Prof. Iddo Drori

Prof. Iddo Drori

I have accepted a tenure track faculty position starting Fall 2025 in NYC
as Associate Professor in the Department of Computer Science at Yeshiva University
and will be a Visiting Associate Professor at Stanford University

Research Interests Contact Me

About Me

My research focuses on artificial general intelligence, computer vision, and machine learning for education and climate science.

If you are interested in working together in my group on AGI then please send me an email about your background and research interests.

Current Position

Associate Professor of practice, Department of Computer Science, Boston University

Research Interests

Artificial General Intelligence (AGI)

Computer Vision

Machine Learning for Education

Machine Learning for Climate Science

Research Highlights

🧠

Reasoning LLMs

Diverse inference and verification by multiple models and methods significantly improves accuracy and generalization of reasoning LLMs on mathematical and coding tasks, IMO combinatorics, ARC puzzles, and HLE questions.

arXiv

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🏛

Machine Learning for Education

Neural networks that solve, explain, and generate university math problems by program synthesis and few-shot learning at human level.

Published in PNAS and featured by MIT news.

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🌎

Machine Learning for Climate Science

Machine learning for predicting Atlantic multi-decadal variability; and computer vision methods for tracking turbulent structures in plasma of fusion reactors.

Best paper award at NeurIPS CCAI; Published in Nature Scientific Reports and featured by MIT news.

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Recent Publications

Artificial General Intelligence: Mathematical Foundations

Iddo Drori

2025

Open-ended self-improving code agents for maximizing crowd market returns

G Longitano, M Mao, B Segev, A Bhandari, I Drori

2025

AI passes Humanity's Last Exam and generates educational video explanations

G Longitano, A Bhandari, B Segev, M Mao, A Shporer, J Vanschoren, A Amit, M Udell, I Drori

2025

AI co-scientist for the Habitable Worlds Observatory

A Shporer and I Drori

2025

Common AI innovation framework competition

I Drori, A Shporer, N Verma, M Udell

2025

Diverse inference and verification for advanced reasoning

I Drori, G Longhitano, M Mao, S Hyun, Y Zhang, S Park, Z Meeks, X Zhang, B Segev, H Yong, N Verma, A Shporer, A Amit, M Udell

2025

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Deep Learning Book

The Science of Deep Learning book cover

The Science of Deep Learning

Cambridge University Press, 2022

#1 new release in computer vision and pattern recognition

This comprehensive textbook explores the fundamental principles and applications of deep learning, providing a solid foundation for students and researchers in the field.