New Faculty Join the School of Computational Science and Engineering

CSE New Faculty Fall 2019

Three new faculty members are set to join the School of Computational Science and Engineering (CSE) this year. The trio come from a diverse research background including the areas of computational biology, data science, and machine learning. 

 

Headshot of Elizabeth Cherry in a bright pink shirt in front of grey background

Elizabeth Cherry

Associate Professor

Cherry joined CSE this month after teaching at the School of Mathematical Sciences at the Rochester Institute of Technology. While at the Rochester Institute, she found her researching stride in computational biology with a focus on cardiac electrophysiology and arrhythmias. 

According to Cherry, “Sudden death is secondary to ventricular fibrillation and remains a leading cause of mortality in the United States. And the occurrence of atrial fibrillation, which is responsible for about 15 percent of all strokes, continues to rise.”

In efforts to address this issue, Cherry utilizes mathematical modeling and simulation of the electrical dynamics of cardiac cells and tissue. This field of research is highly interdisciplinary and requires expertise in a number of sub-fields, including modeling, computational algorithms, scientific applications, and advanced interactive visualization. 

She has won numerous awards and recognitions for her work in this field, including:

  • Recipient of Trustees Scholarship Award, Rochester Institute of Technology, 2019
  • Recipient of the Outstanding Student Mentor Award, Rochester Institute of Technology, College of Science, 2016
  • Recipient of the Outstanding Faculty of the Year Award, Rochester Institute of Technology, College of Science 2013

 

Headshot of Srijan Kumar in front of pillars‚Äč

Srijan Kumar

Assistant Professor

Kumar will join CSE in January 2020 after working as a postdoctoral researcher in the Computer Science Department at Stanford University where he specializes in machine learning and data science with applications in social media, graph mining, cybersecurity, and social computing.

His research group currently focuses on machine learning for the web, creating network science, data science, and social computing models with the goal of enabling useful, safe, and trustful cyberspaces.

According to Kumar, “Our models extract knowledge from complex interactions between multimodal entities, such as users and content, in web-scale online social systems for better decision making. Our trust, safety, and integrity models are being used at major tech companies, including Wikipedia, Reddit, and Flipkart. Our research has also been widely covered by the popular press, including CNNThe Wall Street JournalWired, and New York Magazine.” 

Kumar has won several distinguishing honors for his research in these areas, including:

  • ACM SIGKDD Doctoral Dissertation Award runner up, 2018
  • Dr. Larry S. Davis Doctoral Dissertation Award, 2018
  • ACM International World Wide Web Conference best paper award runner-up, 2017

 

Headshot of Xiuwei Zhang in front of chalkboard

Xiuwei Zhang

Assistant Professor

Zhang joined CSE on Aug. 1 after working as a postdoctoral researcher in the Electrical Engineering and Computer Sciences Department at the University of California at Berkeley. Zhang’s research focuses on data science, method development, and data analysis with an emphasis on computational biology.

While at Berkeley, her time centered on two different projects, each using single-cell sequencing. One project, called SymSim, published in the Nature Communications journal, developed a simulator to model processes observed during single cell RNA sequencing experiments. 

According to Zhang, the SymSim simulates single cell RNA data which allows researchers to benchmark various computational methods.

“What we really want to understand is what is controlling all the changes in the cells and track their differences,” she said. “On a mechanism level, we need to not only look at the RNA sequencing data but also integrate other types of data such as protein analysis.”

Zhang has won several distinguishing awards in the areas of computational biology and data anlysis, including:

  • Swiss National Science Foundation (SNSF) Fellowship for Prospective Researchers, 2012
  • SNSF Advanced Postodc Mobility Fellowship, 2014
  • Simons-Berkeley Research Fellowship, 2016

 

[Related News: ML@GT to Welcome Seven New Faculty Members]

 

Contact: 

Kristen Perez

Communications Officer