Papers

9

Total Citations

180

H-Index

7

About

Celia Shahnaz is a pioneering researcher in speech processing, affective computing, and assistive robotics, whose work bridges artificial intelligence and real-world humanitarian applications. Her most impactful contribution is in speech-emotion recognition, where she developed a convolutional neural network (CNN)-based system (69 citations) that analyzes vocal cues to detect emotional states—a technology with critical implications for cybersecurity and human-computer interaction. She has also advanced autonomous systems for social good, including an object-detection-driven trash collector (31 citations) and a Bangla voice-controlled rescue robot (19 citations) designed for noisy disaster environments. Her R3Diver underwater rescue robot (18 citations) and e-cane navigation system for the visually impaired (11 citations) demonstrate her commitment to low-cost, accessible solutions. Shahnaz’s work on eye-gaze-controlled robotic cars (7 citations) and GPS-guided autonomous transporters (7 citations) further showcases her versatility in deep learning and robotics. With over 180 total citations across her top papers, she is recognized for integrating cutting-edge AI with practical assistive and disaster-response technologies, making her a leading figure in engineering for societal impact.

Research Focus

Key Achievements

7
H-Index
9
Papers
180
Total Citations
20
Avg Citations/Paper
🏆 Most Cited Paper
Convolutional Neural Network (CNN) Based Speech-Emotion Recognition
69 citations · 2019
📈 Most Prolific Year: 2017 (3 Papers)
🤝 Key Collaborators: 35
🏛 Institutions: Bangladesh University of Engineering and Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago