Nakul Verma

简介

I am the Director of the Data Science Master program, and a senior teaching faculty member at Columbia University, focusing on Machine Learning, Algorithms and Theory. My primary area of research is Machine Learning and High-dimensional Statistics. Previously, I worked at Janelia Research Campus, HHMI as a Research Specialist developing statistical techniques to quantitatively analyze neuroscience data. I have also worked at Amazon as a Research Scientist developing risk assessment models for real-time fraud detection. I received my PhD in Computer Science from UC San Diego specializing in Machine Learning.

代表成果

• Compressibility Barriers to Neighborhood-Preserving Data Visualizations Algorithmic Learning Theory (ALT), 2026 pdf
• Sample complexity of learning Mahalanobis distance metrics Neural Information Processing Systems (NIPS), 2015 pdf
• Distance preserving embeddings for general n-dimensional manifolds Journal of Machine Learning Research (JMLR), 2013 pdf