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Danila Valko

Ph.D., M.Sc. in Economics
M.Sc. in Computer Science
^{danila.valko@proton.me}

̇ ̇ ̇ ̇

My research lies at the intersection of behavioural science, sustainability, sustainable development, energy systems research, and modern computational and simulation methods. I am interested in understanding how people, policymakers, and sociotechnical systems perceive, respond to, and adopt sustainability solutions, and how these insights can bridge methodological rigor with real-world societal impact. My work focuses on identifying systemic and sociotechnical solutions, as well as behavioural and policy interventions, that can help societies operate within planetary boundaries.

Working across the social and behavioural sciences, data science, and computer science is both exciting and challenging. While an interdisciplinary background does not always fit neatly within traditional academic departments, it has allowed me to explore complex sustainability questions from multiple perspectives.

My research has been published in journals including Science Advances, Computer Networks, Engineering Applications of Artificial Intelligence, Neural Computing and Applications, Sustainable Production and Consumption, Sustainable Development, Scientific Data, Collabra Psychology, and others.

Open to collaborations and always happy to connect.

Academic interests

Sustainability & Climate Change | Energy Informatics | Green Transition
Environmental Attitudes & Behavior | Climate Change Mitigation & Policy
Data Science for Sustainability | Green Computing & AI

Education

2018 M.Sc. in Computer Science (with distinction)

South Ural State University, Russia

2014 Ph.D. in Economics (with distinction)

Russian Academy of Sciences, Institute of Economics, Russia

2010 M.Sc. in Economics (with distinction)

South Ural Institute of Management and Economics, Russia

Honors

2025 Robert B. Cialdini Prize for an outstanding paper that uses field methods and demonstrates relevance to outside groups.

2025 Awarded “Best Publication of the Quarter” (Q3+Q4 2025) at the L3S Research Center for a paper in the “Green AI” category.

2024 Awarded “Best Publication of the Quarter” (Q1 2024) at the L3S Research Center for a paper in the “Green AI and Computing” category.

Professional experience

2023.10 – n.d., OFFIS – Institute for Information Technology, Carl von Ossietzky University, Germany

Senior Researcher, Research Software Developer

2023.09 – 2023.12, Institute for East European Studies, Free University of Berlin, Germany

Visiting Researcher

2023.08 – 2023.10, choyze (GmbH), Germany

Data Research Analyst

2022.09 – 2023.10, L3S Research Center, Leibniz University Hannover, Germany

Visiting Researcher

Senior Researcher

2021.07 – 2022.09, Center for Advanced Governance (NGO), Russia

Data Scientist, Data Engineer

2018.06 – 2022.08, South Ural University of Technology, Russia

Vice Rector for Research, Senior Researcher

2014.09 – 2018.06, South Ural University of Technology, Russia

Senior Researcher, Associate Professor

2010.09 – 2014.09, South Ural University of Technology, Russia

Researcher, Lecturer

2010.05 – 2013.05, Mechel Foundation (NGO), Russia

Technical Support Engineer

Publications (selected)

