Bio

Dr. Shekhar Singh is an Assistant Professor of Computer Science at the University of South Carolina Lancaster. He earned his Ph.D. in Computer Science from the University of Nevada, Las Vegas, in 2023 and previously received an M.S. in Software Systems from the Birla Institute of Technology and Science (BITS), Pilani, India.

Dr. Singh's research focuses on artificial intelligence, machine learning, deep learning, computer vision, and generative AI, with an emphasis on developing intelligent systems for healthcare. His work integrates biomedical signals, medical imaging, and clinical data to improve disease prediction, risk assessment, and clinical decision support.

Before joining USC Lancaster, Dr. Singh was a Postdoctoral Research Fellow at Wake Forest University School of Medicine, where he developed AI models using electrocardiograms (ECGs), medical imaging, and multimodal clinical data to advance cardiovascular disease detection and risk prediction. His research has contributed to the early identification of heart failure with preserved ejection fraction (HFpEF) and the prediction of atrial fibrillation risk.

Dr. Singh has published peer-reviewed research in artificial intelligence and biomedical informatics. He teaches undergraduate computer science courses and enjoys mentoring students interested in artificial intelligence and machine learning. He welcomes opportunities to collaborate with researchers, clinicians, and industry partners on interdisciplinary projects that use AI to address real-world challenges.

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Selected Publications:

• Karabayir, I., Singh, S., et al. “An Artificial Intelligence Model for ECG-Based Prediction of Heart Failure with Preserved Ejection Fraction Diagnosis.” Journal of Cardiovascular Development and Disease, 2026. https://doi.org/10.3390/jcdd13070340
• Singh, S., & Nasoz, F. Facial Expression Recognition Using CNNs and GANs: A Study on Classification and Generation of Synthetic Images. International Journal of Information Technology, 2025. https://doi.org/10.1007/s41870-025-02521-0
• Singh, S., & Nasoz, F. Facial Expression Recognition with Convolutional Neural Networks. Proceedings of the IEEE 10th Annual Computing and Communication Workshop and Conference (CCWC), 2020. https://doi.org/10.1109/CCWC47524.2020.9031283

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Research Areas:

• Artificial Intelligence
• Machine Learning & Deep Learning
• Computer Vision
• Generative AI & Large Language Models
• AI for Healthcare and Real-World Applications