Machine learning is a rapidly evolving field. To stay ahead of the curve, we actively encourage our quantitative researchers and machine learning engineers to attend conferences like ICML so they can engage in the latest cutting-edge research.
In this ICML paper review series, our team share their insights on the most interesting research and papers presented at the conference. They discuss the latest advancements in ML, offering a comprehensive overview of the field and where it is heading. Through this series, you will gain valuable insights into the latest trends and developments in ML.
Follow the links to read each set of ICML 2024 paper reviews.
Yousuf, Machine Learning Engineer
Danny, Machine Learning Engineer
Jonathan, Software Engineer
Evgeni, Senior Quantitative Researcher
Michael, Scientific Director
Fabian, Senior Quantitative Researcher
Ingmar, Quantitative Researcher
Oliver, Quantitative Researcher
Hear from our Head of Forecasting Engineering on why the term "tech debt" has outlived its usefulness. In this blog, he explores why we should move away from generic labels and instead ask more precise, value-driven questions that lead to meaningful improvements in engineering and business outcomes.
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Each month, we provide up to £2,000 in grant money to early career researchers in quantitative disciplines. Hear from our March grant winners.
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Hear from Jay, an Open Source Software Engineer, on tackling technical debt in OpenStack. As technology evolves, outdated code becomes inefficient and harder to maintain. Jay highlights the importance of refactoring legacy systems to keep open-source projects sustainable and future-proof.
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