Navigation

An Nguyen, M. Sc.

Department of Computer Science
Lehrstuhl für Informatik 14 (Maschinelles Lernen und Datenanalytik)

Room: Room 01.015
Carl-Thiersch-Straße 2b
91052 Erlangen

LinkedIn GoogleScholar ORCID ResearchGate

 

Since 10/2018 Researcher and Ph.D. Student

Machine Learning and Data Analytics Lab, Germany

Department of Computer Science, Friedrich-Alexander-University Erlangen-Nuernberg (FAU)
05/2017 – 08/2017 Vistiting Student and Research Assistant

Frankel Cardiovascular Center in cooperation with the Biomedical & Clinical Informatics Lab

University of Michigan, USA
09/2016 –  04/2017 MSE Electrical and Computer Engineering

University of Michigan, USA

Project Lead at M-HEAL
04/2016 – 09/2018 MSc Electrical Engineering

Technical University of Berlin, Germany

Student researcher at the Control Systems Group
08/2014 – 06/2015 International Student

KTH Royal Institute of Technology, Sweden
10/2011 – 03/2016 BSc Electrical Engineering

Technical University of Berlin, Germany

Tutor at the Institute of Mathmatics

Student researcher at the High Voltage Engineering lab and Control Systems Group

Working student at Vattenfall Europe Netzservice Gmbh

Machine Learning for Predictive Analytics

Process Mining

2019

  • Nguyen, An, Nils Roth, Nooshin Haji Ghassemi, Julius Hannink, Thomas Seel, Jochen Klucken, Heiko Gassner, and Bjoern M. Eskofier. 2019. “Development and Clinical Validation of Inertial Sensor-Based Gait-Clustering Methods in Parkinson’s Disease.” Journal of NeuroEngineering and Rehabilitation 16 (1): 77.
    DOI: https://doi.org/10.1186/s12984-019-0548-2

2018

  • Nguyen, A., S. Ansari, M. Hooshmand, K. Lin, H. Ghanbari, J. Gryak, and K. Najarian. “Comparative Study on Heart Rate Variability Analysis for Atrial Fibrillation Detection in Short Single-Lead ECG Recordings.” In 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 526–29, 2018.

Summer 2020 Machine Learning and Data Analytics for industry 4.0
Winter 2019/20 Machine Learning and Data Analytics for industry 4.0
Summer 2019 Machine Learning and Data Analytics for industry 4.0

If you are interested in any of the topics below, kindly send me your CV, Transcript of Records from meinCampus and brief description of experience and motivation.

The exact work packages and scope of the work can be defined on an individual basis.

I am also happy to discuss other topics with you and to supervise potential guest students.

Scope

[M] = More suited for a Master’s Thesis
[P] = More suited for a Project
[I] = Implementation Task (for Computer Science “Master Project” or Medical Engineering “Research Internship” (Forschungspraktikum))
[W] = Working Student/HiWi

2023 I/P/M “Mixed-Type and Irregularly Sampled Time Series Analysis” – Such data includes for example electronic health records (EHR) or combined sensor and event log data. Tasks include the extension of RNN architectures to deal with such data efficiently. Deep Learning, Machine Learning, Time Series Analysis
1915 I/P/M Deep Learning for Anomaly Detection Deep Learning,

Time Series Analysis
1916 I/P/M Deep Learning for Data Augmentation Deep Learning,

Time Series Analysis
1917 I/P/M Conformance Checking for Medical Processes Process Mining,

Data & Process Science
J1902 W (+ M) Working Student (potentially with follow up Master Thesis) at Siemens Healthineers – Computed Tomography (Data Analytics for non-image data) Research & Development
J1903 W (+ M) Working Student (potentially with follow up Master Thesis) at Siemens Healthineers – Predictive Maintenance (Computed Tomography + Customer Service) Research & Development
J1904 W Student researcher helping with topics in the field of Deep Learning or/and Process Mining Research

 

 

Partners & Funding Agencies