Dr. Ming Shao, assistant professor of computer and information science, is the recipient of a $498,970 National Science Foundation (NSF) CAREER award for his project "CAREER: Enabling Continual Multi-view Representation Learning: An Adversarial Perspective." The CAREER Program is the NSF's most prestigious award in support of early-career faculty who have the potential to serve as academic role models in research and education.
"Representation learning techniques attempt to extract and abstract key information (i.e., the features) from raw data to be used in analyses in a wide range of applications. As a critical step in machine learning systems, representation learning is meant to be robust in its capacity, regardless of the mutation of raw data due to noises or the variations of raw data caused by capture devices," says Shao. "In the era of big data, representation learning techniques are confronted with new challenges. Massive data collected from different sensors (e.g., the multi-view camera system) or presented in different modalities (e.g., audio-visual-text) have overloaded existing representation learning techniques."
This project will develop a robust continual representation-learning model to address these challenges. In real-world scenarios where data access is restricted (e.g., sensitive data) or the processing power of devices is limited (e.g., edge and mobile devices), stakeholders will benefit from the adaptive representation learning techniques to enable continual data analyses. The research outcomes will be leveraged to promote STEM education for K-12 students and education activities at UMass Dartmouth.
"I am grateful to receive this award to support my research in representation learning, student mentorship, and educational activities at UMass Dartmouth, and promote research collaborations and civic engagement in the South Coast of Massachusetts," says Shao.