Join Hugo Dolan in this podcast as he interviews engineers and researchers from the world of data science at various stages of their careers. Find out more about their roles, pathways and the decisions they made that have brought them to where they are today.
Ondrej Bohdal

Ondrej Bohdal is a Phd Researcher in Specialising in Efficient Meta Learning at the University Of Edinburgh. In this podcast we discuss his experiences in software engineering and machine learning at firms including Metaswitch (Communications), JP Morgan (Banking) and Amazon (Advertising). We also discuss his research in meta learning and his work on segregating 3D point clouds generated by drone aerial scans. Amongst other things we touch on various topics in deep learning and the changing landscape of machine learning research as more and more research in now focused on deep learning solutions.

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Oscar Chang

Oscar Chang is a Phd Researcher in Deep Learning at Columbia University in The City of New York, in this podcast we discuss his research in the area of Meta Learning - teaching neural networks to generalise what it has learned from many small datasets to a new domain area. Additionally we discuss selected projects he worked on whilst interning at tech firms including Microsoft, IBM, Google, Sony & Amazon! We also discuss some of the major active research areas in deep learning and also the pitfalls surrounding setting up deep learning applications within companies ranging from startups to large technology firms.

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Ryan Kinnear

Ryan Kinnear is a Phd Researcher in Electrical Engineering at the University of Waterloo (Canada), in this podcast we discuss many topics such as the basics of reinforcement learning and agent based modelling, along with his research in Computational Advertising and Brain Signal Analysis. Furthermore we discuss his participation in data science competitions, working in teams as well as his internship experience in Software Engineering and Quantitative Research at the Hedge Fund Citadel. Additionally we discuss the pros and cons of further academic study vs a career in industry and general advice on entering any of these career paths.

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Andy Jin

Andy Jin is a Computer Science student at Stanford University with experience interning as a software engineer at Hulu and J.D. Power. Andy has also worked as a research intern for three summers at UC Santa Barbara, including one sponsored by the National Science Foundation through the IGERT Program. In the podcast we explore his career so far and his advice for those looking to work in the data industry.

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