time introduce the IEEE 802.15.4 experiment test bed for hands-on experiments. Studets will learn from the real hands-on experiment the design of wireless protocols and thus to develop new applications in wireless networking. College of Electrical Engineering & Computer Science 1. Probability and Statistics 2. Introduction to Computer Networks 3. C/C++ programming CHUNI-TING CHOU Tuesday 234 CommE5039 3

Logic synthesis is an automated process of generating logic circuits satisfying certain Boolean constraints and/or transforming logic circuits with respect to optimization objectives. It is an essential step in the design automation of VLSI systems and is crucial in extending the scalability of formal verification tools. This course introduces classic logic synthesis problems and solutions as well as some recent developments. This course is intended to introduce Boolean algebra, Boolean function representation and manipulation, logic circuit optimization, circuit timing analysis, formal verification, and other topics. The students may learn useful Boolean reasoning techniques for various applications even beyond logic synthesis. College of Electrical Engineering & Computer Science The prerequisite is the undergrad “Logic Design” course. Knowledge about data structures and programming would be helpful. JIE-HONG JIANG Friday 234 EEE5028 3

Data is at the center of the so-called fourth paradigm of scientific research that will spawn new sciences useful to the society. Data is also the new and extremely strong driving force behind many present-day applications, such as smart city, manufacturing informatics, and societal security, to name a few. It is thus imperative that our students know how to handle data, analyze data, use data and draw insights from data. This course aims at acquainting the students with the analytical foundation of data handling techniques. The course consists of a series of seminar talks with substantial student participation, in the form of research and presentation in response to posted questions about main topics in data analytics and modeling. 1. Scope Broad topics covered in the course include: •Regression & curve fitting •Probability distribution & parameter estimation •Mixture models, latent variable models & hybrid distributions •Hidden Markov models, Markov random fields, & graphic models •Pattern recognition & decision theory •Neural networks and deep learning Well spend 2-3 weeks on each topic (some may take up to 4 weeks). 2. Format For each topic, a number of questions to help students learn the subject will be posted in advance. Individual student will be assigned to conduct research, answer specific questions and return with presentations to the class. Each student presentation is of duration ~20 min, followed by ~10 min questions and discussion. Students who are assigned to address specific questions have one week time to prepare for the presentation. Common questions shared by all topics are: – What are the problems that gave rise to the particular topic & concept? (The original motivation) – What problems beyond the original motivation will the topic and the related techniques be able to solve? (New and novel applications) – What are the problem formulations with relevant assumptions that have been proposed? (The methodology and formulation) – What are the ensemble of techniques that were developed to solve the problem? (The tools and capabilities) – How do these techniques solve the problem or contribute to the solutions? (The solution mechanism) – What are the limitations of the solutions proposed so far? Any remaining open problems in the topic? (Research opportunities) In addition to these common questions, some topic-specific questions may also be posted and addressed in student presentations. After all posted questions about a subject are addressed in student presentations, one or two commentary sessions by the lecturer on the subject will follow so as to complete the systematic development of understanding of the subject. The course will be primarily conducted in English. To reflect the applicability of the subject matter to local problems, local languages may also be used as the circumstance calls for it. No official textbook is assigned in this course. Students are expected to conduct research with all university provided resources (e.g., books in the library) and information available on the web. Class notes by the lecturer will be distributed in due course. 3. Prerequisite Both graduate and undergraduate students can enroll in the class, as long as they have completed engineering mathematics courses, particularly Probability and Statistics or the equivalent. Overall, students will be exposed to data analytic topics and their historical perspectives, learn to ask and analyze related problems, understand the modeling techniques and their origins, and conceive of new applications and research opportunities. College of Electrical Engineering & Computer Science No written test will be given in the special course. Student presentations are evaluated by the class and moderated by the lecturer. JUANG BIING-HWANG Thursday 234 CSIE5610 3

This course is designed to guide students to learn about dissolved organic matter in marine environment. Quantitatively, marine dissolved organic matter (DOM) contains a large amount of fixed carbon (660 Pg C) that is approaching the amount of carbon in the atmospheric CO2 (750 Pg C). In the past few decades, our understanding of DOM in the marine environment has greatly advanced due to several breakthroughs in analytical techniques and combining with molecular approaches. While the interactions between DOM and hydrothermal activities are still not well studies, this will be an open field for students. Through this course, I’ll introduce a few current research directions that scientists/oceanographers use to reveal the mysterious marine DOM in hydrothermal systems. The class starts by having each student to present why they are coming to this course. In particular, students will share the connection between DOM to their research topics and their most interested topics. The purpose is to custom-made the course to better meet students’ need. Each week, the course will start by me giving a brief introduction of the topic. We will then spend 40 mins discussing recently published research papers relevant to the topic and another 30-40 mins to compile the data from the published research papers, free online resources such as Earth Cube and combine with your own research data if available. We will then make our own data analysis and interpretations. College of Science his course will be offered in English and thus, students must be able to understand English well enough to enroll. Students are required to read and present in English. This is a reading intensive course. Students are required to attend ALL classes. No more than two unexcused absences are permitted. HUEI-TING LIN Thursday 67 Ocean7174 2

