Applications of Statistical and Machine Learning Methods in Spatial Transcriptomics
Online in Zoom
Online in Zoom

The Department of Biostatistics is excited to announce our "Alumni of the Month" brown bag featuring 2005 graduate, Mingyao Li, PhD. From Dr. Li: I was trained as a statistical geneticist at the University of Michigan, but since I joined the faculty at the University of Pennsylvania, I have gradually transitioned my research from traditional statistical genetics to statistical genomics with the goal of having a deeper understanding of the molecular mechanism of human diseases. The central theme of my current research is to use statistical and machine learning methods to understand cellular heterogeneity in human-disease-relevant tissues, to characterize gene expression diversity across cell types, to study the patterns of cell state transition and crosstalk of various cells using data generated from single-cell and spatial transcriptomics studies, and to translate these findings into the clinics. In addition to methods development, I am also interested in collaborating with researchers seeking to identify complex disease susceptibility genes and acting cell types. At UPenn, I serve as the Director of Biostatistics for the Gene Therapy Program, where I advise biostatistics and bioinformatics analysis for various gene therapy studies. I also chair the Graduate Program in Biostatistics, and I have found the interactions with graduate students to be very rewarding. Talk title: Applications of statistical and machine learning methods in spatial transcriptomics.

Passcode: 705190

Applications of Statistical and Machine Learning Methods in Spatial Transcriptomics

Mingyao Li, PhD

icon to add this event to your google calendarAugust 19, 2021
12:00 pm - 1:00 pm
Online in Zoom
Online URL: https://umich.zoom.us/j/97364781928
Contact Information: Mandi Larson, larsoama@umich.edu

The Department of Biostatistics is excited to announce our "Alumni of the Month" brown bag featuring 2005 graduate, Mingyao Li, PhD. From Dr. Li: I was trained as a statistical geneticist at the University of Michigan, but since I joined the faculty at the University of Pennsylvania, I have gradually transitioned my research from traditional statistical genetics to statistical genomics with the goal of having a deeper understanding of the molecular mechanism of human diseases. The central theme of my current research is to use statistical and machine learning methods to understand cellular heterogeneity in human-disease-relevant tissues, to characterize gene expression diversity across cell types, to study the patterns of cell state transition and crosstalk of various cells using data generated from single-cell and spatial transcriptomics studies, and to translate these findings into the clinics. In addition to methods development, I am also interested in collaborating with researchers seeking to identify complex disease susceptibility genes and acting cell types. At UPenn, I serve as the Director of Biostatistics for the Gene Therapy Program, where I advise biostatistics and bioinformatics analysis for various gene therapy studies. I also chair the Graduate Program in Biostatistics, and I have found the interactions with graduate students to be very rewarding. Talk title: Applications of statistical and machine learning methods in spatial transcriptomics.

Passcode: 705190