Join a Young & Ambitious Research Team!

I supervise students and early-career researchers working on theory-oriented mathematical optimization, data-driven decision-making, and applications in public health, sustainability, energy systems, artificial intelligence, and fairness. My supervision style is research-oriented and academically traditional: projects are designed to develop strong mathematical and computational skills and, where possible, to lead to peer-reviewed publications.

Over the years, I have supervised exceptional BSc, MSc, PhD students, postdoctoral researchers, and hosted academic visitors from across the UK, Germany, India, Turkey, China, and the US. Many student-led projects have resulted in publications in leading journals as well as international awards. Several students have continued into PhD study or research roles, analytics careers, and externally visible professional positions. Examples are listed on my Publications page and in the alumni section below.

Research Culture and Expectations

My research projects typically involve mathematical modeling, algorithm design, computation, repeated revision, and careful writing. Students who join should expect to work exceptionally hard, take ownership of their project, and develop the discipline needed for publishable research.

My supervision style is academically traditional and professional. I work closely with students on research, but I also maintain clear expectations, intellectual standards, and an appropriate professional distance between supervisor and student. This environment is best suited to students who are self-motivated and serious about developing as independent researchers.

Who Can Join

I welcome inquiries from students and early-career researchers at different stages of their academic development. Both in-person and remote options are possible. Suitable backgrounds include mathematics, operations research, computer science, statistics, business analytics, public health, energy systems, and related interdisciplinary fields. The common requirement is a strong quantitative ability and a serious research attitude. For research themes of my expertise, see my Research page

I expect a strong technical background, normally evidenced by excellent grades in relevant quantitative courses. More importantly, I look for students who are willing to work carefully, independently, and persistently on difficult problems. Good candidates usually have some combination of:

This is not intended as a light or casual project environment. It is best suited to students who want to be challenged and who are prepared to work seriously toward research-level outcomes.

PhD Students

If you are interested in pursuing a PhD in Operational Research with me at the University of Southampton, please apply directly through the University’s postgraduate research application portal. Prospective applicants are welcome to contact me before applying, but must include a CV, transcript, and a short description of their interests. Before writing, please look at my Research and Publications pages so that your message clearly explains the fit.

Postdoctoral Researchers and Visitors

I have previously hosted and worked with postdoctoral researchers through externally funded projects, including DFG-supported research on stochastic optimization for pandemic-resource allocation. That specific funding has now ended. Future postdoctoral opportunities will depend on new grants, project fit, or external fellowship routes. Strong candidates may also consider external funding schemes such as Commonwealth Scholarships, Marie Skłodowska-Curie Postdoctoral Fellowships, or other national and international funding routes.

Team & Alumni

My team members have come from a variety of interdisciplinary scientific backgrounds. The list below highlights recent and former team members, together with selected publications, awards, and research outcomes. You could be next!