学院新闻
美国南卡罗来纳大学博士招生信息
国南卡罗来纳大学（University of South Carolina）博士招生信息
美国南卡罗来纳大学电气工程系BIN ZHANG招收博士研究生。感兴趣的同学可以联系BIN ZHANG博士，University of South Carolina学校、院系及招生教师的基本信息附后。
Ph.D. Openings
I am seeking 1-2 exceptionally qualified Ph.D. students for the upcoming admissions (Fall 2015).
The research will focus on the development of fault diagnostics, failure prognostics, and health management algorithms, hardware, and software. This will involve studies of measurement, modeling, robots, estimation, prediction, multi-agent systems, control, etc.
Students with master degree and previous research experience in related areas are especially welcomed.
Please contact via telephone and email if you are interested and have any questions
Application Information
http://www.sc.edu/study/colleges_schools/engineering_and_computing/apply/graduate/index.php
http://www.sc.edu/study/colleges_schools/engineering_and_computing/apply/assistantships/
南卡罗来纳大学（University of South Carolina）
South Carolina’s Flagship University, founded in 1801.
Located in historic campus at Columbia, SC.
One of 35 public universities to be named a top research university by the Carnegie Foundation
College of Engineering and Computing
160 faculty are leaders in their fields.
Offers students many opportunities to participate in cutting edge research.
Electrical Engineering
Offers bachelor’s, masters and doctoral programs
Ranked No. 6 nationally and No. 1 in the south for faculty research productivity
Ranked No. 7 nationally and No. 1 in the south for program quality
Research on Energy & Control; Communications; Photonics & Microelectronis; and Decision & Control
Bin Zhang，Department of Electrical Engineering，University of South Carolina，Tel: 803-777-8335
Email: zhangbin@cec.sc.edu
Research Interests
Prognostics and Health Management: fault diagnosis, failure prognosis, condition-based maintenance, and fault-tolerance.
Intelligent Systems: adaptive systems, diagnosis and prognosis enhanced systems, real-time approximation and learning systems, predication and estimation, and system reconfiguration.
Distributed Systems: collaboration of multi-agent system in which one or more agents have failing component to achieve optimal and adaptive mission allocation.
