Summary
Sindhu Hegde is a machine learning researcher and PhD candidate at Oxford with nine years of experience focused on multimodal AI, particularly the intersections of vision, speech, and language. Currently working on challenging self-supervised image–text alignment and robust ASR for telephone conversations, she brings production-facing experience from Verisk and an industry AI Scientist role at RØDE. Her MS by Research at IIIT Hyderabad produced peer-reviewed work in audio-visual denoising and a portfolio of projects spanning speech synthesis from silent video, extreme-scale talking-face upsampling, and audio-visual super-resolution. Known for strong communication and leadership in cross-disciplinary teams, she pairs deep technical fluency in PyTorch/TensorFlow/OpenCV with a habit of rapidly translating research prototypes into scalable solutions. An academically rigorous problem-solver with top-tier academic performance throughout, she also enjoys collaborating to gain new perspectives that shape her multimodal research direction.
9 years of coding experience
4 years of employment as a software developer
SSLC, 98.4%, SSLC, 98.4% at KLS School
Doctor of Philosophy - PhD, Computer Vision, Doctor of Philosophy - PhD, Computer Vision at University of Oxford
Masters by Research (MS), Computer Vision, CGPA: 9.67, Masters by Research (MS), Computer Vision, CGPA: 9.67 at IIIT Hyderabad
PUC, 96.33%, PUC, 96.33% at Jain College
Bachelor of Engineering (B.E.), Computer Science, CGPA: 9.82, Bachelor of Engineering (B.E.), Computer Science, CGPA: 9.82 at KLE Technological University - Hubballi (India)
English, Hindi, Kannada, Marathi