Danila Valko

M.Sc. in Computer Science

^{danila.valko@proton.me}

Academic interests and expertise

Energy Informatics & Sustainability
Data Science for Sustainability
Green computing & Green AI

Education

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

South Ural State University (National Research University), Russia
Supervisor: Mikhail Zymbler

2010 B.A.+M.A. in Finance and Economics (summa cum laude)

South Ural Institute of Management and Economics, Russia
Supervisor: Irina Sergeicheva

Professional experience

2023 – n.d. OFFIS - Institute for Information Technology, Carl von Ossietzky University, Germany

Researcher, Software Developer
Energy Informatics
Smart Grids co-simulation

2022 – 2023 L3S Research Center, Leibniz University Hannover, Germany

Visiting Researcher (12 months)
AI & Deep Reinforcement Learning, Green Computing

2021 – 2022 Center for Advanced Governance (NGO), Russia

Data Scientist, Data Engineer
Research & Data Analysis
Data Mining & Preparation (Python/PostgreSQL, ETL/ELT, Apache Airflow)

2014 – 2022 The South Ural University of Technology, Russia

Senior Researcher, Associate Professor
Quantitative Analysis, Econometrics (ANOVA, SEM, ATET, PSM, CS-ADRL)
Teaching IT, B.A./M.A. Thesis Supervision

2010 – 2013 Mechel-Fund (NGO), Russia

Technician
IT-infrastructure maintenance

Courses (taken recently)

2022 Data Science Summer School / Hertie School
2021 Quantitative Methods / University of Amsterdam | Coursera
2021 Machine Learning and Computer Vision / IT Korpus
2021 Introduction to Data Analysis in Python / Center for Advanced Governance
2020 Data Science, 10 courses Specialization / John Hopkins University | Coursera
2020 Data Analysis, 4 courses Specialization / Novosibirsk State University | Coursera
2020 Machine Learning and IT Project Management for Educators / Moscow Institute of Physics and Technology
2020 IT Infrastructure and Artificial Intelligence / Tomsk State University
2020 Artificial Intelligence, Big Data and Machine Learning / Tomsk State University

Publications (selected)

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., & Kudenko, D. (2024). 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
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., Alsharif, S., Tolk, D., & Grimm, T. (2024). MASSCA: Scalable multi-agent system framework for smart power cell co-simulation. In Proc. of the European Simulation and Modelling Conference 2024 (ESM 2024), San Sebastian, Spain, https://doi.org/10.5281/zenodo.14004357
Valko, D. (2018). A recommendation system based on data mining of a scientometric research profile. Software & Systems, http://doi.org/10.15827/0236-235X.122.275-283
Valko, D. (2016). Training software to perform technological calculations. Software & Systems, http://doi.org/10.15827/0236-235X.114.179-184

Preprints (recent)

Valko, D., & Kudenko, D. (2024). Sustainable broadcasting in Blockchain Networks with Reinforcement Learning. arXiv, https://doi.org/10.48550/arXiv.2407.15616

Prepared datasets and data papers (recent)

Petersen, K., Valko, D., & Tolk, D. (2025). hyBit open data collection. Zenodo, https://doi.org/10.5281/zenodo.15052032

Patents

Valko, D., & Muhina, Yu. (2020). Web application "Science Festival of the South Ural University of Technology" / Reg. No. RU2020616358.
Valko, D., & Zymbler, M. (2018). Decision support system in the field of scientific research management based on intellectual analysis of scientometric data / Reg. No. RU2018613068.
Valko, D., & Koltashov, A. (2016). Module for data mining and aggregating of scientometric data from open services on the Internet / Reg. No. RU2016619028.
Valko, D., & Moskvina, V. (2015). Calculation program for calibration systems for a rolling mill / Reg. No. RU2015618937.

Other professional skills

Language skills: Russian (native), English (advanced), German (limited)
Software Development skills: Python, C#, Java, HTML/CSS/JS, QA:SpecFlow/Playwright
ML & Data Science skills: Data Mining and Machine Learning in Python, PyTorch, TensorFlow, OpenCV