Ph.D. Student Recruitment (Inactive for Now)
I am looking for motivated students to join my group in Spring 2024 or Fall 2024. The dissertation research will focus on developing data-driven solutions for smart manufacturing, especially high-resolution 3D printing. Statistical process monitoring, data mining, and machine learning will be intensively used in dissertation research. Specific topics may cover methodology innovation for manufacturing data processing and modeling, data-driven decision-making, interpretable or physics-informed machine learning, diagnostic and prognostics for advanced manufacturing processes. You are welcome to apply if you are passionate about data and interested in solving real-world decision-making challenges! Qualified candidates will be financially supported with full research assistantship.
Qualifications:
1. Meet the admission requirement for the Ph.D. Program:
Ph.D. in Manufacturing Engineering (Manufacturing Engineering, PhD - School of Manufacturing Systems and Networks (asu.edu))
2. Solid academic background in statistics, data analysis, and machine learning, e.g., undergraduate/graduate major in these areas, or have learned multiple courses related to the subjects.
3. Proficiency in coding (Python/R/MATLAB/C/C++/Java). Python is highly preferred. Linux experience is a plus.
4. Preferred major: electronic engineering, mechanical engineering, computer science, statistics, applied mathematics, financial mathematics. Both graduate and undergraduates are encouraged to apply, but having a graduate degree is a plus.
5. Self-motivation, persistence, curiosity for knowledge, and willingness to learn.
Contact: Shenghan.Guo@asu.edu
LinkedIn: (2) Shenghan Guo | LinkedIn
Volunteering Opportunities for ASU Students
I am looking for research volunteers to work with my PhD student and myself.
Description:
1. Video processing and analysis with Python/R/MATLAB/C++. Proficiency in Python is preferred.
2. Collaboration with my PhD student to help with data collection and selection.
3. 1~3 hours per week for Fall 2023. The schedule is flexible and adjustable per the progress.
Requirements:
1. Must be a current ASU student. Undergraduate and graduate students are both welcome.
2. Strong interest in data analytics and smart manufacturing.
3. Motivation in gaining research experience to enrich your resume.
Contact: send your resume to my email, Shenghan.Guo@asu.edu