Amnir Hadachi, Ph.D.

Univerity of Tartu

Delta Center, Narva mnt 18, Tartu


Enjoys Research and Education, Shaping Future Generations and Collaborating with Industry, as well as Contributing into Building Future Mobility and Sustainable Transportation.

My research interest includes: Mobility Modelling, Applied Machine Learning, Intelligent Transportation Systems, Location-based Services, and Data Mining.

Current Research

My current research topics are related to:
  • Mobility Modelling Using Mobile Network Data
  • Pedestrian Safety System
  • Simultaneous Localisation and Mapping
  • Mobile Positioning
  • Solving Urban Mobility Problems


My primary research interests are related to:
  • Mobility Modelling
  • Location Based Services
  • Perception for Autonmous Vehciles
  • Tracking and Localization
  • Intelligent Transporation Systems

Theses Under-Supervision

  • Toivo Vajakas, Phd student, (sup) Eero Vainikko; Amnir Hadachi, Analysis of Situation in Mobile Positioning Applications, University of Tartu, Faculty of Science and Technology, Institute of Computer Science.
  • Joonas Lõmps, Phd student, (sup) Amnir Hadachi, MultiSensor Fusion for Direct Simultaneous Localization and Mapping on Self-Driving Cars, University of Tartu, Faculty of Science and Technology, Institute of Computer Science.
  • Shan Wu, Phd student, (sup) Amnir Hadachi, Building Robust perception Algorithms for Enabling MultiSensor-Based pedestrian Protection in Self Driving Cars, University of Tartu, Faculty of Science and Technology, Institute of Computer Science.
  • Artjom Lind, Phd student, (sup) Eero Vainikko; Amnir Hadachi, Exploring the Potential Behind Mobile Network Data for Extracting Accurate Mobile Positioning, University of Tartu, Faculty of Science and Technology, Institute of Computer Science.

PostDoc Supervision

  • Khoshkhah, Kaveh,“ Building daily activities model of human mobility behaviour using CDR data” - 2021-2023.
  • Pourmoradnasseri, Mozhgan, and Khoshkhah, Kaveh, “Road traffic simulation model calibration for zero emission delivery applications” - ZEUS project 2020.
  • Pourmoradnasseri, Mozhgan,“Trajectory reconstruction and mobility patterns extraction from CDR data” - 2019.
  • Khoshkhah, Kaveh,“CDR based trajectory enrichment using Markov chain algorithm” - 2019.

Supervided Dissertations


ModSplit 2021-Ongoing

Designing a methodology for real-time visualisation and estimation of mobility modality distribution in Tartu City. The project addresses one of the challenging ...

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ZEUS 2019-2020

Zero Emission off-peak Urban deliverieS project contributes to MOBiLus´vision to transform urban spaces to the benefit of citizens, companies and cities ...

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NutikasUGV 2018-2021

Applied research on system of sensors and software algorithms for safety and driver assistance on remotely operated ground vehicles for off-road applications ...

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Methods and Algorithms for Urban Mobility: The cooperation between Taxify and University of Tartu will be a two-way process. On one hand, Taxify will be able to bring ...

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Population Movement Analytics, Monitoring and Prediction Algorithms project is shaped around the idea of modeling human mobility and prediction because it is ...

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Predictive and Mining Algorithms for Behavioral Analysis and Performance Assessment project is to make use of big data and create algorithms and tools for better ...

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NoFar is about desiging a noise model for refining farming activities recognition based on Sentinel Data. The idea is to provide a solution for denoising the data ...

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Data Science Methods and Applications project o extract useful and predictive knowledge from big, medium, and small data. We are focusing on new methods in data ...

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LR-LDA: 2013-2015

Large Real-time Location Data Algorithms project is to improve the quality and the speed of individual mobile positioning based data stream processing for real-time ...

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Copyright AH 2021