This course provides the introduction to Industrial Organization, including the study of the market structure and the theory of the firm. The focus will be on some basic theoretical models and related empirical studies in IO. 先修科目 Prerequisites 1. Microeconomics I and II (ECON 2001, 2002) 2. Statistics and Econometrics I and II (ECON 2014, 2015) College of Social Sciences Week 1: Introduction and Cost Theory. Week 2: Perfect Competition and Monopoly. Week 3-4: Oligopolistic Competition. Week 5: Cartels and Collusion Week 6-7: Product Differentiation Week 8: Entry, Accommodation, and Exit Week 9: Midterm Week 10: Entry Deterrence Week 11-12: Price Discrimination Week 13: Vertical Integration Week 14: Regulation of A Monopoly Week 15: Advertising Week 16: Search and Price Dispersion Week 17: Auctions Week 18: Presentations (or Final Exam) [to be announced in the syllabus] problem Sets (30%) Midterm (30%) Final Exam (or Term Papers) (40%) [to be announced in the syllabus] JIANDA ZHU Friday 234 ECON5127 3

The continuous developments in genomics, proteomics and metabomics will help to drive the uses of micro/nano sensor technologies for personalized medicine or companion medicine. This course aims to provide the necessary background knowledge for multi-disciplinary students on both sides of medical applications and engineering approaches. Prepare students for multi-disciplinary natures of micro-sensors and systems and drive for innovative approaches for medical applications. College of Engineering General background in Physics, Chemistry, Engineering mathematics. Finish reading assignments before each class and participate in active discussion. CHENG-HUNG, WU Friday 678 IE5038 3

The course requires students’ teamwork to accomplish projects of topics in response to current crop production inquires based on their accumulated knowledge taught in other courses. After taking this course, the students will have a better understanding about the current status of agriculture industries and will be better equipped with problem-solving skills. The possible project topics include (1) crop production and management, (2) crop physiology and biotechnology, (3) genetics and molecular breeding, and (4) biometrics and bioinformatics. College of Engineering The students will be grouped into teams to plan and implement the project together under instructors’ supervision. There are three progress checkpoints throughout the semester and the team members have to present their results at the end of the semester. Evaluations on the progress at three checkpoints _ 20% each; evaluations on the final project _ 40%. FENG-HUEI LIN Monday 789 Biomed5002 3

Organizers Dr. Hsou-min Li College of Medicine 1. A two-hour exam will be conducted in a close-book and in-class format for both the mid-term and final exams. Some instructors may also use in-class quits or homework for grading. 2. Each lecture will weight the same in your final grade. 3. Students with a final grade ? 70 are regarded as “pass”. Students who fail the course cannot be granted the course credits and should retake the course if the course required by their program. SHU-CHUN TENG Monday 34 Thursday 78 PTMP8015 4

The Stem Cell Biology Course is primarily consisted of a series of lectures which covers from basics of the general biology of stem cells to a more in-depth discussion on various stem cell types: embryonic stem cells, adult somatic stem cells and cancer stem cells, and finally to some of their potential clinical application/implication. For evaluation, students are required to write a review essay on designated research topics so that they can horn their skills in the search, organization and critical assessment of literatures. College of Medicine (i) A written essay on a selected topics 40 % (ii) A short presentation on a selected topics (10 min) 40% (ii) Attendance 20 % SHU-CHUN TENG Thursday 789 PTMP8025 3

THIS COURSE WILL PRESENT AN INTRODUCTION TO PROCESS DYNAMICS AND CONTROL. STUDENTS WILL LEARN HOW TO CONSTRUCT DYNAMIC MODELS OF PROCESS SYSTEMS, HOW TO ANALYZE PROCESS DYNAMICS USING LAPLACE TRANSFORMS AND TRANSFER FUNCTIONS, THE CHARACTERISTIC RESPONSES OF DYNAMIC PROCESSES, AND THE DESIGN AND IMPLEMENTATION OF FEEDBACK CONTROL. STUDENTS WILL ALSO LEARN TO USE COMPUTER SOFTWARE TO MODEL PROCESS DYNAMICS AND CONTROL. College of Engineering Jeffrey Daniel Ward Monday 2 Wednesday 34 ChemE4007 3

This course is about the econometric analysis of financial time series. We will cover some popular and useful methods and their empirical applications. These methods include ARIMA processes, GARCH models, stochastic volatility models, and continuous-time models. If time is allowed, we will also look at copula methods and their applications in finance. College of Management First priority: Master or PhD studnents in Finance CHUNG-MING KUAN Monday 789 Fin8036 3

Classroom: IBMS TIGP classroom (8F, New Building) Coordinator:徐志文 College of Medicine SHU-CHUN TENG Tuesday 67 PTMP8011 2