Srimit Sritik Das

About

Srimit Sritik Das is a leading researcher in the intersection of artificial intelligence and biomedical signal processing, with a primary focus on human emotion recognition using electroencephalography (EEG). His most influential work, a 2022 study on "CNN and LSTM based ensemble learning for human emotion recognition using EEG recordings," has garnered 170 citations, establishing him as a key contributor to affective computing. Das pioneered the integration of convolutional neural networks (CNNs) and long short-term memory (LSTM) networks to decode emotional states from brainwave data, achieving unprecedented accuracy in classifying emotions like happiness, sadness, and stress. This ensemble approach not only advanced real-time emotion detection but also opened new pathways for brain-computer interfaces and mental health monitoring. His research is widely cited in fields ranging from human-computer interaction to clinical neuroscience, reflecting its practical impact on developing empathetic AI systems. Das’s work continues to inspire students and researchers exploring how deep learning can bridge the gap between neural signals and emotional understanding.

Research Focus

Key Achievements

Top Papers

1. 1
   CNN and LSTM based ensemble learning for human emotion recognition using EEG recordings

   170 citations · 2022

Key Collaborators

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