Summary
Vivian S is a Ph.D. candidate in Computer Science and AI at Royal Holloway with eight years of hands-on experience building and researching deep learning systems, particularly in computer vision, segmentation, and tracking. She holds a First Class BSc in AI and has investigated GAN behavior, vanishing gradients, and ECG classification using RNNs/LSTMs, demonstrating both theoretical rigor and practical experimentation. Her background spans academia and industry—contributing to open-source ML projects, teaching ML at Google x RHUL Developers Club, and engineering ML solutions at OpenSourceWare. Vivian blends mathematical optimization skills with applied interests in federated learning for aerospace and reinforcement learning for Formula 1 simulation, showing a knack for cross-disciplinary innovation. She has experience with auto-disentangled autoencoders and game development (Unity, C++/C#), an uncommon mix that fuels creative approaches to model design and deployment. Open to collaborations, she publishes code and research on GitHub and welcomes discussions that bridge research and real-world systems.
8 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy - PhD Computer Science and Artificial intelligence, Doctor of Philosophy - PhD Computer Science and Artificial intelligence at Royal Holloway, University of London
Certifications Computer Science, Certifications Computer Science at Coursera
SAT Mathematics, SAT Mathematics at College Board
A / AS Level A Levels, A / AS Level A Levels at Elthorne Park High School
Japanese, English, Hindi, Urdu, Punjabi