Artem Baklanov
Research Scholar
Agriculture, Forestry, and Ecosystem Services Research Group
Biodiversity and Natural Resources Program
Research Scholar
Exploratory Modeling of Human-natural Systems Research Group
Advancing Systems Analysis Program
Biography
Artem Baklanov joined IIASA as a Postdoctoral Research Scholar in September 2014. He is currently affiliated with the Exploratory Modeling of Human-Natural Systems (EM) research group within the Advancing Systems Analysis (ASA) program, where he works on the application of control theory, game theory, and machine learning to inform environmental decision making. Currently, he develops tools for a trade-off analysis in Integrated Assessment Models (IAMs) and studies consistency between short-term policies and long-term targets. Dr. Baklanov applies the attainable set approach to circumscribe possible short-term actions that are consistent with a specified long-term target, as well as to reveal which long-term targets are still attainable depending on a chosen short-term policy.Last update: 22 JAN 2021
Publications
Baklanov, A. (2017). On a density property of weakly absolutely continuous measures. General case. Izvestiya Instituta Matematiki i Informatiki 2 (50) 3-12.
Chentsov, A., Baklanov, A. , & Savenkov, I. (2017). On Control Problem with Constraints of Asymptotic Character. In: 8th International Conference on Physics and Control (PhysCon 2017). International Physics and Control Society (IPACS).
Subkhankulova, D., Baklanov, A. , & McCollum, D. (2017). Demand Side Management: A Case for Disruptive Behaviour. In: Advanced Computational Methods for Knowledge Engineering. Eds. Le, Nguyen-Thinh, van Do, Tien, Nguyen, Ngoc Thanh, & Thi, Hoai An Le, pp. 47-59 Cham, Switzerland: Springer International Publishing AG. ISBN 978-3-319-61911-8 10.1007/978-3-319-61911-8_5.
Baklanov, A. , Chentsov, A., & Savenkov, I. (2017). On reachable sets for one-pulse controls under constraints of asymptotic character. Cybernetics and Physics 6 (4) 166-173.
Rekabsaz, N., Lupu, M., Baklanov, A. , Hanbury, A., Duer, A., & Anderson, L. (2017). Volatility Prediction using Financial Disclosures Sentiments with Word Embedding-based IR Models. In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics. pp. 1712-1721 Vancouver, Canada: Association for Computational Linguistics. 10.18653/v1/P17-1157.