Join the lab
We welcome Ph.D., master's, and undergraduate students, remote collaborators, and research interns who want to combine rigorous methods with consequential problems in AI, operations research, transportation, logistics, and sustainability.
Who thrives here
You do not need to arrive with every technical skill in place. We value intellectual curiosity, reliability, kindness, and the willingness to learn. Strong candidates enjoy moving between mathematical ideas, computational experiments, and the real systems that motivate the work.
We are especially interested in students who want to explore:
- Learning-augmented and generative-AI methods for optimization
- Sequential decision-making and reinforcement learning
- Transportation, urban mobility, logistics, and supply-chain systems
- Sustainable AI and life-cycle assessment
- Responsible deployment of data-driven decision systems
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Ph.D. students
Work toward independent research contributions while building depth in optimization, machine learning, data analysis, and domain knowledge.
How to apply: follow the two-step process below. An email does not replace the interest form or the official USC application.
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Master's students
Contribute through thesis research, independent study, or focused projects, depending on preparation, interests, and availability.
Helpful preparation: coursework or experience in optimization, probability, statistics, programming, or machine learning.
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Undergraduates
Start with a well-scoped project and grow toward independent work. Prior research experience is welcome but not required.
What matters most: steady time commitment, curiosity, and comfort asking questions.
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Remote researchers
Students who are not local may be considered for clearly scoped remote projects that suit online collaboration.
A strong fit: dependable communication, independent progress, and enough time-zone overlap for regular meetings.
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Research interns
Intensive, project-based internships may be available during the academic year or summer.
When you write: include preferred dates, duration, location, and whether you seek academic credit or financial support.
Applying for the Ph.D.
Applications are open for Spring and Fall 2027. Qualified students receive full funding covering a stipend and tuition. Students apply to the Mechanical Engineering Ph.D. program and pursue industrial-engineering research.
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Complete the lab interest form
Submit the prospective graduate student interest form with:
- CV or résumé
- Unofficial transcript(s)
- A research-interest statement of no more than one page
- Contact information for three references (letters are requested from finalists)
- Optional links to publications, code, or a portfolio
Shortlisted candidates are invited to a virtual or in-person interview. Questions can go to zyin at sc dot edu with the subject “Prospective PhD student”.
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Submit the official USC application if selected
Candidates selected in the lab's preliminary review also apply through the USC portal and submit every document the Mechanical Engineering Ph.D. program requires.
Mechanical Engineering Ph.D. requirements
USC Graduate School application
Application deadlines
Spring 2027: September 20, 2026 (international); October 5, 2026 (domestic).
Fall 2027: January 1, 2027 (international); January 15, 2027 (domestic).
Master's, undergraduate, remote, and internship inquiries
Email zyin at sc dot edu with the subject “Prospective Opportunity — [Master's / Undergraduate / Remote / Internship] — [Your Name]” and attach:
- Your CV
- A short research statement covering your interests, relevant preparation, and why you would like to work with our lab
In the email, briefly introduce yourself and name the opportunity you are seeking. For remote projects or internships, also include your location, availability, preferred dates, and expected duration.
A note on admissions
Admission decisions and degree requirements are governed by the university and program. A conversation with the lab or an interest-form submission does not guarantee admission, funding, academic credit, an internship, or a research position. Opportunities depend on program eligibility, university and employment rules, project fit, mentoring capacity, and available support.