Monitoring real-time personal locomotion behaviors over smart indoor-outdoor environments via body-worn sensors
67 citations
Q1 Journal
I turn data, models, and ideas into impactful research
A researcher specializing in AI and machine learning, with expertise in predictive modeling, statistical modelling, sports analytics, and deep learning. My impactful research, published in leading journals such as IEEE, Springers, Wiley, CMC, and PeerJ, has attained over 530 citations, reflecting significant academic and practical contributions.
Areas of expertise and ongoing research initiatives
Leveraging AI and machine learning to uncover insights in image, video, signal, and sports data. Developing novel algorithms for pattern recognition and predictive analytics.
Investigating machine learning applications in healthcare data analytics, with a focus on predictive modelling, patient outcomes, and diagnostic assistance systems.
Utilizing advanced statistical methods for data analysis and interpretation to inform decision-making processes in various sectors including sports and IoT.
Quantitative overview of academic contributions and influence
Research-driven implementations with open-source code
A comprehensive smart home dataset using triaxial IMU sensors for human activity recognition. Features 11 different activities captured from wrist, chest, and thigh regions.
Advanced fraud detection system using LSTM neural networks for real-time transaction analysis. Features multiple risk factors and user behavior pattern recognition.
CAPSULE is a modular smart home framework leveraging context-aware reasoning and predictive control for real-time IoT device automation and behavior prediction.
Peer-reviewed research in leading journals and conferences
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