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CV Engineer with a 58% EPE reduction on a production robotics dense correspondence model (UFM/DINOv2), achieving a new SOTA of 1.40 EPE via DoRA + STRING RoPE, outperforming full encoder fine-tuning while reducing trainable parameters by over 90%. Open-source contributor to Google Keras Hub and experienced in developing production DICOM AI pipelines.

Experience2

  1. Deep Vision and Model Optimization Intern

    Feb 2026 — Present

    Perceptyne

    Achieved a 58% EPE reduction through extensive ablation studies on UFM, discovering optimal feature extraction points and validating performance improvements. Implemented DoRA and STRING RoPE techniques to achieve a new state-of-the-art EPE of 1.40 while significantly reducing trainable parameters. Resolved critical MLOps bottlenecks by architecting efficient data pipelines.

  2. DICOM AI/ML Engineer Intern

    Nov 2025 — Feb 2026

    Unidoc Healthcare

    Engineered a safety monitoring layer for live DICOM streams and implemented algorithms for data drift detection to prevent model failures. Developed a validation pipeline for 3D medical segmentation models to ensure compliance with regulatory standards.

Projects3

  • End-to-End 3D Medical Segmentation Framework for the Medical Segmentation Decathlon

    Developed a config-driven MLOps framework supporting multiple 3D architectures, implementing custom training strategies to address class imbalance and achieving high performance on medical segmentation tasks.

    • TPU
    • UNET++
    • TransUNet
    • SwinTransUNet

  • AI Study Assistant: Personalized LLM-Powered Tutor

    Created a retrieval-augmented generation system that transforms handwritten and typed notes into an interactive study platform, leveraging advanced models for contextual Q&A and automated quiz generation.

    • LangChain
    • Hugging Face
    • OCR
    • FAISS
    • Streamlit

  • Built a TPU-Distributed Semantic Segmentation Benchmarking Framework

    Implemented various segmentation models from scratch on the Cityscapes dataset using a modular TPU-distributed training pipeline, developing custom loss functions and evaluation metrics.

    • FCN
    • UNet
    • UNet++

Education1

  • BE

    2022 — 2026

    Progressive Modern College of Engineering

    Artificial Intelligence & Machine Learning