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Rick Gilmore

Rick Gilmore, associate professor of psychology, will deliver the first CyberScience Seminar on reproducibility in computational research.

ICS launches CyberScience Seminar series

Posted on August 16, 2017

This fall a new, monthly seminar series from the Penn State Institute for CyberScience (ICS) will explore the frontiers of cyberscience research. The seminars, presented by Penn State faculty who use computational and big data methods in their research, are free and open to the public. ICS aims for the seminars to bring together researchers from diverse fields so they can learn from one another about new and emergent methods in high-peformance computing.

“Cyberscience is inherently interdisciplinary,” said ICS Director Jenni Evans. “No matter your field, if you do cyberscience, you can learn something from researchers in very different fields who are using similar methods and grappling with similar issues. The CyberScience Seminars will build the knowledge base of the entire cyberscience community at Penn State.”

The kick-off seminar will be held September 7 from 1:30-3:00 p.m. in 223A HUB-Robeson Center. This seminar will feature Rick Gilmore, an associate professor of psychology at Penn State. To RSVP for this seminar, click here.

Gilmore will discuss the “reproducibility crisis” in computational research. Researchers across scientific disciplines are voicing concern that many published findings may be false. But reproducing computationally intensive studies to verify their findings can be difficult. Gilmore will explore practical ways that scientists are addressing this issue.

Future seminars will explore a wide range of cutting-edge topics, including big data and fake news, forecasting student learning outcomes, and protecting data privacy. All seminars include a 30-minute lecture, an extended question-and-answer session, and time to socialize over refreshments.

Full schedule of fall and spring speakers and topics:

  • Sept. 7: The Reproducibility Crisis in Computationally-Intensive Human Behavior Research – Rick Gilmore, Dept. of Psychology
  • Oct. 5: Forecasting Student Outcomes with Machine Learning – Drew Wham, Education Technology Services
  • Nov. 2: Big Data and Fake News – Shyam Sundar, College of Communications, and Dongwon Lee, College of Information Sciences and Technology
  • Feb. 7: Learning Analytics and Individual Differences in Brain and Behavior – Ping Li, Dept. of Psychology
  • March 1: Privacy-Preserving Analysis and the MID/DLE Project – Tim Brick, Dept. of Human Development and Family Studies
  • April 4: Bayesian Modeling in the Social Sciences – Zita Oravecz, Dept. of Human Development and Family Studies

All seminars will take place in 223A HUB-Robeson Center from 1:30-3:00 p.m.


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