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Danila Valko

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

I am a passionate researcher with a diverse background in sustainability, spanning social sciences, data science, and computer science. My papers settled in leading journals such as 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 for collaborations!

Academic interests

Sustainability | Energy Informatics | Green Computing
Social & Data Science for Sustainability
Environmental Attitudes & Behavior

Education

2018 M.Sc. in Computer Science (summa cum laude)

  South Ural State University, Russia

2014 Ph.D. in Economics (summa cum laude)

  Russian Academy of Sciences, Institute of Economics, Russia

2010 M.Sc. in Economics (summa cum laude)

  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.

Professional experience

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

  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 Assistant

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

  Visiting Researcher

2022.10 – 2023.08, School of Environmental and Social Studies, Tyumen State University, Russia

  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., 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

Social & Behavioural Science

• 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 analysis, econometrics, machine learning
• 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 (advanced)