Dr. Mehrdad Mahdavi

Associate Professor

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Biography

Mehrdad Mahdavi is an Associate Professor in the School of Electrical Engineering and Computer Science at Pennsylvania State University. His research focuses on various aspects of data science and artificial intelligence, including large-scale optimization, high-dimensional learning, convex and non-convex optimization, and statistical computational learning theory. He has published numerous articles in prestigious journals and conferences, contributing significantly to the fields of machine learning and data analysis. With experience as a research assistant professor in machine learning at the Toyota Technological Institute at the University of Chicago, he has a strong background in both theoretical and applied aspects of optimization and machine learning. His work includes exploring distributed optimization and online (adversarial) learning, with applications to machine learning in social graphs, recommender systems, and text analysis. He has received several awards for his research, including the NSF CAREER Award, recognizing his contributions and potential in the field of electrical engineering and computer science.

Research Interests

Experience

Associate Professor

— Present

Pennsylvania State University • University Park, PA

Teaching and conducting research in the School of Electrical Engineering and Computer Science.

Awards

#

NSF CAREER Award

#

Mark Fulk Student Paper Award

2012-07-01
#

Top Cited Paper Award

Requirements for Pennsylvania State University

Doctorate Program
Requirements
GPA Requirement
Required:3
TOEFL
Writing
Required:24
Speaking
Required:23
Total
Required:100
IELTS
Writing
Required:7
Speaking
Required:7
Overall
Required:7
GRE General
Prerequisites
Master's degree in related field for PhD Baccalaureate degree from accredited institution
Application Checklist
  • Three letters of recommendation
  • Statement of Purpose
  • Writing Sample
  • Official Transcripts
  • Resume/CV
Specialization Notes

GRE scores are highly recommended but not strictly required for Applied Linguistics.