Mitra Baratchi
Associate professor
- Name
- Dr. M. Baratchi
- Telephone
- +31 71 527 7492
- m.baratchi@liacs.leidenuniv.nl
- ORCID iD
- 0000-0002-1279-9310
Mitra Baratchi leads the Spatio-temporal data Analysis and Reasoning (STAR) research group and is a member of the interdisciplinary research programme Society, Artificial Intelligence and Life Sciences (SAILS). Her research interest lies in spatio-temporal, time-series, and mobility data modelling.
More information about Mitra Baratchi
PhD Candidates
News
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Real-life data ask for strong algorithms: Mitra Baratchi designs them -
Carolien Rieffe honoured with a NWO grant for research project on loneliness -
What happens on the schoolyard? Sensors on clothing reveal painful patterns -
Using data science to promote a healthy life style -
ESA grant to improve the Earth's 'digital twin' -
BNAIC/Benelearn conference big success -
Three Leiden scientists receive NWO ENW-KLEIN grant for innovative research -
From smarter cities to epidemic control: algorithms can help -
Six Computer Science master students excel and go to Oxford
Links
Former PhD candidates
Mitra Baratchi leads the Spatio-temporal data Analysis and Reasoning (STAR) research group and is a member of the research interdisciplinary programme Society, Artificial Intelligence and Life Sciences (SAILS). Her research interest lies in spatio-temporal, time-series, and mobility data modelling. Specifically, she designs algorithms that extract patterns from such data in a fully automated manner. Her research targets applications in a broad range of urban, environmental, and industrial domains for which she has collaborations notably with the European Space Agency, Honda Research Institute, various municipalities, and researchers in other scientific disciplines.
Before joining Leiden, she worked as a postdoc researcher in the Design and Analysis of Communication Systems research group at the University of Twente. Prior to that, she was a researcher in the Ambient Intelligence research group at Saxion University of Applied Sciences. In June 2015 she received her PhD degree from University of Twente.
Associate professor
- Science
- Leiden Inst of Advanced Computer Science
- Wasala J., Marselis S.M., Arp L.R., Hoos H.H., Longépé N. & Baratchi M. (2024), AutoSR4EO: an autoML approach to super-resolution for earth observation images, Remote Sensing 16(3): 443.
- Laanen R., Nasri M., Dijk M.K. van, Baratchi M., Koutamanis A. & Rieffe C. (2023), Automated classification of pre-defined movement patterns: a comparison between GNSS and UWB technology. Joint International Scientific Conferences on AI and Machine Learning. BNAIC/BeNeLearn 2022 7 November 2022 - 9 November 2022.
- Yang L., Baratchi M. & Leeuwen M. van (2023), Unsupervised discretization by two-dimensional MDL-based histogram, Machine Learning 112: 2397-2431.
- Eichengreen A., Rooijen M. van, Klaveren L. van, Nasri M., Tsou Y., Koutamanis A., Baratchi M. & Rieffe C. (2023), The impact of loose‐parts‐play on schoolyard social participation of children with and without disabilities: a case study, Child: Care, Health and Development 50(1): e13144.
- Nasri M., Tsou Y.-T., Koutamanis A., Baratchi M., Giest S., Reidsma D. & Rieffe C. (2022), A novel data-driven approach to examine children’s movements and social behaviour in schoolyard environments, Children 9(8): 1177.
- Rahmani H.A., Aliannejadi M., Baratchi M. & Crestani F. (2022), A systematic analysis on the impact of contextual information on point-of-interest recommendation, ACM Transactions on Information Systems 40(4): 88.
- Tetteroo J., Baratchi M. & Hoos H.H. (2022), Automated machine learning for COVID-19 forecasting, IEEE Access 10: 94718-94737.
- Arp L.R., Baratchi M. & Hoos H.H. (2022), VPint: value propagation-based spatial interpolation, Data Mining and Knowledge Discovery 36(5): 1647-1678.
