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Tuesday, February 2 2021
11:00am - 12:00pm
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Kristen Peres

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CSE Seminar with University of Illinois at Urbana-Champaign Ph.D. student Yunan Luo

Name: Yunan Luo

Date/Time: Tuesday, February 2 at 11:00 am


Presentation title: Machine learning for large- and small-data biomedical discovery

Abstract: In modern biomedicine, the role of computation becomes more crucial in light of the ever-increasing growth of biological data, which requires effective computational methods to integrate them in a meaningful way and unveil previously undiscovered biological insights. In this talk, I will discuss my research on machine learning for large- and small-data biomedical discovery. First, I will describe a representation learning algorithm for the integration of large-scale heterogeneous data to disentangle out non-redundant information from noises and to represent them in a way amenable to comprehensive analyses; this algorithm has enabled several successful applications in drug repurposing. Next, I will present a deep learning model that utilizes evolutionary data and unlabeled data to guide protein engineering in a small-data scenario; the model has been integrated into lab workflows and enabled the engineering of new protein variants with enhanced properties. I will conclude my talk with future directions of using data science methods to assist biological design and to support decision making in biomedicine.

Bio: Yunan Luo ( is a Ph.D. student advised by Prof. Jian Peng in the Department of Computer Science, University of Illinois at Urbana-Champaign. Previously, he received his Bachelor’s degree in Computer Science from Tsinghua University in 2016. His research interests are in computational biology and machine learning. His research has been recognized by a Baidu Ph.D. Fellowship and a CompGen Ph.D. Fellowship.