About Me

2nd Year UG student with unsatiated hunger to advance in the field of deep learning intersecting with computer vision and computer graphics, research and specialize in 3D reconstuction and view synthesis. Finds zen staring at decrementing loss counters while listening to korn.

Experience Logo
Next Tech Lab
Member - McCarthy Lab

Oct 2023 - Present

Chennai, IN

    • Contributed to a portfolio of multiple Deep Learning projects, gaining proficiency in Computer Vision and Computer Graphics disciplines.
    • Trained many models utilizing frameworks such as PyTorch Lightning and Weights & Biases for experiment tracking, enhancing project efficiency and reproducibility.
Experience Logo
Data Science Community SRM
Research Director

Oct 2023 - Present

Chennai, IN

  • Curated an article on DataX Journal exploring the revolution of the Transformer Architecture in the 2020s.

  • Finetuned a DistilBERT model to detect toxic behaviour online, enhancing child safety in digital environments, achieved an F1-score of 0.97 on testing.

/ / /
Experience Logo
Neural Radiance Fields

Mar 2024 - Apr 2024

  • Implemented the research paper ”NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis” and trained the NeRF on a synthetic NeRF dataset with 400px resolution.

  • Leveraged Lightning for a flexible and scalable pipeline and W&B for tracking over 10+ experiments.

  • Achieved an average Peak Signal-to-Noise Ratio score of 29.20 on the test set for View Synthesis.

Experience Logo
Recursive Ray-Tracer

Feb 2024 – Mar 2024

  • Developed a recursive ray tracing algorithm to render scenes with photo-realistic lighting and shading effects.

  • Leveraged the GLM library for streamlined vector and matrix computations, optimizing computational performance and enhancing code readability.

  • Rendered 7 scenes using the ray tracer, showcasing a diverse range of visual compositions.

Experience Logo
Panorama - Image Stitching

Jan 2024

  • Utilized SIFT algorithm to extract robust keypoints and descriptors from overlapping regions of each image pair.

  • Employed RANSAC to estimate the homography matrix, defining geometric transformations between image pairs.

  • Introduced weighted blending techniques to ensure smooth transitions, reducing artifacts by 50%.

  • Orchestrated recursive stitching of intermediate panoramas to optimize render efficiency.

Experience Logo
Vision Transformers

Aug 2023 – Nov 2023

  • Implemented the ViT-B/16 model from the research paper ”An image is worth 16x16 words” in PyTorch.

  • Analyzed the motivations behind the architecture and conducted image classification experiments.

  • Authored a detailed blog post on Medium exploring Transformers and their social impacts. Garnered over 50 likes within the 1st week of publication.

This is a fork of my friend's website!