/filters:quality(90)/prod01/production-cdn-pxl/media/umassdartmouth/profiles/engineering/Yuchou-CHANG-22.jpg?text=945+WebP)
faculty
Yuchou Chang, PhD
Assistant Professor
Computer & Information Science
Contact
508-999-8475
xbg`mf0?tl`rrc-dct
Dion 317B
Education
| 2012 | University of Wisconsin-Milwaukee | PhD |
| 2006 | Shanghai Jiao Tong University | ME |
| 2003 | Northwestern Polytechnical University | BE |
Teaching
Programs
Programs
- Computer Science BS, BS/MS
- Computer Science Cybersecurity
- Computer Science MS
- Data Science BS, BS/MS
- Data Science Graduate Certificate
- Data Science MS
- Engineering and Applied Science PhD
Teaching
Courses
Artificial intelligence problem-solving paradigms. The course covers heuristic versus algorithmic methods, rational and heuristic approaches, and description of cognitive processes; and objectives of work in artificial intelligence, the mid-brain problem and nature of intelligence, simulation of cognitive behavior, and self-organizing systems. Examples are given of representative applications.
Theories and models in visual analytics. Visual analytics covers cognitive theories, advanced computational models and usable visual interface for sensemaking of data. This course is intended for graduate students interested in using visualizations for data analytics in their own work, or students interested in building visual analytics tools.
Prerequisites: Completion of three core courses. Development of a detailed, significant project in computer science under the close supervision of a faculty member, perhaps as one member of a student team. This project may be a software implementation, a design effort, or a theoretical or practical written analysis. Project report with optional oral presentation must be evaluated by three faculty members including the project supervisor.
Prerequisites: Completion of three core courses. Development of a detailed, significant project in computer science under the close supervision of a faculty member, perhaps as one member of a student team. This project may be a software implementation, a design effort, or a theoretical or practical written analysis. Project report with optional oral presentation must be evaluated by three faculty members including the project supervisor.
Prerequisite: Completion of three core courses. Research leading to submission of a formal thesis. This course provides a thesis experience, which offers a student the opportunity to work on a comprehensive research topic in the area of computer science in a scientific manner. Topic to be agreed in consultation with a supervisor. A written thesis must be completed in accordance with the rules of the Graduate School and the College of Engineering. Graded A-F.
A team-based learning experience that gives students the opportunity to synthesize prerequisite course material and to conduct real-world analytics projects using large data sets of diverse types and sources. Students work in independent teams to design, implement, and evaluate an appropriate data integration, analysis, and display system. Oral and written reports and ethical aspects are highlighted.
A team-based learning experience that gives students the opportunity to synthesize prerequisite course material and to conduct real-world analytics projects using large data sets of diverse types and sources. Students work in independent teams to design, implement, and evaluate an appropriate data integration, analysis, and display system. Oral and written reports and ethical aspects are highlighted.
Written presentation of an original research topic in Data Science which demonstrates the knowledge & capability to conduct independent research. The thesis shall be completed under the supervision of a faculty advisor. An oral examination in defense is required.
Research investigations of a fundamental and/or applied nature defining a topic area and preliminary results for the dissertation proposal undertaken before the student has qualified for EAS 701. With approval of the student's graduate committee, up to 15 credits of EAS 601 may be applied to the 30 credit requirement for dissertation research.
Investigations of a fundamental and/or applied nature representing an original contribution to the scholarly research literature of the field. PhD dissertations are often published in refereed journals or presented at major conferences. A written dissertation must be completed in accordance with the rules of the Graduate School and the College of Engineering. Admission to the course is based on successful completion of the PhD comprehensive examination and submission of a formal proposal endorsed by the student's graduate committee and submitted to the EAS Graduate Program Director.
Teaching
Online and Continuing Education Courses
Expert system architectures: forward-production, logic programming, deductive retrieval, and semantic network systems. The course also treats natural language systems, illustrative working systems, and AI programming.
Research
Research awards
- $ 20,000 awarded by Office of Naval Research for Tiny ML-UUVs: Tiny Machine Learning for Low-Power Unmanned Undersea Vehicles
Research
Research interests
- Artificial Intelligence / Machine Learning / Pattern Recognition
- Biomedical Imaging
- Intelligent Robotics
- Brain-Computer Interface
- Statistical Signal Processing