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General Information

Full Name Prarthana Bhattacharyya
Languages English, Bengali, Hindi, Japanese
Work Authorization UK Global Talent

Experience

  • 2025 - Present
    Machine Learning Engineer
    Eedi, London, UK
    • Developing and deploying ML and Gen-AI solutions for education technology across UK schools.
    • Co-authored research on uncertainty-based approach for identifying struggling students.
    • Refactored Knowledge Tracing (KT) pipeline, reducing code by 31% and implementation time by 80%.
    • Deployed a generative next-question selector for dynamic quizzes in pilot schools. Productionized on Azure using LitServe, Terraform, and GitHub Actions.
    • Led internal workshop on Generative AI for Education and LearnLM, building team capability in LLM applications.
  • 2023 - 2025
    Senior Machine Learning Engineer
    Ultraleap, Bristol, UK
    • Led hand tracking foundation model development for AI music tutors, redesigning core architecture within 4 months for improved temporal modeling and 3D spatial accuracy.
    • Developed ultra-low-power gesture control for smart glasses achieving 20% accuracy improvement (F1>80%) with 25x power reduction (CES 2025, public launch).
    • Built micro-gesture detection system for smart eyewear, demonstrated at AWE USA 2024 and featured by CNET (Best Paper, ECCVW 2024).
    • Improved IR pinch-tracking accuracy by 50%+ through dataset curation and addressing pose-class imbalances.
  • 2021 - 2022
    Machine Learning Researcher
    Gatik, Toronto, Canada
    • Designed and implemented temporal motion forecasting solutions for autonomous driving (Mitacs PhD Fellowship).
  • Summer 2022
    Machine Learning Engineer Intern
    Apple, Toronto, Canada
    • Implemented self-supervised learning for Vision Transformers, improving Visual Lookup classification accuracy by 4-6%.
  • Summer 2021
    Applied Scientist II Intern
    Amazon Science, Vancouver, Canada
    • Developed self-supervised transformer for logo recognition, achieving 4-11% improvement over SOTA (ICASSP 2022).

Skills

Machine Learning PyTorch, Keras, TensorFlow, Transformers, Vision Transformers, Self-Supervised Learning, Knowledge Tracing, Computer Vision, Gesture Recognition
MLOps & Cloud Azure, LitServe, Terraform, GitHub Actions, CI/CD
Domains Generative AI, Edge ML, Autonomous Driving, Educational Technology, 3D Computer Vision
Programming Python, MATLAB, SQL, Git

Education

  • PhD in Electrical and Computer Engineering
    University of Waterloo, Canada
    • Developed ML algorithms for 3D object detection, tracking and motion forecasting for autonomous vehicles. 3rd place at NeurIPS 2019 Argoverse competition.
    • Research deployed on autonomous vehicles operating on public roads in Canada.
    • Published at top-tier conferences and workshops (ECCV, ICCV, CoRL, IV) with 450+ citations and 400+ GitHub stars.
    • Mentored five undergraduate and MS students on thesis projects in 3D computer vision, self-supervised learning, and temporal motion forecasting.
  • Master of Science and Technology
    University of Tokyo, Japan
    • Specialized in 3D scene understanding and sensor fusion for autonomous vehicles. Developed ML approach for traffic analysis at urban intersections validated with real-world Tokyo data (IEEE VTC). MEXT Scholarship recipient.
  • Bachelor of Engineering
    Jadavpur University, India
    • Focused on digital image compression using machine learning and fuzzy clustering. Published research on vector quantization-based image compression at IEEE conference.

Honors and Awards

    • CES 2025 - Public demonstration of hand gesture recognition system on smartglasses
    • Best Paper Award, ECCV 2024 Workshop on Smart Eyewear
    • AWE USA 2024 - Public demonstration of micro-gesture detection (featured by CNET)
    • Mitacs Accelerate Fellowship, Gatik AI (2021-2022)
    • 3rd Place, NeurIPS 2019 Argoverse 3D Tracking Competition
    • Graduate Fellowships, University of Waterloo
    • MEXT Scholarship by the Japanese Government, for M.S. studies in Japan