The Shanghai AI/ML Group from MSRA Shanghai focuses on research areas related to machine learning and its application. For machine learning research, we are interested to fundamental deep learning techniques including neural network architecture design, graph neural network, sequential learning, reinforcement learning, vector graphics recognition and domain-specific language and speech processing. For machine learning applications, we are interested to solving real-world problems in healthcare and sustainability areas, such as pathological speech/language/behavior analysis, bio-medical signal processing, bio-medical knowledge graph mining and genomics sequences analysis. 

Advanced Machine Learning

• Bio-inspired neural network for general-purpose machine learning
• Graph neural network for temporal dynamics, interpretability, and anomaly detection
• Computer vision for vector graphics, ensemble learning, and domain adaptation/generalization
• Sequential learning, reinforcement learning and decision making for real-world applications
• Fundamental technologies for language generation and domain-specific NLP applications

Machine Learning for Healthcare

• Speech recognition for patients with speech pathology
• Time series modelling and analysis for bio-medical signals
• Bio-medical knowledge graph learning for biomedicine and pharmacotherapy
• Machine learning for transcriptomics and genomics sequences
• Pathological behavior detection for autism and neurocognitive disease