Yangming Lee Headshot

Yangming Lee

Assistant Professor

Department of Electrical and Computer Engineering Technology
College of Engineering Technology

585-475-4184
Office Hours
Tuesday and Thursday 4:00PM~6:00PM zoom link is posted on mycourses and syllabus.
Office Location

Yangming Lee

Assistant Professor

Department of Electrical and Computer Engineering Technology
College of Engineering Technology

Education

BS, MS, Hefei University of Technology (China); Ph.D., University of Science and Technology of China (China)

Bio

Assistant Professor

Department of Electrical and Computer Engineering Technology

Department BioMedical Engineering (affiliated)

Electrical and Computer Engineering Ph.D. Program(affiliated)

Golisano College of Computing and Information Sciences Ph.D. Program (affiliated)

Center for Imaging Science (affiliated)

585-475-4184

Select Scholarship

Published Conference Proceedings
Li, Yangming. "Soft-obstacle Avoidance for Redundant Manipulators with Recurrent Neural Network." Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Ed. none. Madrid, Spain: IEEE, Print.

Currently Teaching

CPET-121
3 Credits
This is the first course in a two-course sequence in computational problem solving of engineering and scientific problems. The problems solved will stress the application of sequence, selection, repetitive, invocation operations, and arrays. The development of proper testing procedures to ensure computational accuracy will be stressed. Students, upon successful completion of this course, will be able to analyze introductory engineering and scientific problems, design, code, test, and document procedural software solutions.
CPET-347
3 Credits
This course will introduce how intelligent robots use sensors to solve environmental perception problems. It takes visual sensors as an example to explain sensor data access and storage, to model and to calibrate sensors, to extract image information by scientific models, and to use deep neural networks to process image data. Laboratory exercises are designed to illustrate concepts and acquaint programming and problem solving skills. Projects are designed to integrate the skills and to develop the abilities of solving real-world intelligent robot perception problems.
CPET-371
1 - 3 Credits
Special Topics is an experimental lower-division course intended as a means for offering innovative topics not currently reflected in either the Computer or Electrical Engineering Technology curriculums
CPET-461
3 Credits
This course will provide students with an introduction to operating systems theory, and practical problem solving approaches to real-time systems. An embedded real-time operating system is used as the foundation for a variety of programming projects. Students, upon successful completion of this course, will be able to understand the operation and describe the various components of an operating system. They will be able to evaluate design trade-offs and selection criteria for different types of operating systems, and demonstrate the ability to write multiple process that run together within an embedded, real-time operating system.
EEET-116
1 Credits
This laboratory develops skills and practice in the construction, measurement and analysis of DC and introductory AC circuits. Standard laboratory equipment is introduced and utilized to measure resistance, voltage and current in basic and relatively complex circuit configurations. Measurements are employed extensively to verify Ohm's Law; Kirchoff’s Voltage and Kirchoff’s Current Laws and to demonstrate current and voltage division. Circuit simulation software is used throughout to support calculations and establish a baseline for comparison. Students collaborate within teams to research technology areas of curiosity, observe trends about the changing world and inform their peers via verbal presentations.
ENGT-510
0 Credits
This faculty directed undergraduate research experience involves student(s) in a research project. Under the guidance of CET faculty and using one or a variety of methods, students will collect data and contribute to problem solving within a research environment. As an undergraduate research experience, emphasis is on the process of scientific research, including problem definition, formulating a research plan, data collection/analysis and interpretation based on existing research. Department permission is required.
IMGS-890
1 - 6 Credits
Doctoral-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor.