This page in English

Hadi Banaee

Tjänstetitel: Postdoktor Organisation: Institutionen för naturvetenskap och teknik

E-post:

Telefon: 019 303658

Rum: T2233

Hadi Banaee

Om Hadi Banaee

Since September 2012, I have been working towards the Ph.D degree at Örebro University, center for applied autonomous sensor systems (AASS), Örebro, Sweden. I am currently engaged in the research on the fields of data mining and health informatics. In particular, my interests include wearable sensor data mining, symbolic representation of time series, and natural language generation of numeric data. My current activity is focused on rule mining in physiological sensor data and finding a semantic model for the descriptive rules in order to exploit a symbolic representation of physiological data streams.

I received my Master degree in Computer Science from Tehran Polytechnic, Iran in 2011 in the field of Computational Geometry with studying the utility of geometrical algorithms in Bioinformatics problems, particularly gene expression clustering.

Publikationer

Artiklar i tidskrifter |  Doktorsavhandlingar, sammanläggningar |  Konferensbidrag | 

Artiklar i tidskrifter

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.
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.

Doktorsavhandlingar, sammanläggningar

Banaee, H. (2018). From Numerical Sensor Data to Semantic Representations: A Data-driven Approach for Generating Linguistic Descriptions. (Doctoral dissertation). (Sammanläggning) Örebro: Örebro University.

Konferensbidrag

Vajdi, A. , Haspel, N. & Banaee, H. (2015). A New DP Algorithm for Comparing Gene Expression Data Using Geometric Similarity. I: Proceedings 2015 IEEE International Conference on Bioinformatics and Biomedicine. Konferensbidrag vid IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2015), Washington, DC, USA, November 9-12, 2015 (ss. 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. I: Proceedings of the 8th International conference of Health Informatics (HEALTHINF 2015). Konferensbidrag vid 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. I: INTERNET OF THINGS USER-CENTRIC IOT, PT I. Konferensbidrag vid 1st International Conference on IoT Technologies for HealthCare, HealthyIoT, October 27-29, Rome, Italy, 2014 (ss. 178-186). Springer.
Banaee, H. & Loutfi, A. (2014). Using Conceptual Spaces to Model Domain Knowledge in Data-to-Text Systems. I: Proceedings of the 8th International Natural Language Generation Conference. Konferensbidrag vid 8th International Natural Language Generation(INLG)Conference, 19-21 June, Philadelphia, Pennsylvania, USA (ss. 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. I: IEEE International Conference on Systems, Man, and Cybernetics, 13-16 Oct. 2013, Manchester. Konferensbidrag vid IEEE International Conference on Systems, Man, and Cybernetics, 13-16 Oct. 2013, Manchester (ss. 3876-3881). IEEE conference proceedings.
Banaee, H. , Ahmed, M. U. & Loutfi, A. (2013). Towards NLG for Physiological Data Monitoring with Body Area Networks. I: 14th European Workshop on Natural Language Generation. Konferensbidrag vid 14th European Workshop on Natural Language Generation, Sofia, Bulgaria, August 8-9, 2013 (ss. 193-197).