Nooshin Haji Ghassemi
Nooshin Haji Ghassemi, M. Sc.

Alumnus
Carl-Thiersch-Straße 2b
91052 Erlangen
Department Artificial Intelligence in Biomedical Engineering (AIBE)
Lehrstuhl für Maschinelles Lernen und Datenanalytik
Carl-Thiersch-Straße 2b
91052 Erlangen
- Phone number: +49 9131 85-20286
- Email: nooshin.haji@fau.de
- Website: https://www.mad.tf.fau.de/person/nooshin-haji-ghassemi/
Nooshin’s Research Focus
My research entails designing, developing and implementing machine learning (ML) and deep learning (DL) methods for analysing Parkinsonian gait. I have been also involved in creating and teaching of several university level courses related to ML/DL models and optimisation methods.
Since 2015 | PhD Candidate in the Machine Learning and Data Analytics Lab at the Friedrich-Alexander-University Erlangen-Nüremberg, Germany |
2013 – 2014 | Researcher at Blekinge Institute of Technology, Sweden |
10.2012 – 06.2013 | Master thesis at Technical University of Darmstadt, Germany |
2010 – 2012 | M.Sc. degree in Computer Science at Blekinge Institute of Technology, Sweden |
2007 – 2009 | Software Developer |
2002 – 2006 | B.Sc. degree in Computer Science at the Ferdowsi University, Iran |
2019
- Haji Ghassemi N., Hannink J., Roth N., Gaßner H., Marxreiter F., Klucken J., Eskofier B.:
Turning analysis during standardized test using on-shoe wearable sensors in parkinson’s disease
In: Sensors 19 (2019), Article No.: 3103
ISSN: 1424-8220
DOI: 10.3390/s19143103
BibTeX: Download - Nguyen A., Roth N., Haji Ghassemi N., Hannink J., Seel T., Klucken J., Gaßner H., Eskofier B.:
Correction to: Development and clinical validation of inertial sensor-based gait-clustering methods in Parkinson's disease (J Neuroeng Rehabil (2019) 16:77 DOI: 10.1186/s12984-019-0548-2)
In: Journal of neuroEngineering and rehabilitation 16 (2019), Article No.: 98
ISSN: 1743-0003
DOI: 10.1186/s12984-019-0567-z
BibTeX: Download - Nguyen A., Roth N., Haji Ghassemi N., Hannink J., Seel T., Klucken J., Gaßner H., Eskofier B.:
Development and clinical validation of inertial sensor-based gait-clustering methods in Parkinson's disease
In: Journal of neuroEngineering and rehabilitation 16 (2019)
ISSN: 1743-0003
DOI: 10.1186/s12984-019-0548-2
BibTeX: Download
2018
- Haji Ghassemi N., Hannink J., Martindale C., Gaßner H., Müller M., Klucken J., Eskofier B.:
Segmentation of Gait Sequences in Sensor-Based Movement Analysis: A Comparison of Methods in Parkinson's Disease.
In: Sensors 18 (2018)
ISSN: 1424-8220
DOI: 10.3390/s18010145
BibTeX: Download - Haji Ghassemi N., Hannink J., Martindale C., Gaßner H., Müller M., Klucken J., Eskofier B.:
Segmentation of Gait Sequences in Sensor-Based Movement Analysis: A Comparison of Methods in Parkinson’s Disease
In: Sensors (2018)
ISSN: 1424-8220
DOI: 10.3390/s18010145
URL: http://www.mdpi.com/1424-8220/18/1/145
BibTeX: Download
2016
- Haji Ghassemi N., Marxreiter F., Pasluosta CF., Schlachetzki J., Schramm A., Eskofier B., Klucken J.:
Combined Accelerometer and EMG Analysis to Differentiate Essential Tremor from Parkinson’s Disease
38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society of the IEEE Engineering in Medicine and Biology Society EMBC'16 (Orlando)
In: 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society of the IEEE Engineering in Medicine and Biology Society EMBC'16 2016
BibTeX: Download
2014
- Haji Ghassemi N., Deisenroth M.:
Analytic long-term forecasting with periodic Gaussian processes
Proc. of AISTATS
In: Proc. of AISTATS 2014
BibTeX: Download
2013
- Berger E., Vogt D., Haji Ghassemi N., Jung B., Ben Amor H.:
Inferring guidance information in cooperative human-robot tasks
Humanoid Robots (Humanoids), 2013 13th IEEE-RAS International Conference on
In: Inferring guidance information in cooperative human-robot tasks 2013
BibTeX: Download
- Machine Learning for Engineers (Summer 2020)
- Machine Learning for Time Series Exercises (Winter 2019/20)
- Machine Learning for Time Series Exercises (Winter 2018/19)
- Pattern Recognition Exercises (Winter 2016/17)
- Pattern Recognition Exercises (Winter 2015/16)
Funding Agencies and Collaborators