Computer Science Colloquia
Wednesday, April 3, 2013
Host: Gabe Robins
3:30 PM, Rice Hall, Room 130 (auditorium), followed by a reception in Rice Hall Fourth Floor Atrium (west end)
Machine Learning for Big Data in Biomedicine
As one of the most exciting multi-disciplinary research
fields, biomedical data analytics has seen dramatic growth over the past
decade, especially with respect to newly available data. This
rapidly-growing resource has posted many interesting new challenges for
machine learning since biomedical data are often noisy, complex,
relationally structured and highly diverse. In this talk, I will present
a number of machine learning approaches we have proposed, including
semi-supervised learning, multi-task learning, feature learning, deep
learning, etc., to handle different types of data complexities that are
urgent to be addressed in biomedical domain.
Biosketch: Yanjun Qi is a research staff member working in the Machine Learning Department at NEC Labs America. Her research interests focus on developing and applying machine learning techniques on real-world data analytics problems. Yanjun obtained her Ph.D. degree from School of Computer Science at Carnegie Mellon University in 2008 and received her Bachelor degree with high honors from Computer Science Department at Tsinghua University, Beijing. She co-chaired the "NIPS Machine Learning in Computational Biology" workshop from 2009 to 2011. She has also served as journal special issue editor, session chair, program committee and reviewers on multiple renowned international conferences & journals (e.g., NIPS, JMLR, EMNLP).