Lingkang Jin's research focuses on developing multi-physics asset integration and energy systems modeling through mathematical programming with support of AI and Machine Learning tools to reduce computational burdens.

He is a postdoctoral researcher at Electrical Engineering department,  Electrical Energy Systems group, at Eindhoven University of Technology (TU/e).

Currently working on:

- Multi-physics based energy systems modeling

- Surrogate mode ( AI/ML) for the complex optimization models 

 - Power systems and energy systems planning and scheduling

Obtained a master’s degree in mechanical engineering  Cum Laude with thesis focused on a preliminary project on a offshore wind farm in the Mediterranea Sea.

Ph.D in Energy Systems at Università Politecnica delle Marche, Italy (UnivPM), with the thesis title “Energy storage in multi-energy carrier communities: Li-ion batteries and hydrogen multi-physical details for
integration into the planning stage”.

During the PhD period, secured two visiting periods, firstly six months in Technical University of Denmark (DTU) energy with key outputs having 1 journal and 2 conference publications, resulted as highly cited paper of the group, second in Eindhoven Unversity of Technology (TU/e) for three months having as the ouput a Journal publication in Applied Energy.

PhD thesis ranked as finalist among the best phd thesis 2024 in energy system domain for the italian energy system society. Finalist of the best paper award 2026 from the Postdoc association from TU/e.

Supervised 10 Msc thesis project as daily supervisor, Co-lecturer in 'Electricity Markets: Modeling and Optimization' course and Currently in the obtaining the University Teaching Qualification (UTQ)

Worked in both national and horizon europe projects as task leader involving both industry partners (Stedin, Enexis, DNV etc.) and academia (ENEA, TNO, DTU etc.) and supported in project proposals.

Currently having published over 12 journal publications (8 as first author) and more than 12 conference papers, serving as peer reviewer to journals from both IEEE and Elsevier

Nothing in life is to be feared, it is only to be understood. Now is the time to understand more, so that we may fear less. (Maria Skłodowska-Curie)