Strengthening the marriage of computation and experimentation is a goal of Peng Liu, assistant professor in Pitt’s Department of Chemistry. The Liu lab is using Pitt CRC in refining computation models as part of a research process incorporating rapid experimental feedback.
“With only computation, we can never really reproduce reality,” explains Liu. “There can be a tremendous amount of error in computation when dealing with complex chemical systems. Experimentation works with realistic systems, but it is often based on trial and error. To advance computation to guide experiments you need new computational models that incorporate experimentation. Experimentation may be trial and error, but don’t forget the importance of intuition in trial and error.”
We want to thank everyone who participated in ARC 2019 - our speakers, our guests, students who contributed to the poster session, and the many people who helped Pitt CRC to organize and publicize the event.
Tuesday, April 2, 1-4 pm. Location: 311A Schenley Place. MATLAB for basic computations, followed by discussion of different types of machine learning techniques and their workflows. The workshop will conclude with hands-on activity with real data using MATLAB Statistics and Machine Learning Toolbox. The presenter will be Elvira Osuna-Highley, PhD, senior customer success engineer at MathWorks, Inc
Introduction to Data Science with R
Wednesday, April 17, 1-4 pm. Location: 311A Schenley Place. Pitt CRC consultant Kim Wong will introduce attendees to tools for performing data science with R.
Computational flow cytometry offers new possibilities to researchers at Pitt with the acquisition of the Cytek Aurora model, which identifies thousands of cells with disease indicators per second, twice the capacity of existing technology. Pitt CRC customized data pipelines that automate the analysis.
At left, Lisa Borghesi, PhD, scientific director of the Unified Flow Core, points out the powerful lasers within the cytometer.
University faculty members obtain free access to Pitt CRC resources via a streamlined submission and proposal process. Each faculty member is automatically eligible for 10,000 compute hours (or service units) on Pitt CRC computer clusters. What does 10,000 service units mean? That is roughly the equivalent of running a laptop 24/7 for a year. And the laptop never crashing.