Publications

2023

1. Unsupervised discretization by two-dimensional mdl-based histogram

   Yang, Lincen, Baratchi, Mitra, and Leeuwen, Matthijs

   Machine Learning, 2023

   [URL] [DOI]
2. A GNN-based Architecture for Group Detection from spatio-temporal Trajectory Data

   Nasri, Maedeh, Fang, Zhizhou, Baratchi, Mitra, Englebienne, Gwenn, Wang, Shenghui, Koutamanis, Alexander, and Rieffe, Carolien

   In Proceedings of the 21th International Symposium on Intelligent Data Analysis (IDA 2023), 2023

2022

1. A Novel Data-driven Approach to Examine Children’s Movements and Social Behaviour in Schoolyard Environments

   Nasri, Maedeh, Tsou, Yung-Ting, Koutamanis, Alexander, Baratchi, Mitra, Giest, Sarah, Reidsma, Dennis, and Rieffe, Carolien

   Children, vol. 9, 2022

   [URL] [DOI]
2. VPint: value propagation-based spatial interpolation

   Arp, Laurens, Baratchi, Mitra, and Hoos, Holger

   Data Mining and Knowledge Discovery, vol. 36, pp. , 2022

   [URL] [DOI]
3. Automated classification of pre-defined movement patterns: A comparison between GNSS and UWB technology

   Laanen, Rodi, Nasri, Maedeh, Dijk, Richard, Baratchi, Mitra, Koutamanis, Alexander, and Rieffe, Carolien

   In online proceedings of BNAIC/BeNeLearn, 2022

   [URL]
4. VPint: value propagation-based spatial interpolation

   Arp, Laurens, Baratchi, Mitra, and Hoos, Holger

   Data Mining and Knowledge Discovery, vol. 36, pp. , 2022

   [URL] [DOI]
5. AutoML for estimating grass height from ETM+/OLI data from field measurements at a nature reserve

   Sa, Nuno Cesar, Baratchi, Mitra, Buitenhuis, Vincent, Cornelissen, Perry, and Bodegom, Peter M.

   GIScience & Remote Sensing, vol. 59, pp. 2164-2183, 2022

   [URL] [DOI]
6. Automated classification of pre-defined movement patterns: A comparison between GNSS and UWB technology

   Laanen, Rodi, Nasri, Maedeh, Dijk, Richard, Baratchi, Mitra, Koutamanis, Alexander, and Rieffe, Carolien

   In BNAIC/BeNeLearn 2022, 2022

   [URL]
7. A Novel Data-driven Approach to Examine Children’s Movements and Social Behaviour in Schoolyard Environments

   Nasri, Maedeh, Tsou, Yung-Ting, Koutamanis, Alexander, Baratchi, Mitra, Giest, Sarah, Reidsma, Dennis, and Rieffe, Carolien

   Children, vol. 9, 2022

   [URL] [DOI]
8. An end-to-end pipeline for uncertainty quantification and remaining useful life estimation: An application on aircraft engines

   Kefalas, Marios, Stein, Bas, Baratchi, Mitra, Apostolidis, Asteris, and Bäck, Thomas

   In PHM Society European Conference, vol. 7, pp. 245–260, 2022
9. A Systematic Analysis on the Impact of Contextual Information on Point-of-Interest Recommendation

   Rahmani, Hossein A., Aliannejadi, Mohammad, Baratchi, Mitra, and Crestani, Fabio

   ACM Transactions on Information Systems, vol. 40, 2022

   [URL] [DOI]
10. Towards Time-Series Feature Engineering in Automated Machine Learning for Multi-Step-Ahead Forecasting

    Wang, Can, Baratchi, Mitra, Bäck, Thomas, Hoos, Holger H., Limmer, Steffen, and Olhofer, Markus

    Engineering Proceedings, vol. 18, 2022

    [URL] [DOI]
11. Automated Machine Learning for COVID-19 Forecasting

    Tetteroo, Jaco, Baratchi, Mitra, and Hoos, Holger H.

