Super Data Science: ML & AI Podcast with Jon Krohn 451: Translating PhD Research into ML Applications
Mar 11, 2021
Dan Shiebler, a Staff Machine Learning Engineer at Twitter and PhD candidate at the University of Oxford, dives into the intersection of academia and industry. He discusses the challenges of balancing a full-time job with PhD research in category theory. Dan shares insights on transitioning from MATLAB to Python, innovative data labeling strategies in insurance, and the skills sought in tech interviews. He also reflects on the evolving roles of data professionals and the future of machine learning approaches. It's a blend of theoretical depth and practical application!
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PhD While Working
- Consider pursuing a PhD part-time while working full-time if you don't want to interrupt your career.
- Dan Shiebler is pursuing a PhD at Oxford while working at Twitter, aiming for a 4.5-year timeline.
Category Theory in ML
- Dan Shiebler's PhD research applies category theory to machine learning, focusing on how transformations and object behaviors define algorithms.
- This approach can offer new perspectives for algorithm development and improvement.
Balancing Work and PhD
- To balance work and a PhD, choose a research area unrelated to your job to treat it as a hobby.
- This separation can minimize stress and prevent overlap, enhancing mental focus.
