The one where vision meets understanding and argues over perspective | Interested in CV, DL, VLMs
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
vehicle_counting_ui
September 22, 2023 – Present
Simple annotation tool for counting vehicle in the video. Written using PyQt6 library
View ProjectMulti-Radius-Deep-SVDD-PyTorch
April 17, 2023 – April 17, 2023
Extended Implementation of 'Deep One Class Classification' paper
View Projectfreematch-pytorch
January 27, 2023 – April 17, 2023
Unofficial PyTorch implementation of the paper 'FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning'
View Projectpytorch-models-ctaugment
June 7, 2022 – June 9, 2022
A plug 'n' play CTAugment wrapper that can be used with classification tasks using pytorch framework.
View ProjectmAP-calculator
June 6, 2022 – June 8, 2022
A simple script to calculate the mAP using PascalVOC2012 and COCO standards for object detection
View ProjectTransplan
February 18, 2022 – September 5, 2024
my implementations for the transplan project
View ProjectMLNet-Pytorch
November 14, 2018 – March 12, 2019
Implementation of A Deep Multi-Level Network for Saliency Prediction in Pytorch
View ProjectGraph_Image_Segmentation
August 30, 2018 – August 30, 2018
Implementation of Efficient Graph Based Image Segmentation by Pedro F. Felzenszwalb and Daniel P. Huttenlocher
View ProjectBoxDetection
July 22, 2018 – June 29, 2020
A Box detection algorithm for any image containing boxes.
View ProjectCultural Fit Analysis
The candidate's projects are predominantly personal and research-oriented, focusing heavily on deep learning and computer vision. While this aligns with a Data Scientist role, the lack of team projects, diverse industry applications, or explicit collaboration experiences makes it difficult to assess cultural fit comprehensively. The projects indicate a strong individual contributor profile.
Soft Skills & Operational Fit
Insufficient data to assess soft skills, logical reasoning, work attitude, stress handling, or team collaboration. The candidate's project descriptions are concise, but there is no information on communication clarity or professional language usage from the English test score (0/100).