Dr. Richard Zemel

Professor

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Biography

Richard Zemel is the Trianthe Dakolias Professor of Engineering and Applied Science in the Department of Computer Science at Columbia University. He has broad research interests including machine learning, artificial intelligence, statistics, neuroscience, and cognitive science. Dr. Zemel is the director of the new National Science Foundation Artificial Intelligence Institute, ARtificial Natural Intelligence (ARNI). His recent research pursuits include robust AI, few-shot learning, algorithmic fairness, and continual learning. He teaches various courses related to machine learning and deep learning, demonstrating a commitment to incorporating the latest advancements in these fields into his curriculum. Throughout his career, he has published numerous influential papers and contributed significantly to advancing the understanding of AI and its applications in various domains.

Research Interests

Machine Learning Artificial Intelligence Statistics Neuroscience Cognitive Science Robust AI Few-Shot Learning Algorithmic Fairness Continual Learning

Experience

Trianthe Dakolias Professor of Engineering and Applied Science

2016-08-01 — Present

Columbia University • New York, NY

Richard Zemel is a renowned researcher in the field of AI and machine learning, significantly contributing to both theoretical advancements and practical applications.

Courses

Neural Networks and Deep Learning Fair & Robust Algorithms Self Supervised Learning Introduction to Machine Learning Machine Learning Data Mining Probabilistic Graphical Models AI Ethics: Mathematical Foundations and Algorithms Computational Neuroscience

Requirements for Columbia University

Doctorate Program
Requirements
GPA Requirement
Required:3
TOEFL
Total
Required:100
IELTS
Overall
Required:7.5
Prerequisites
Bachelor's degree or international equivalent
Application Checklist
  • Online application
  • Transcripts
  • Statement of Academic Purpose
  • Personal Statement
  • Three letters of recommendation
  • CV or Resume
  • Application fee
Specialization Notes

Department of Anthropology (GSAS)