For the very first episode of the CDSS Podcast we interview Professor Nakul Verma! Nakul Verma is a professor at Columbia University who works on various aspects of machine learning problems and high dimensional statistics; he is especially interested in exploiting the intrinsic structure of data to design effective learning algorithms. His theoretical work in distance preserving embeddings is currently state of the art. He is also considered one of the best lecturers in the Computer Science Department by his students. In the following interview, we discuss topics including Professor Verma’s career path, his tips and advice to students, his outlook towards ML in the for the future, as well as a discussion about his work in Distance Preserving Manifolds.