معرفی
Md Maruf Hossain Shuvo is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Texas at El Paso (UTEP). His research focuses on artificial intelligence (AI) and edge computing, particularly in healthcare applications such as AI-driven medical decision support tools, biomedical signal/image analysis, and edge intelligence. He integrates engineering, data science, and medicine to develop hardware designs and experimental validations for cutting-edge AI algorithms.
Dr. Shuvo's expertise spans AI-enabled biomedical instrumentation, deep learning for sensors and integrated circuits, and application-specific integrated circuits. His interdisciplinary work addresses challenges in computationally intensive AI techniques, emphasizing real-time healthcare solutions. He is affiliated with UTEP's IDRE (Interdisciplinary Research and Education) and AAI (Applied Artificial Intelligence) initiatives.
His publications highlight advancements in explainable AI for hypoglycemia detection, wearable sensor data analysis, neuromorphic computing, and semiconductor device modeling. While no explicit awards are mentioned, his contributions to AI in healthcare and edge computing reflect significant academic impact. His research narrative includes collaborations on predictive analytics for glycemic control and hardware optimization for spiking neural networks. Dr. Shuvo's work also explores energy-efficient AI inference on edge devices and sensor-based plant health monitoring using VOC analysis.
