JY

Jessica Yung

Research Engineer at DeepMind

United Kingdom

Overview

Work Experience

  • Research Engineer

    2022 - Current

    Main projects: - AlphaProof (AlphaZero with LLMs for mathematical reasoning) - SynthID (image watermarking) - Video compression with MuZero

  • Venture Scout

    2018 - 2022

  • Cofounder and Chief Science Officer

    2021 - 2021

    Helping auto-patch vulnerabilities in code in seconds rather than days or weeks.

  • AI Resident

    2019 - 2021

    Researched transfer learning for computer vision. Published state-of-the-art BigTransfer (BiT) model at ECCV, open-sourced code, wrote TensorFlow blog post. Co-author of MLP-Mixer (NeurIPS). Created and open-sourced synthetic dataset SI-SCORE to analyse robustness of image models in a fine-grained way. Co-first author of robustness study at CVPR, workshop paper at ICLR. Worked on developing more recommender systems that are more user-experience-centric instead of just maximising profits and engagement (and so often maximising for things like anger and polarisation in the process). Co-author of NLP work on recommender systems. Gave TensorFlow tutorial workshop at Perspektywy Women in Tech conference 2020.

  • AI Engineering Consultant

    2018 - 2018

    Machine Learning, Python, PyTorch, AWS, Google Cloud Platform - Researched augmenting models with external memory. - Contributed to open-source implementation of Relational RNNs (Santoro et. al., 2018). - Researched methods for time series prediction and unsupervised learning.

  • Founder and developer

    2016 - 2018

    Debating motions database with more than 2.5 million pageviews. Easily find a random debating motion or look up previous motions to prepare for upcoming tournaments. The site is maintained with the help of beyond incredible volunteers from the debating community. (I'm still doing this! I will push a new Flask version in Dec 2021 with motions tagged with categories using Transformer-based models and advanced filtering for search and random motions.)

  • Quantitative Researcher Intern

    2017 - 2017

    Machine Learning, Trading and Market Mechanics, Statistics, Python, C++ - Researched data preprocessing and modelling techniques for predicting financial data. - Built machine learning research frameworks in Python to facilitate experiments on high performance computing clusters.

  • Discover Digital (Insight)

    2017 - 2017

    - Discussed and presented findings on how to improve mobile operator's profits and increase market share based on company data - Designed new prototype for mobile app with student team - Previously also selected for McKinsey Discover 2016

  • User Experience Design Intern

    2016 - 2016

    - Overhauled design: removed unnecessary features and repositioned key elements. - Designed wireframes iteratively and developed interactive prototypes. - EquitySim went on to win a Fintech award from the UK Government and got into 500 Startups.

  • Institutional Securities Spring Insight Intern

    2016 - 2016

    Work shadowed Investment Banking Division (IBD), Sales and Trading and Equity Research. Fast-tracked to Assessment Centre.

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