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Harish Chandran, PhD
Machine Learning Engineer & PhD in Computer Science, Duke University
Harish Chandran is the Engineering Site Lead and Senior Staff Research Engineer at DeepMind, where he leads the engineering efforts to integrate AI research results into Google products. Harish received his PhD in Computer Science from Duke University in 2012. While in graduate school, he worked as a Teaching Assistant, helping undergraduate students learn about algorithms and data structures. He has experience in DNA self-assembly, evolutionary algorithms, computational neuroscience, complexity theory, computer architecture, and super-computing.
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Q&A Comments (31)
What is needed to study engineering?
It helps to have a good grasp of the math and science required for your particular field. Things like linear algebra, algorithmic techniques, and programming are really going to help as well. Beyond that, you have to have a love of problem solving.
What about software engineering and programing? Will that help with a career in other engineering fields?
Programming, data analysis, and software engineering are vital ingredients in fields like machine learning, so absolutely. Those are phenomenal tools if you're looking at branching out into a new field in engineering.
What does it take to land an engineering position if I'm doing machine learning?
You need a basic understanding of algorithmic techniques, like searching, sorting, graph structures, dynamic programming, and all of the other 10 big blocks of software engineering. Once you have a good solid grasp of that, you need to be able to answer whiteboard questions to prove that you have the chops for problem solving. For interviews, you'll have to solve engineering puzzles and possibly craft an algorithm.
