This interdisciplinary seminar will explore advanced analytical methods used in energy systems and climate change research (with emphasis on data science and systems models). Students will also learn about each step of the research process to achieve high impact in science and practice — including research design, data or model development and analysis, visualizing complex results, and writing for high-impact peer-reviewed journals. Students will have the opportunity to bring in related issues from their research and get extensive feedback.

The seminar will focus on interdisciplinary research for transforming energy systems* to align with European net-zero or global climate change goals that involves many aspects, including innovation, investment, finance, markets, business strategies, economics, public policy, behavior change, supply chains, geopolitics, etc. Addressing these complexities requires scholars to understand the systemic changes necessary to achieve meaningful emissions reductions and to communicate research findings with businesses, governments, and society.

*See below for an illustrative list of topics that fall within the scope of energy systems and climate change (see IPCC for an extended definition):

  • Energy supply and transformation (e.g., electricity, renewables, fossil fuels, low-carbon fuels, grid infrastructures)
  • Energy use (e.g., in transport, industry, buildings)
  • Energy demand and emissions (e.g., energy efficiency, carbon capture and utilization, carbon removal)
  • Technological change in energy systems (e.g., innovation, entrepreneurship, digitalization, manufacturing)

Learning outcomes

The students participating in this research seminar will develop a more advanced understanding of:

  • the interdisciplinary dimensions of energy systems and climate change research and analysis and key emerging questions for scholars and practitioners
  • a range of methodological approaches with foundations in systems models and data science that are used for energy systems and climate change analysis
  • critically engaging with academic material through reading, presenting, and discussing high-impact peer-reviewed publications
  • preparing visualization of data or complex modeling output for scientific publications that are also accessible to (and useful for) practitioners in business, government, and society
  • preparing research for high-impact journals in this area, by understanding expectations on scope, writing style, data and code, figures and visuals
  • giving and getting concrete and constructive feedback

The participants will also advance their own research through a concrete output (e.g., writing an extended abstract, new data or model visualization)

Attendance requirements

This is a discussion-based seminar with mutual feedback expected, hence attendance is required in all sessions. If you are sick, please email Prof. Surana.

Teaching/learning method(s)

This discussion-based course is based on preparatory readings, joint seminars, instructor input, and discussions with an interdisciplinary group of scholars.

Readings will be assigned from high-impact peer-reviewed journals and discussed collectively, with each participant (co)leading at least one discussion. The specific readings will be aligned to some extent with the collective research interests of the participants. External speakers or methodological experts may be invited.

The readings and discussion will be a foundation for advancing students’ research, where mutual feedback on scope, writing, methods, analysis and figures will be provided.

The course language is English.

  • Active participation in class and contributions to discussions (30%)
  • Team paper presentation (30%)
  • Individual assignment for advancing on your research (relative to the research progress shared at the beginning of the course) (30%)
  • Peer review (10%)

Prerequisites for participation and waiting lists

Background (or interest in) interdisciplinary and data-intensive approaches (e.g., systems models, integrated assessment models, data science, network science, complex systems) is expected, regardless of discipline or department. For students from other universities, consent from Prof. Surana is required. Please email


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Last edited: 2023-12-04