Partha Pratim Roy

Papers

Total Citations

326

H-Index

About

Partha Pratim Roy is a leading researcher at the intersection of artificial intelligence, computer vision, and human-computer interaction. His work focuses on developing intelligent systems that can understand and interpret human behavior, with key contributions in facial expression recognition, document analysis, and brain-computer interfaces. Roy's most impactful work, "Efficient Facial Expression Recognition Algorithm Based on Hierarchical Deep Neural Network Structure" (2019), has garnered over 300 citations, establishing a foundational approach for understanding human emotional states through visual data. This work has significant implications for affective computing and human-robot interaction. Beyond facial analysis, Roy has advanced automatic document retrieval with his work on multi-lingual date field extraction, enabling more efficient processing of diverse textual documents. Most recently, he has ventured into the emerging field of brain-computer interfaces, developing novel ensemble architectures combining Stacked BLSTM-LSTM networks with Transformer models for motor activity recognition from EEG data. This work demonstrates his ability to bridge traditional computer vision techniques with cutting-edge neural network architectures. Roy's research portfolio reflects a consistent focus on making machines more perceptive of human signals—whether through facial expressions, written documents, or neural activity—pushing the boundaries of how artificial systems can interpret and respond to human intent.