博士申请 | 弗吉尼亚理工大学金然教授招收数据科学方向全奖博士生

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弗吉尼亚理工大学

导师简介

Dr. Ran Jin is an Associate Professor and the Director of Laboratory of Data Science and Visualization at the Grado Department of Industrial and Systems Engineering at Virginia Tech. He received his Ph.D. degree in Industrial Engineering from Georgia Tech, Atlanta, his Master’s degrees in Industrial Engineering, and in Statistics, both from the University of Michigan, Ann Arbor, and his bachelor’s degree in Electronic Engineering from Tsinghua University, Beijing. His research focuses on supervised learning and computation services in smart manufacturing and human-centric Artificial Intelligence (AI). His research includes lightweight middleware design in Industrial Internet, machine learning pipelines and deep neural networks in manufacturing, data fusion modeling, interface between data quality and data-driven modeling, cognitive visualization system design, and interpretable AI models. His research outcomes have been broadly applied in additive manufacturing, thermal spray coating, broaching, semiconductor, printed electronics, optical fiber, and continuous fiber manufacturing industries.

Dr. Jin is currently serving as an Associate Editor for IISE Transactions (Design and Manufacturing), Associate Editor for ASME Journal of Manufacturing Science and Engineering, Associate Editor for IEEE Transactions on Automation Science and Engineering, and Associate Editor for INFORMS Journal on Data Science. He is a member of IEEE Standard P21451-1-6 Working Group (MQTT). He is also serving as Co-Chair of Commission on Research of Virginia Tech and the Operations Officer of Virginia Tech Faculty Senate. He served as Chair of Quality, Statistics and Reliability (QSR) Subdivision in INFORMS (2018-2019) and President of Engineering Faculty Organization at Virginia Tech (2019-2021) before.

个人主页：

https://www.ise.vt.edu/people/faculty/jin.html

招生信息

Dr. Ran Jin at the Grado Department of Industrial and Systems Engineering at Virginia Tech plans to provide financial support to 1-2 doctoral students starting in Fall 2024.

研究方向

The students will investigate a few critical research questions in the area of Manufacturing Industrial Internet and human-centric data science, including but not limited to:

1. Interface between data quality and data-driven modeling

2. Computation services and middleware design in Industrial Internet

3. Data fusion modeling and decision making

4. Cognitive visualization system design, and

5. Interpretable data-driven models

Specific research topics will be identified by students’ interest, with consultation with the faculty advisor.

关于奖学金

Financial support will be provided to the students and is expected to support the students obtaining their Ph.D. degrees, if the academic progress is satisfactory. Financial support will be provided in either research assistantship, or teaching assistantship, or the combination of the two forms. Fellowships are also available, subject to the qualifications of the candidates. Research or teaching assistantship includes a monthly stipend of $2,500 or higher, with tuition coverage. Actual stipends may vary.

招生要求

Candidates should have Bachelor of Engineering/Science or equivalent degree in relevant science and engineering majors, such as Industrial Engineering, Computer Science, Electronic Engineering, Automation, Statistics and Mathematics, and Mechanical Engineering. A graduate degree is considered a plus but not required.

We are looking for outstanding candidates with the following preferred skills:

1. solid mathematical and engineering background;

2. computer programming skills, such as using Python, Java, or Matlab;

3. proficient English skills in both oral and written communications; the testing scores, such as TOEFL and GRE, if required, should satisfy the minimal requirements by Virginia Tech.

申请方式

Application will be accepted and reviewed from now until the positions are filled. Early application is strongly encouraged. Please contact Dr. Ran Jin at jran5@vt.edu before the application. Please go through the formal application process by university. For detailed information, please visit https://www.ise.vt.edu/academics/graduate/phd.html

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