5014 - Research and Development Methods for Engineers
Course Description
Research and development methods for engineers. Scientific literature searches using bibliometric tools such as Google Scholar and Web of Science. Introduction and significance of the Hirsh-Factor for measurement of scientific productivity. Issues of ethics and integrity including: plagiarism, text reuse, and data falsification; and real-world examples such as the Schon scandal case at Bell Labs. The establishment of the postwar American innovation system as proposed in “Science the Endless Frontier,” a report to the president by Vannevar Bush. An introduction to patent law and intellectual property as it applies to academic and industrial research. Not for CPE-MS, EE-MS, CPE-PhD, or EE-PhD credit. May be taken for CPE-MEng or EE-MEng credit.
Why take this course?
During the past 30 years we have witnessed dramatic advances in electronic communications, social media platforms, and advances in radical computing and ultra-powerful sensing. These advances have enabled engineers to radically increase the speed, complexity, and influence the generation of new knowledge and intellectual property development. In turn, these improved engineering processes are bringing to the market innovative products and new industrial applications. This course will help prepare graduate students for the profession of scientific and engineering research and enable them to appreciate the modern research and development ecosystem.
Learning Objectives
- Implement technical literature searches using modern bibliographic tools such as web-of-science, Google scholar and compute and interpret Hirsh-factors of individuals contributors and organizations.
- Produce a two-page IEEE conference paper, a referee’s report on a recent technical manuscript, and a three-page white paper to a funding agency.
- Evaluate issues of importance in professional ethics in research and development teams.
- Distinguish issues of plagiarism and its ramifications.
- Practice safe and legal use of scientific data arising from research and development projects.
- Analyze the development timelines and budgetary constraints in the execution of an engineering or research project.
- Appraise the importance of intellectual property and the prospect of patent opportunities in examples of academic and industrial research.
- Evaluate national research and development initiatives.