Hadi BanaeePosition: Researcher School/office: School of Science and Technology
Phone: No number available
About Hadi Banaee
I am a postdoc 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.
Articles in journals
- Kalidindi, S. S. V. , Banaee, H. , Karlsson, H. & Loutfi, A. (2023). Indoor temperature prediction with context-aware models in residential buildings. Building and Environment, 244.
- Banaee, H. , Schaffernicht, E. & Loutfi, A. (2018). Data-Driven Conceptual Spaces: Creating Semantic Representations for Linguistic Descriptions of Numerical Data. The journal of artificial intelligence research, 63, 691-742.
- Banaee, H. & Loutfi, A. (2015). Data-driven rule mining and representation of temporal patterns in physiological sensor data. IEEE journal of biomedical and health informatics, 19 (5), 1557-1566.
- Banaee, H. , Ahmed, M. U. & Loutfi, A. (2013). Data mining for wearable sensors in health monitoring systems: a review of recent trends and challenges. Sensors, 13 (12), 17472-17500.
- Ahmed, M. U. , Banaee, H. & Loutfi, A. (2013). Health monitoring for elderly: an application using case-based reasoning and cluster analysis. ISRN Artificial Intelligence, 2013 (2013), 1-11.
- Banaee, H. , Chimamiwa, G. , Alirezaie, M. & Loutfi, A. (2020). Explaining Habits and Changes of Activities in Smart Homes. Paper presented at Artificial Intelligence for Health, Personalised Medicine and Wellbeing (HELPLINE), in conjunction with ECAI 2020, Santiago de Compostela, Spain (Digital Conference), August 29 - September 8, 2020.
- Chimamiwa, G. , Alirezaie, M. , Banaee, H. , Köckemann, U. & Loutfi, A. (2019). Towards Habit Recognition in Smart Homes for People with Dementia. In: Ioannis Chatzigiannakis, Boris De Ruyter, Irene Mavrommati, Ambient Intelligence 15th European Conference, AmI 2019, Rome, Italy, November 13–15, 2019, Proceedings. Paper presented at 15th European Conference on Ambient Intelligence (AmI 2019), Rome, Italy, November 13-15, 2019. (pp. 363-369). Springer Nature.
- Vajdi, A. , Haspel, N. & Banaee, H. (2015). A New DP Algorithm for Comparing Gene Expression Data Using Geometric Similarity. In: Proceedings 2015 IEEE International Conference on Bioinformatics and Biomedicine. Paper presented at IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2015), Washington, DC, USA, November 9-12, 2015. (pp. 1157-1161). New York: IEEE conference proceedings.
- Banaee, H. , Ahmed, M. U. & Loutfi, A. (2015). 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). Paper presented at HEALTHINF 2015 : HEALTHINF 8th International Conference on Health Informatics, 12-15 january, Lisabon, Portugal. SciTePress.
- Ahmed, M. U. , Banaee, H. , Rafael-Palou, X. & Loutfi, A. (2015). Intelligent Healthcare Services to Support Health Monitoring of Elderly. In: INTERNET OF THINGS USER-CENTRIC IOT, PT I. Paper presented at 1st International Conference on IoT Technologies for HealthCare, HealthyIoT, October 27-29, Rome, Italy, 2014. (pp. 178-186). Springer.
- Banaee, H. & Loutfi, A. (2014). Using Conceptual Spaces to Model Domain Knowledge in Data-to-Text Systems. In: Proceedings of the 8th International Natural Language Generation Conference. Paper presented at 8th International Natural Language Generation(INLG)Conference, 19-21 June, Philadelphia, Pennsylvania, USA. (pp. 11-15). Association for Computational Linguistics.
- Banaee, H. , Ahmed, M. U. & Loutfi, A. (2013). 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. Paper presented at IEEE International Conference on Systems, Man, and Cybernetics, 13-16 Oct. 2013, Manchester. (pp. 3876-3881). IEEE conference proceedings.
- Banaee, H. , Ahmed, M. U. & Loutfi, A. (2013). Towards NLG for Physiological Data Monitoring with Body Area Networks. In: 14th European Workshop on Natural Language Generation. Paper presented at 14th European Workshop on Natural Language Generation, Sofia, Bulgaria, August 8-9, 2013. (pp. 193-197).
Doctoral theses, comprehensive summaries
- Banaee, H. (2018). From Numerical Sensor Data to Semantic Representations: A Data-driven Approach for Generating Linguistic Descriptions. (Doctoral dissertation). (Comprehensive summary) Örebro: Örebro University.