    IEEE Access, vol. 10, pp. 94718-94737, 2022

    [DOI]
12. Towards Automated Machine Learning for Time-Series Forecasting

    Wang, Can, Baratchi, Mitra, Bäck, Thomas, Hoos, Holger H., Limmer, Steffen, and Olhofer, Markus

    Under review, 2022

2021

1. Automated Machine Learning for Satellite Data: Integrating Remote Sensing Pre-trained Models into AutoML Systems

   Palacios Salinas, Nelly Rosaura, Baratchi, Mitra, Rijn, Jan N., and Vollrath, Andreas

   In Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track, pp. 447–462, 2021

   [Abs] [DOI]

   Current AutoML systems have been benchmarked with traditional natural image datasets. Differences between satellite images and natural images (e.g., bit-wise resolution, the number, and type of spectral bands) and lack of labeled satellite images for training models, pose open questions about the applicability of current AutoML systems on satellite data. In this paper, we demonstrate how AutoML can be leveraged for classification tasks on satellite data. Specifically, we deploy the Auto-Keras system for image classification tasks and create two new variants, IMG-AK and RS-AK, for satellite image classification that respectively incorporate transfer learning using models pre-trained with (i) natural images (using ImageNet) and (ii) remote sensing datasets. For evaluation, we compared the performance of these variants against manually designed architectures on a benchmark set of 7 satellite datasets. Our results show that in 71% of the cases the AutoML systems outperformed the best previously proposed model, highlighting the usefulness of a customized satellite data search space in AutoML systems. Our RS-AK variant performed better than IMG-AK for small datasets with a limited amount of training data. Furthermore, it found the best automated model for the datasets composed of near-infrared, green, and red bands.

2. MultiETSC: automated machine learning for early time series classification

   Ottervanger, Gilles, Baratchi, Mitra, and Hoos, Holger H

   Data Mining and Knowledge Discovery, vol. 35, pp. 2602–2654, 2021

   [URL] [DOI]
3. Automated Machine Learning for Satellite Data: Integrating Remote Sensing Pre-trained Models into AutoML Systems

   Salinas, Nelly Rosaura Palacios, Baratchi, Mitra, Rijn, Jan N., and Vollrath, Andreas

   In Joint European Conference on Machine Learning and Knowledge Discovery in Databases, Virtual, 13-17 September, 2021, pp. 447–462, 2021

2020

1. Metaheuristic macro scale traffic flow optimisation from urban movement data

   Arp, Laurens, Vreumingen, Dyon, Gawehns, Daniela, and Baratchi, Mitra

   arXiv preprint arXiv:2006.02214, 2020
2. Dynamic macro scale traffic flow optimisation using crowd-sourced urban movement data

   Arp, Laurens, Vreumingen, Dyon, Gawehns, Daniela, and Baratchi, Mitra

   In 2020 21st IEEE International Conference on Mobile Data Management (MDM), pp. 168–177, 2020
3. Reconciling Predictions in the Regression Setting: An Application to Bus Travel Time Prediction

   Mendes-Moreira, João, and Baratchi, Mitra

   In Advances in Intelligent Data Analysis XVIII, pp. 313–325, 2020

   [Abs]

   In different application areas, the prediction of values that are hierarchically related is required. As an example, consider predicting the revenue per month and per year of a company where the prediction of the year should be equal to the sum of the predictions of the months of that year. The idea of reconciliation of prediction on grouped time-series has been previously proposed to provide optimal forecasts based on such data. This method in effect, models the time-series collectively rather than providing a separate model for time-series at each level. While originally, the idea of reconciliation is applicable on data of time-series nature, it is not clear if such an approach can also be applicable to regression settings where multi-attribute data is available. In this paper, we address such a problem by proposing Reconciliation for Regression (R4R), a two-step approach for prediction and reconciliation. In order to evaluate this method, we test its applicability in the context of Travel Time Prediction (TTP) of bus trips where two levels of values need to be calculated: (i) travel times of the links between consecutive bus-stops; and (ii) total trip travel time. The results show that R4R can improve the overall results in terms of both link TTP performance and reconciliation between the sum of the link TTPs and the total trip travel time. We compare the results acquired when using group-based reconciliation methods and show that the proposed reconciliation approach in a regression setting can provide better results in some cases. This method can be generalized to other domains as well.

