John Yen

Professor
Professor-in-Charge of Data Sciences and Artificial Intelligence
Faculty Affiliate, Center for Socially Responsible Artificial Intelligence

E359 Westgate Building
288 Burrowes Road
University Park, PA 16802

Email juy1@psu.edu
Phone 814-865-6174

Areas of Expertise

Artificial Intelligence
Cybersecurity
Machine Learning, Deep Representation Learning
Federated Analytics and Federated Learning
Human AI Trust and Collaboration
Knowledge Representation and Reasoning

Education

Ph.D., Computer Science, University of California, Berkeley, 1986
M.S., Computer Science, University of Santa Clara, 1982
B.S., Electrical Engineering, National Taiwan University, 1980

Websites

Dr. John Yen

I joined the College of IST at Penn State in 2001 because my research in human-AI collaboration aligns well with the college’s fresh and innovative vision. I have been fascinated by AI since I was a Ph.D. student (in computer science) at the University of California, Berkeley. I have conducted AI research in several areas:

Knowledge representation and reasoning under uncertainty (1982-2000, 2021-present)
Human-AI collaboration (1997-present), which created the R-CAST agent architecture and a related U.S. patent
AI-enabled scalable analytics using big data (2007-present)

While the emphasis of AI has shifted over my career, the vision of its impacts has grown significantly. The first thrust of my research focuses on using AI to automate decisions for problems people know how to solve (e.g., medical diagnosis). The second thrust of my research recognizes that complex problems often involve a team to collaborate, share relevant information, and make good and timely decisions. How AI can be leveraged to create “smart teammates” for people in a team became the driving question of our research. The third thrust of my research aims to discover patterns/knowledge, which people may or may not know about, by harvesting big data. One result of this line of research is the uncovering of temporal causal factors for sentiment change of cancer survivors in online cancer forums. During the past decade, I have focused on uncovering patterns from big data for enhanced cybersecurity.

Cybersecurity has been widely recognized as one of the most important grand challenges for maintaining peace and for enhancing safety and security for individuals, critical infrastructures, enterprises, and governments. However, the global proliferation of the Internet of Things (IoT) and the broad utilization of P2P communications for games, streaming services, and social media platforms have resulted in much larger attack surfaces that have been fully exploited by cyber attackers at an unprecedented rapid pace. How can AI be leveraged—together with scalable big data processing (e.g., Spark), protected research infrastructure, de-identified but linkable real-world network data—to develop scalable AI-enabled analytics so that we can not only detect cyber threats, whether they are known or unknown (e.g., zero-day attack), early but also enable human-AI collaboration for cyber defense, leveraging knowledge distributed across organizations? Answering this use-inspired AI research question can also contribute to the foundation of AI by addressing limitations, constraints, and weakness of the current AI technology revealed by the extremely complex and dynamic cybersecurity problem domain.

Selected Research Projects

NSF CCRI Planning-C: A Community Research Infrastructure for Integrated AI-Enabled Malware and Network Data Analytics
Cancer Informatics Initiative http://cani.ist.psu.edu

Honors and Awards

Penn State Graduate Teaching and Mentoring Award, 2015
Senior Member, Association for the Advancement of Artificial Intelligence (AAAI), 2014
IBM Faculty Award, 2012
IEEE Fellow, 2000
NSF Young Investigator Award, 1992

Google Scholar