Computer Science & Engineering

Valko, D., & Marx Gómez, J. (2026). Topological and temporal stability analysis of the lightning network. Applied Network Science, https://doi.org/10.1007/s41109-026-00820-4
Valko, D., Schwarz, J. S., Isenmann, R., & Marx Gómez, J. (2026). Advancing energy system research with the FAIR+S framework. In Proc. of the 3rd NFDI4Energy Conference, Aachen, Germany, https://doi.org/10.52825/ocp.v9i.3278
Valko, D., & Kudenko, D. (2025). Hybrid pathfinding optimization for the lightning network with reinforcement learning. Engineering Applications of Artificial Intelligence, https://doi.org/10.1016/j.engappai.2025.110225
Valko, D., & Marx Gómez, J. (2025). Geolocated lightning network topology snapshots: A dataset covering 2019–2023. Scientific Data, https://doi.org/10.1038/s41597-025-06413-7
Valko, D., & Kudenko, D. (2025). Increasing energy efficiency of bitcoin infrastructure with reinforcement learning and one-shot path planning for the lightning network. Neural Computing and Applications, https://doi.org/10.1007/s00521-024-10588-2
Alsharif, S., Valko, D., & Veith, E. M. S. P. (2025). Dynamic optimization-based method for determining the flexibility potential at vertical system interconnections. In Proc. of 28th International Conference and Exhibition on Electricity Distribution (CIRED 2025), Geneva, Switzerland, https://doi.org/10.1049/icp.2025.1795
Alsharif, S., Valko, D., Wibbeke, J., & Lehnhoff, S. (2025). Co-simulation and MAS approach for assessment of large-scale electrolysers potential in flexibility markets. In Proc. of 2025 IEEE Kiel PowerTech Conference, Kiel, Germany, https://doi.org/10.1109/PowerTech59965.2025.11180369
Valko, D., Alsharif, S., & Rosinger, S. (2025). Mix matters: Technical evaluation of a carbon-aware power plant operation strategy for an industrial area in Bremen. In Proc. of the European Simulation and Modelling Conference 2025 (ESM 2025), Ghent, Belgium, https://doi.org/10.5281/zenodo.17443836
Valko, D., & Kudenko, D. (2024). Reducing CO₂ emissions in a peer-to-peer distributed payment network: Does geography matter in the lightning network? Computer Networks, https://doi.org/10.1016/j.comnet.2024.110297
Valko, D., Alsharif, S., & Tolk, D. (2024). An open-source carbon emissions simulator for smart grid co-simulation scenarios. In Proc. of the European Simulation and Modelling Conference 2024 (ESM 2024), San Sebastian, Spain, https://doi.org/10.5281/zenodo.13984401

Valko, D., & Thompson, K. (2025). Cultural differences and interdependencies in climate change mitigation efforts and their psychological antecedents across 63 countries. Sustainable Development, https://doi.org/10.1002/sd.70454
Sosnovskikh, S., Valko, D., & Meyer-Alten, R. (2025). Predictors of sustainable investment motivation: An interpretable machine learning approach. Sustainable Development, https://doi.org/10.1002/sd.3387
Vlasceanu, M., Doell, K. C., …, Valko, D., …, & Van Bavel, J. J. (2024). Addressing climate change with behavioral science: A global intervention tournament in 63 countries. Science Advances, https://doi.org/10.1126/sciadv.adj5778
Valko, D., Vasilevskaia, M., Bunina, M., Kozlova, M., Filippova, A. M., & Rud, D. (2024). Educational and career trajectories in Russia: Introducing a new source and datasets with a high granularity. Research Data Journal for the Humanities and Social Sciences, https://doi.org/10.1163/24523666-bja10046
Valko, D. (2023). Does going green feel good in Russia: implicit measurements with visual stimuli. Collabra: Psychology, https://doi.org/10.1525/collabra.73637
Valko, D. (2021). Environmental attitudes and contextual stimuli in emerging environmental culture: An empirical study from Russia. Sustainable Production and Consumption, https://doi.org/10.1016/j.spc.2021.05.008

Courses (selected)

2025 Green Software Practitioner / Green Software Foundation
2024 Renewable Energy, 4 courses Specialization / University of Colorado Boulder | Coursera
2024 Electric Industry Operations and Markets / Duke University | Coursera
2022 Data Science Summer School / Hertie School
2021 Quantitative Methods / University of Amsterdam | Coursera
2020 Data Science, 10 courses Specialization / John Hopkins University | Coursera

Skills

Methodological skills

Quantitative methods, econometrics (including structural, spatial and mixed-level), machine learning and LLM
Experimental and survey data analysis
Policy evaluation and causal inference

Programming & Simulation

Python, R (data analysis, modeling, simulation workflows)
Statistical and computational analysis (SPSS, Stata)
Software development: Python/PyTorch/OpenCV, C#, NodeJS, HTML/CSS/JS

Languages

English (advanced), German (independent)

Other

I am the first in my family to pursue an academic career (“first-generation academic”).
At the time I completed my first university degree in Economics in Russia, the standard program lasted five years. I was awarded a “Specialist” degree, which is recognized as equivalent to a Master’s degree. A separate Bachelor’s degree was not awarded, as the Bachelor’s stage had not yet been introduced in the Russian education system.

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