Manoj Ramanathan

Dr. Manoj Ramanathan

orcid

Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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12 June 2019
Verified
Book Chapter
Closed access
PDF file
MRManoj Ramanathan
Manoj Ramanathan
NMNidhi Mishra
Nidhi Mishra
NTNadia Magnenat Thalmann
Nadia Magnenat Thalmann

8 August 2023
Verified
Conference Paper
Open access
MRManoj Ramanathan
Manoj Ramanathan
LLLincong Luo
Lincong Luo
MFMing Jeat Foo
Ming Jeat Foo
CCChye Hsia Chiam
Chye Hsia Chiam
WYWei-Yun Yau
Wei-Yun Yau
WAWei Tech Ang
Wei Tech Ang

1 May 2025 in IEEE Robotics and Automation Letters
Verified
Journal Article
Closed access
KTKuan Yuee Tan
Kuan Yuee Tan
NGNeha Priyadarshini Garg
Neha Priyadarshini Garg
MRManoj Ramanathan
Manoj Ramanathan
WAWei Tech Ang
Wei Tech Ang

26 June 2025 in Robotics and Autonomous Systems
Verified
Journal Article
Closed access
NGNeha Priyadarshini Garg
Neha Priyadarshini Garg
MLMarcus Leong
Marcus Leong
MRManoj Ramanathan
Manoj Ramanathan
WPWee-Ching Pang
Wee-Ching Pang
LLLei Li
Lei Li
WAWei Tech Ang
Wei Tech Ang

16 June 2022
Verified
Book Chapter
Closed access
PDF file
MRManoj Ramanathan
Manoj Ramanathan
ASAalind Singh
Aalind Singh
ASArathy Suresh
Arathy Suresh
DTDaniel Thalmann
Daniel Thalmann
NMNadia Magnenat-Thalmann
Nadia Magnenat-Thalmann

30 May 2019 in arXiv
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Preprint
Open access
PDF file
NMNidhi Mishra
Nidhi Mishra
MRManoj Ramanathan
Manoj Ramanathan
RSRanjan Satapathy
Ranjan Satapathy
Erik CambriaErik Cambria
Erik Cambria
NMNadia Magnenat-Thalmann
Nadia Magnenat-Thalmann
Hiring robots for the workplaces is a challenging task as robots have to cater to customer demands, follow organizational protocols and behave with social etiquette. In this study, we propose to have a humanoid social robot, Nadine, as a customer service agent in an open social work environment. The objective of this study is to analyze the effects of humanoid robots on customers at work environment, and see if it can handle social scenarios. We propose to evaluate these objectives through two modes, namely, survey questionnaire and customer feedback. We also propose a novel approach to analyze customer feedback data (text) using sentic computing methods. Specifically, we employ aspect extraction and sentiment analysis to analyze the data. From our framework, we detect sentiment associated to the aspects that mainly concerned the customers during their interaction. This allows us to understand customers expectations and current limitations of robots as employees.