Vasant Honavar

Vasant
Honavar

Huck Chair in Biomedical Data Sciences and Artificial Intelligence ,
Director of the Artificial Intelligence Research Lab

Expertise:

  • Internet & Technology

Focus Areas:

  • Artificial Intelligence
  • Big Data
  • Machine Learning

About

  • More than three decades of artificial intelligence research
  • Published more than 250 peer-reviewed research papers, which have been cited at least 16,000 times
  • Led the establishment of Penn State’s Center for Artificial Intelligence Foundations and Scientific Applications and the Center for Big Data Analytics and Discovery Informatics

Vasant Honavar is the Dorothy Foehr Huck and J. Lloyd Huck Chair in Biomedical Data Sciences and Artificial Intelligence and director of the Artificial Intelligence Research Lab at Penn State. He has more than three decades of academic experience in the field of AI. Specifically, Honavar’s areas of research interest include machine learning, causal inference and knowledge representation, as well as computer science, data sciences, cognitive and brain sciences and applied informatics (particularly bioinformatics and health informatics). His work in these areas has been foundational, with more than 250 peer-reviewed publications, which have been cited at least 16,000 times.

In addition to directing the AI Research Lab, Honavar led the establishment of Penn State’s Center for Artificial Intelligence Foundations and Scientific Applications and the Center for Big Data Analytics and Discovery Informatics. He can offer expertise and answer questions on a wide range of questions regarding AI and informatics, including how predictive models can be built from “big data” and how to build AI systems that are fair, explainable and accountable.

In The Media

How Artificial Intelligence Is Totally Changing Everything

from HowStuffWorks December 20, 2019

"A machine might be good at some diagnoses in radiology, but if you ask it about baseball, it would be clueless."

Using data to better understand climate change

from National Science Foundation August 23, 2016

"The Nature Climate Change piece provides a hint of how sophisticated data-mining methods could help fill gaps in our understanding of climate change."

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