Alia Karim Abdul Hassan
Papers
13
Total Citations
186
H-Index
6
About
Alia Karim Abdul Hassan is a researcher whose work sits at the dynamic intersection of artificial intelligence, human-robot interaction (HRI), and multimodal signal processing. Her research spans emotion recognition, speaker profiling, bio-signal analysis, and adaptive robotics — areas she has shaped through both novel methodologies and comprehensive survey contributions. Hassan's most influential work, a 2019 study on graph mining-based facial emotion recognition (53 citations), introduced an innovative approach to interpreting emotional states from complex graph-structured data, addressing a critical challenge in making robots more socially responsive. Her complementary surveys on emotion recognition and voice-based interfaces for HRI (36 and 25 citations, respectively) have become valuable reference points for researchers entering these fields. Beyond emotion, Hassan has made significant strides in automatic speaker profiling, proposing CatBoost-driven methods for age and gender recognition from short speech utterances (20 citations) and conducting systematic reviews of multimodal estimation techniques (17 citations). Her more recent investigations into EEG/EMG-based upper limb movement recognition further demonstrate her commitment to assistive and rehabilitative technologies. With a growing body of work consistently cited across AI and robotics communities, Hassan stands as a productive and wide-ranging contributor to intelligent human-machine interaction research.
Research Focus
Key Achievements
Top Papers
- 1A novel facial emotion recognition scheme based on graph mining53 citations · 2019
- 2A Review on Voice-based Interface for Human-Robot Interaction36 citations · 2020
- 3A Survey on Emotion Recognition for Human Robot Interaction25 citations · 2021
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- 7Review of Automatic Speaker Profiling: Features, Methods, and Challenges5 citations · 2023
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- 10A survey on bio-signal analysis for human-robot interaction4 citations · 2022