Lingkang Jin, Ph.D.
Energy Systems Researcher | Optimization modeler | Data Scientist
Lingkang is a Postdoctoral Researcher in the Department of Electrical Engineering at Eindhoven University of Technology (TU/e), The Netherlands.
His 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 and enhance scenario generation.
News and updates 📈
2026
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09 October: ORKEST Demo event for the Q3 2026 for the ORKEST results dissemination, Stedin Utrecht office - 02–04 September: Speaker at the Nordic energy Informatic conference 2026, Reykjavik, Iceland
- 03 July: ORKEST Demo event for the Q2 2026 in Stedin Utrecht office for the ORKEST results dissemination
- 15 June: 3 minutes Pitch as finalist for the best paper award from Postdoc Association TU/e
- 10 June: Presenter at the Eurotech stand (18) at the EUSEW energy fair 2026
- 22 May: Invited presentation on surrogate modeling in power systems, at IE&Information Systems, invited by Dr. Laurens Bliek
- 26 Apr–10 May: Eurotech visiting in DTU Wind and Energy Systems, Denmark hosted by Dr. Haris Ziras
- 01 April: Joined Horizon Europe Erasmus Project-SG: SKILL as TU/e representative and involved in WP2 and WP3
2025
- 15 June: Joined the ORKEST project as R4 leader
Show older news and updates...
2024
- 30 March: PhD defense with thesis: Energy storage in multi-energy carrier communities: Li-ion batteries and hydrogen multi-physical details for integration into the planning stage
- 15 January: Started the postdoc researcher position working in NO-GIZMOS project as main TU/e responsible researcher
2023
- March–May: Visiting PhD at Eindhoven University of Technology EES group under supervision of Dr. Christina Papadimitriou
2022
- March–September: Visiting PhD at Technical University of Denmark, DTU energy, CMT section under supervision of Prof. Henrik Lund Frandsen and collaboration with Prof. Rafael Nogueira Nakashima
2020
- October: Started PhD in industrial engineering with specialization in energy systems, at Università Politecnica delle Marche under supervision of Prof. Gabriele Comodi
Research Framework 🧩
Components
(Power to H2)
... etc.
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Physic-based layer
... etc.
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System decisions/policy
scheduling
... etc.
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AI-support layer
speed up
scenarios generation
... etc.
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ML/AI tools
optimization models
Neural Network
... etc.
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Multi-physic AI supported System Level Energy System Modeling
