TU Berlin

Quality and Usability LabBabak Naderi

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Dr. -Ing. Babak Naderi

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Research Interests:

  • Subjective quality assessment
  • Speech Quality Assessment in Crowdsourcing
  • Motivation, Workload, and Performance in Crowdsourcing
  • Statistical Modeling, field data and applied statistics
  • Speech Enhancement
  • Text Complexity and Simplification

Biography:

Babak Naderi has obtain his Dr.-Ing degree (PhD) on the basis of his thesis with a title of Motivation of Workers on Microtask Crowdsourcing Platforms in September 2017. Babak has Master's degree in Geodesy and Geoinformation Science form the Technical University Berlin with a thesis on "Monte Carlo Localization for Pedestrian Indoor Navigation Using a Map Aided Movement Model". He has also a Bachelor's degree in Software Engineering.

Since August 2012, Babak Naderi is working as a research scientist at the Quality and Usability Lab of  TU-Berlin.

2013-2015 Babak was awarded with an BMBF funded Education program for future IT and Development Leadership involving Bosch, Datev, Deutsche Telekom AG, Holtzbrinck, SAP, Scheer Group, Siemens, and Software AG  amongst highly ranked academic institution (Softwarecampus). He was taking part by leading CrowdMAQA project.

Within dissertation, Babak studies the motivation of crowdworkers in details. He has developed the Crowdwork Motivation Scale for measuring general motivation based on the Self-Determination Theory of Motivation. The scale has been validated within several studies. In addition, he has studied factors influencing the motivation, and influence of different motivation type on the quality of outcomes. Models for predicting task selection strategy of workers are developed, including models for automatically predicting expected workload associated to a task from its design, task acceptance and performance. 

Beside others research activities, Babak is actively working on the standardization of methods for speech quality assessment in crowdsourcing environment in the P.CROWD work program of Study Group 12 in ITU-T Standardization Sector.

Reviewed for WWW, CHI, ICASSP, CSCW, MMSys, PQS, HCOMP, ICWE, QoMEX, International Journal of Human-Computer Studies, Computer Networks, Behaviour & Information Technology, Quality and User Experience.

 

Selected talks:

  • "Motivation of Crowd Workers, does it matter?",Schloss Dagstuhl, Evaluation in the Crowd: Crowdsourcing and Human-Centred Experiments, November 2015.
  • "Motivation and Quality Assessment in Online Paid Crowdsourcing Micro-task Platforms",Schloss Dagstuhl, Crowdsourcing: From Theory to Practice and Long-Term Perspectives, September 2013.

 

Office Hours: On Appointment

 

Adresse:

Quality and Usability Lab

Technische Universität Berlin
Ernst-Reuter-Platz 7
D-10587 Berlin

Tel.:+49 (30) 8353-54221
Fax: +49 (30) 8353-58409

babak.naderi[at]tu-berlin.de

Publications

A Latency Compensation Technique Based on Game Characteristics to Mitigate the Influence of Delay on Cloud Gaming Quality of Experience
Zitatschlüssel sabet2020c
Autor Sabet, Saeed Shafiee and Schmidt, Steven and Zadtootaghaj, Saman and Naderi, Babak and Griwodz, Carsten and Möller, Sebastian
Buchtitel Proceedings of the 11th ACM Multimedia Systems Conference
Seiten 15–25
Jahr 2020
ISBN 9781450368452
DOI 10.1145/3339825.3391855
Ort Istanbul, Turkey
Adresse New York, NY, USA
Monat jun
Verlag Association for Computing Machinery
Serie MMSys ’20
Wie herausgegeben Fullpaper
Zusammenfassung Cloud Gaming (CG) is an immersive multimedia service that promises many benefits. In CG, the games are rendered in a cloud server, and the resulted scenes are streamed as a video sequence to the client. Using CG users are not forced to update their gaming hardware frequently, and available games can be played on any operating system or suitable device. However, cloud gaming requires a reliable and low-latency network, which makes it a very challenging service. Transmission latency strongly affects the playability of a cloud game and consequently reduces the users' Quality of Experience (QoE). In this paper, we propose a latency compensation technique using game adaptation that mitigates the influence of delay on QoE. This technique uses five game characteristics for the adaptation. These characteristics, in addition to an Aim-assistance technique, were implemented in four games for evaluation. A subjective study using 194 participants was conducted using a crowdsourcing approach. The results showed that the majority of the proposed adaptation techniques lead to significant improvements in the cloud gaming QoE.
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