2019

1. LGLMF: local geographical based logistic matrix factorization model for POI recommendation

   Rahmani, Hossein A, Aliannejadi, Mohammad, Ahmadian, Sajad, Baratchi, Mitra, Afsharchi, Mohsen, and Crestani, Fabio

   In proceedings of The 15th Asia Information Retrieval Societies Conference, 2019

   [URL]
2. Category-Aware Location Embedding for Point-of-Interest Recommendation

   Rahmani, Hossein A., Aliannejadi, Mohammad, Mirzaei Zadeh, Rasoul, Baratchi, Mitra, Afsharchi, Mohsen, and Crestani, Fabio

   In Proceedings of the 2019 ACM SIGIR International Conference on Theory of Information Retrieval, pp. 173-176, 2019

   [URL] [DOI]
3. Design & analysis of a distributed routing algorithm towards Internet-wide geocast

   Meijerink, Bernd, Baratchi, Mitra, and Heijenk, Geert

   Computer Communications, vol. 146, pp. 201 - 218, 2019

   [URL] [DOI]
4. Automated Machine Learning for Short-term Electric Load Forecasting

   Wang, Can, Bäck, Thomas, Hoos, Holger H., Baratchi, Mitra, Limmer, Steffen, and Olhofer, Markus

   In IEEE Symposium Series on Computational Intelligence, SSCI 2019, Xiamen, China, December 6-9, 2019, pp. 314–321, 2019

   [URL] [DOI]
5. A Glossary for Research on Human Crowd Dynamics

   Adrian, Juliane, Bode, Nikolai, Amos, Martyn, Baratchi, Mitra, Beermann, Mira, Boltes, Maik, Corbetta, Alessandro, Dezecache, Guillaume, Drury, John, Fu, Zhijian, and others,

   Collective Dynamics, vol. 4, pp. 1–13, 2019

2018

1. Identifying Movements in Noisy Crowd Analytics Data

   Chilipirea, Cristian, Dobre, Ciprian, Baratchi, Mitra, and Steen, Maarten

   In 19th IEEE International Conference on Mobile Data Management, pp. 515-520, 2018

   [URL]
2. Identifying Stops and Moves in WiFi Tracking Data

   Chilipirea, Cristian, Dobre, Ciprian, Baratchi, Mitra, and Steen, Maarten

   Sensors, vol. 18, pp. 4039, 2018

   [URL] [DOI]

2017

1. Evaluation of Geocast Routing Trees on Random and Actual Networks

   Meijerink, Bernd, Baratchi, Mitra, and Heijenk, Geert

   In Wired/Wireless Internet Communications, pp. 127–142, 2017

   [URL]
2. WiFi Tracking of Pedestrian Behavior

   Petre, Andreea-Cristina, Chilipirea, Cristian, Baratchi, Mitra, Dobre, Ciprian, and Steen, Maarten

   pp. 309 - 337, 2017

   [URL]
3. Reliable Vehicular Broadcast Using 5G Device-to-device Communication

   Gholibeigi, Mozhdeh, Sarrionandia, Nora, Karimzadeh, Morteza, Baratchi, Mitra, Berg, Hans, and Heijenk, Geert

   In 2017 10th IFIP Wireless and Mobile Networking Conference (WMNC), pp. 1-8, 2017

   [URL]
4. Inferring the Social-Connectedness of Locations from Mobility Data

   Brugman, Tristan, Baratchi, Mitra, Heijenk, Geert, and Steen, Maarten

   In Social Informatics, pp. 443–457, 2017

   [URL]
5. Spaceprint: A Mobility-based Fingerprinting Scheme for Spaces

   Baratchi, Mitra, Heijenk, Geert, and Steen, Maarten

   In Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, pp. 102:1–4, 2017

   [URL]

