Hadi Banaee

Hadi Banaee


AASS Research Center
School of Science and Technology
Örebro University
70182 Örebro, Sweden
Room T2233
Phone +46 (0)19 30 36 58

Google Scholar

I am a researcher at the Center for Applied Autonomous Sensor Systems (AASS), Örebro University, from where I also received my PhD in 2018, with a research topic in using semantic representations in data2text frameworks.

My research is about bridging the inferred numerical information (e.g., via machine learning models) to the human-understandable descriptions. My research interests include knowledge representation (i.e., conceptual spaces), machine learning, explainable AI, and natural language generation (NLG). In particular, my research activity is focused on studying a data-driven approach to creating semantic models for numeric data. This model is then utilised for generating natural language text. Since 2018, I have been working on a couple of research areas wherein the aim is to analyse the streams of data and infer meaningful information. Currently, I am involved in a project called Campus.AI wherein for a network of sensors, I am working on the analysis of multi-channel data recordings to first detect the patterns, trends and changes in the data, and then present this information in natural language.


[1] H. Banaee, G. Chimamiwa, M. Alirezaie and A. Loutfi. Explaining Habits and Changes of Activities in Smart Homes. 2020BibTeX | DiVA | PDF ]
[2] G. Chimamiwa, M. Alirezaie, H. Banaee, U. Köckemann and A. Loutfi. Towards Habit Recognition in Smart Homes for People with Dementia. In Ambient Intelligence : 15th European Conference, AmI 2019, Rome, Italy, November 13–15, 2019, Proceedings, 11912(11912):363-369, 2019BibTeX | DiVA ]
[3] H. Banaee, E. Schaffernicht and A. Loutfi. Data-Driven Conceptual Spaces : Creating Semantic Representations for Linguistic Descriptions of Numerical Data. The journal of artificial intelligence research, 63:691-742, 2018BibTeX | DiVA | PDF ]
[4] H. Banaee. From Numerical Sensor Data to Semantic Representations : A Data-driven Approach for Generating Linguistic Descriptions. Örebro University, School of Science and Technology, Ph.D. Thesis, 2018BibTeX | DiVA | PDF ]
[5] A. Vajdi, N. Haspel and H. Banaee. A New DP Algorithm for Comparing Gene Expression Data Using Geometric Similarity. In Proceedings 2015 IEEE International Conference on Bioinformatics and Biomedicine, pages 1157-1161, 2015BibTeX | DiVA ]
[6] H. Banaee and A. Loutfi. Data-driven rule mining and representation of temporal patterns in physiological sensor data. IEEE journal of biomedical and health informatics, 19(5):1557-1566, 2015BibTeX | DiVA ]
[7] H. Banaee, M. U. Ahmed and A. Loutfi. Descriptive Modelling of Clinical Conditions with Data-driven Rule Mining in Physiological Data. In Proceedings of the 8th International conference of Health Informatics (HEALTHINF 2015) 2015BibTeX | DiVA | PDF ]
[8] M. U. Ahmed, H. Banaee, X. Rafael-Palou and A. Loutfi. Intelligent Healthcare Services to Support Health Monitoring of Elderly. In INTERNET OF THINGS : USER-CENTRIC IOT, PT I, 150(150):178-186, 2015BibTeX | DiVA | PDF ]
[9] H. Banaee and A. Loutfi. Using Conceptual Spaces to Model Domain Knowledge in Data-to-Text Systems. In Proceedings of the 8th International Natural Language Generation Conference, pages 11-15, 2014BibTeX | DiVA | PDF ]
[10] H. Banaee, M. U. Ahmed and A. Loutfi. A framework for automatic text generation of trends in physiological time series data. In IEEE International Conference on Systems, Man, and Cybernetics, 13-16 Oct. 2013, Manchester, pages 3876-3881, 2013BibTeX | DiVA ]
[11] H. Banaee, M. U. Ahmed and A. Loutfi. Data mining for wearable sensors in health monitoring systems : a review of recent trends and challenges. Sensors, 13(12):17472-17500, 2013BibTeX | DiVA | PDF ]
[12] M. U. Ahmed, H. Banaee and A. Loutfi. Health monitoring for elderly : an application using case-based reasoning and cluster analysis. ISRN Artificial Intelligence, 2013(2013):1-11, 2013BibTeX | DiVA | PDF ]
[13] H. Banaee, M. U. Ahmed and A. Loutfi. Towards NLG for Physiological Data Monitoring with Body Area Networks. In 14th European Workshop on Natural Language Generation, pages 193-197, 2013BibTeX | DiVA | PDF ]