- Kefalas M., Stein B. van, Baratchi M., Apostolidis A. & Bäck T.H.W. (2022), End-to-end pipeline for uncertainty quantification and remaining useful life estimation: an application on aircraft engines. Do P. (Ed.), Proceedings of the European conference of the PHM Society 2022 . PHM Society European Conference 6 July 2022 - 8 July 2022. PHM Society European Conference no. 7: PHM Society. 245-260.
- Wang C., Baratchi M., Bäck T.H.W., Hoos H.H., Limmer S. & Olhofer M. (2022), Towards time-series feature engineering in automated machine learning for multi-step-ahead forecasting. Rojas I., Pomares H., Valenzuela O., Rojas F. & Herrera L.J. (Eds.), Engineering Proceedings. The 8th International Conference on Time Series and Forecasting 27 June 2022 - 30 June 2022 no. 18: MDPI. 17.
- Sa N.C. de, Baratchi M., Hauser L.T. & Bodegom P. van (2021), Exploring the impact of noise on hybrid inversion of PROSAIL RTM on Sentinel-2 data, Remote Sensing 13(4): 648.
- Ottervanger G.B., Baratchi M. & Hoos H.H. (2021), MultiETSC: automated machine learning for early time series classification, Data Mining and Knowledge Discovery 35: 2602–2654 .
- Staalduinen J.H. van, Tetteroo J., Gawehns D. & Baratchi M. (2021), An intelligent tree planning approach using location-based social networks data. Baratchi M., Cao L., Kosters W.A., Lijffijt J., Rijn J.N. van & Takes F.W. (Eds.), Artificial intelligence and machine learning: 32nd Benelux conference, BNAIC/Benelearn 2020, Leiden, the Netherlands, November 19–20, 2020, revised selected papers. BNAIC/Benelearn 2020 19 November 2020 - 20 November 2020. Communications in Computer and Information Science no. 1398. Cham: Springer. 157-171.
- Kefalas M., Baratchi M., Apostolidis A., Herik D. van den & Bäck T.H.W. (2021), Automated machine learning for remaining useful life estimation of aircraft engines, 2021 IEEE International conference on prognostics and health management (ICPHM). IEEE International Conference on Prognostics and Health Management (ICPHM) 7 June 2021 - 9 June 2021: IEEE. 1-9.
- Salinas N.R.P., Baratchi M., Rijn J.N. van & Vollrath A. (2021), Automated machine learning for satellite data: integrating remote sensing pre-trained models into AutoML systems. Dong Y., Kourtellis N., Hammer B. & Lozano J.A. (Eds.), Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track. ECML PKDD 2021. Joint European Conference on Machine Learning and Knowledge Discovery in Databasis. ECML PKDD 2021 13 September 2021 - 17 September 2021 no. 12979. Cham: Springer International Publishing. 447-462.
- Arp L., Vreumingen D. van, Gawehns D. & Baratchi M. (2020), Dynamic macro scale traffic flow optimisation using crowd-sourced urban movement data, 2020 21st IEEE International Conference on Mobile Data Management (MDM) . IEEE International Conference on Mobile Data Management (MDM 2020) 30 June 2020 - 3 July 2020: IEEE. 168-177.
- Wang C., Bäck T.H.W., Hoos H.H., Baratchi M., Limmer S. & Olhofer M. (2019), Automated Machine Learning for Short-term Electric Load Forecasting, 2019 IEEE Symposium Series on Computational Intelligence (SSCI). 2019 IEEE Symposium Series on Computational Intelligence (SSCI) 6 December 2019 - 9 December 2019: IEEE. 314-321.
- Chilipirea C., Dobre C., Baratchi M. & Steen M. van (2018), Identifying Movements in Noisy Crowd Analytics Data, 2018 19th IEEE International Conference on Mobile Data Management (MDM). IEEE MDM 2018 - 19th IEEE International Conference on Mobile Data Management 26 June 2018 - 28 June 2018: IEEE. 161-166.
- Chilipirea C., Baratchi M., Dobre C. & Steen M. van (2018), Identifying Stops and Moves in WiFi Tracking Data, Sensors 18(11): 4039.