2016

1. Traffic-adaptive Duty Cycle Adaptation in TR-MAC Protocol for Wireless Sensor Networks

   Morshed, Sarwar, Baratchi, Mitra, and Heijenk, Geert

   In 2016 Wireless Days (WD), pp. 1-6, 2016

   [URL]
2. A Multi-channel Multiple Access Scheme Using Frequency Offsets-Modelling and analysis

   Morshed, Sarwar, Baratchi, Mitra, Mandal, Pranab. K., and Heijenk, Geert

   In 2016 IEEE 12th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), pp. 1-7, 2016

   [URL]
3. Towards Decisive Garments for Heat Stress Risk Detection

   Baratchi, Mitra, Teunissen, Lennart, Ebben, Peter, Teeuw, Wouter, Laarhuis, Jan, and Steen, Maarten

   In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct, pp. 1095–1100, 2016

   [URL]
4. Towards Reliable Multi-hop Broadcast in VANETs: An Analytical Approach

   Gholibeigi, Mozhdeh, Baratchi, Mitra, Berg, Hans, and Heijenk, Geert

   In 2016 IEEE Vehicular Networking Conference (VNC), pp. 1–8, 2016

   [URL]
5. An Efficient Geographical Addressing Scheme for the Internet

   Meijerink, Bernd, Baratchi, Mitra, and Heijenk, Geert

   In Wired/Wireless Internet Communications, pp. 78–90, 2016

   [URL]

2014

1. A Hierarchical Hidden semi-Markov Model for Modeling Mobility Data

   Baratchi, Mitra, Meratnia, Nirvana, Havinga, Paul J. M., Skidmore, Andrew K., and Toxopeus, Bert A. K. G.

   In Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing, pp. 401–412, 2014

   [URL]
2. Recognition of Periodic Behavioral Patterns from Streaming Mobility Data

   Baratchi, Mitra, Meratnia, Nirvana, and Havinga, Paul J. M.

   In Mobile and Ubiquitous Systems: Computing, Networking, and Services, pp. 102–115, 2014

   [URL]

2013

1. Evaluation of Incentives for Body Area Network-based Healthcare Systems

   Aflaki, Siavash, Meratnia, Nirvana, Baratchi, Mitra, and Havinga, Paul J. M.

   In 2013 IEEE Eighth International Conference on Intelligent Sensors, Sensor Networks and Information Processing, pp. 515–520, 2013

   [URL]
2. Sensing Solutions for Collecting Spatio-Temporal Data for Wildlife Monitoring Applications: A Review

   Baratchi, Mitra, Meratnia, Nirvana, Havinga, Paul J. M., Skidmore, Andrew K., and Toxopeus, Bert A. G.

   Sensors, vol. 13, pp. 6054–6088, 2013

   [URL]
3. Finding Frequently Visited Paths: Dealing with the Uncertainty of Spatio-temporal Mobility Data

   Baratchi, Mitra, Meratnia, Nirvana, and Havinga, Paul J. M.

   In 2013 IEEE Eighth International Conference on Intelligent Sensors, Sensor Networks and Information Processing, pp. 479-484, 2013

   [URL]
4. On the Use of Mobility Data for Discovery and Description of Social Ties

   Baratchi, Mitra, Meratnia, Nirvana, and Havinga, Paul J. M.

   In Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, pp. 1229–1236, 2013

   [URL]
5. Sensing Solutions for Collecting Spatio-Temporal Data for Wildlife Monitoring Applications: A Review

   Baratchi, Mitra, Meratnia, Nirvana, Havinga, Paul J. M., Skidmore, Andrew K., and Toxopeus, Bert A. G.

   Sensors, vol. 13, pp. 6054–6088, 2013

   [URL]