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
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.
Associate Professor of practice, Department of Computer Science, Boston University
Artificial General Intelligence (AGI)
Computer Vision
Machine Learning for Education
Machine Learning for Climate Science
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.
Learn MoreNeural 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.
Learn MoreMachine 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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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.