Shraddha S. Kashid

MIT Art, Design and Technology University

Papers

Total Citations

H-Index

About

Shraddha S. Kashid is a forward-looking researcher at the forefront of artificial intelligence, with a primary focus on Neuro-Symbolic AI and speech emotion recognition. Her most cited work, "Neuro-Symbolic AI: A Future of Tomorrow" (2025, 10 citations), offers a visionary synthesis of neural learning and symbolic reasoning, arguing that this hybrid approach can overcome the limitations of purely data-driven or rule-based systems. By bridging deep learning’s pattern recognition with knowledge representation and logical inference, Kashid outlines a pathway toward more robust, explainable, and human-like AI—a contribution that resonates with researchers seeking to integrate reasoning into modern neural architectures. In a complementary vein, her 2024 paper "Enhancing Speech Emotion Recognition Combining Silence Elimination and Attention Model with a Novel CNN Architecture" (3 citations) demonstrates practical innovation in affective computing. Here, she introduces a custom CNN that leverages silence removal and attention mechanisms to improve emotion detection from speech, addressing real-world noise and variability. Though early in her career, Kashid’s work signals a commitment to both foundational AI theory and applied systems, positioning her as a promising voice in the evolving landscape of intelligent, context-aware technologies.