Titus Zaharia
Papers
3
Total Citations
145
H-Index
3
About
Titus Zaharia is a leading researcher at the intersection of affective computing, multimedia signal processing, and immersive technologies. His primary contributions lie in advancing **speech and multimodal emotion recognition**, where he has pioneered novel deep learning architectures that fuse audio and visual data. His most cited work, a 2023 paper on cross-modal audio-video fusion with attention and deep metric learning (119 citations), introduces a state-of-the-art framework for robust emotion classification by aligning heterogeneous sensory streams. Earlier, his 2021 study on utterance-level feature aggregation for speech emotion recognition (23 citations) established foundational techniques for capturing paralinguistic cues, directly impacting applications in mental health diagnosis, human behavior understanding, and e-learning. Beyond affective computing, Zaharia explores **digital twin technology** for autonomous construction, as demonstrated in his 2022 work on VR-based earthwork supervision. This research addresses critical challenges in human-machine collaboration for hazardous environments. With a citation trajectory reflecting growing interest in multimodal AI, Zaharia’s work bridges theoretical deep metric learning with real-world deployment, making him a key figure in both emotion-aware interfaces and industrial automation.
Research Focus
Key Achievements
Top Papers
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