Computer Vision and Deep Learning
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Assessing your cultural and operational fit
EEGStyleGAN-ADA
August 18, 2023 – March 21, 2024
Pytorch code of paper "Learning Robust Deep Visual Representations from EEG Brain Recordings". [WACV 2024]
View ProjectBlind-Image-Restoration
April 1, 2023 – December 18, 2023
Pytorch based implementation of earlier State of the Art Deep Generative Filter for Motion Deblurring with integration of advanced techniques to significantly improve the results
View ProjectEEG2Image
February 16, 2023 – March 15, 2025
EEG2IMAGE: Image Reconstruction from EEG Brain Signals. [ICASSP 2023]
View ProjectTNerf-Pytorch
January 28, 2023 – April 23, 2024
Implementation of paper D-Nerf: Neural Randiance Fields for Dynamic Scenes
View ProjectNeRF-Pytorch
January 18, 2022 – February 22, 2024
Implementing NeRF model from scratch Pytorch Version.
View ProjectTreeGCN-ED
October 3, 2021 – December 20, 2023
An autoencoder for point cloud encoding-decoding build using tree-GAN as base work. [Pacific Graphics Poster 2023]
View ProjectOpenCv-Morse-Code-Solver
May 28, 2018 – March 31, 2022
Convert morse code data from image to text
View ProjectCultural Fit Analysis
The candidate's project portfolio is heavily focused on academic/research-oriented deep learning and computer vision, primarily using Python. While demonstrating strong technical depth in a specific domain, there is a lack of diversity in technologies and project types typically associated with a general Backend Engineer role (e.g., web frameworks, databases, distributed systems, API design). This narrow focus might indicate a potential mismatch for a standard backend engineering role requiring broader system development skills.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's profile primarily showcases technical project work without details on collaboration, problem-solving approaches, or communication in a team setting.