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.
| [1] |
O. Mironenko, H. Banaee and A. Loutfi. Evaluation of Human Interaction with Fleets of Automated Vehicles in Dynamic Underground Mining Environments. In Agents and Robots for reliable Engineered Autonomy : 4th Workshop, AREA 2024, Santiago de Compostela, Spain, October 19, 2024, Proceedings, pages 54-72, 2024 [ BibTeX | DiVA ] |
| [2] |
H. Banaee, F. Klügl, F. Novakazi and S. Lowry. Intention Recognition and Communication for Human-Robot Collaboration. In CEUR Workshop Proceedings, 3825:101-108, 2024 [ BibTeX | DiVA ] |
| [3] |
E. Gutiérrez Maestro, H. Banaee and A. Loutfi. Towards Addressing Label Ambiguity in Sequential Emotional Responses Through Distribution Learning. In 12th International Conference on Affective Computing and Intelligent Interactions, Glasgow, United Kingdom, September 15-18, 2024 2024 [ BibTeX | DiVA ] |
| [4] |
S. S. V. Kalidindi, H. Banaee, H. Karlsson and A. Loutfi. Indoor temperature prediction with context-aware models in residential buildings. Building and Environment, 244, 2023 [ BibTeX | DiVA ] |
| [5] |
E. Gutiérrez Maestro, H. Banaee and A. Loutfi. Stress Lingers : Recognizing the Impact of Task Order on Design of Stress and Emotion Detection Systems. In 2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology, pages 175-176, 2023 [ BibTeX | DiVA | PDF ] |
| [6] |
S. S. V. Kalidindi, H. Banaee and A. Loutfi. Transformers and Contextual Information in Temperature Prediction of Residential Buildings for Improved Energy Consumption. 2022 [ BibTeX | DiVA | PDF ] |
| [7] |
H. Banaee, G. Chimamiwa, M. Alirezaie and A. Loutfi. Explaining Habits and Changes of Activities in Smart Homes. 2020 [ BibTeX | DiVA | PDF ] |
| [8] |
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, 2019 [ BibTeX | DiVA ] |
| [9] |
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, 2018 [ BibTeX | DiVA | PDF ] |
| [10] |
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, 2018 [ BibTeX | DiVA | PDF ] |
| [11] |
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, 2015 [ BibTeX | DiVA ] |
| [12] |
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, 2015 [ BibTeX | DiVA ] |
| [13] |
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) 2015 [ BibTeX | DiVA | PDF ] |
| [14] |
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, 2015 [ BibTeX | DiVA | PDF ] |
| [15] |
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, 2014 [ BibTeX | DiVA | PDF ] |
| [16] |
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, 2013 [ BibTeX | DiVA ] |
| [17] |
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, 2013 [ BibTeX | DiVA | PDF ] |
| [18] |
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, 2013 [ BibTeX | DiVA | PDF ] |
| [19] |
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, 2013 [ BibTeX | DiVA | PDF ] |
