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Dalhousie University
Data Scientist
June 26, 2026 – Present
DEFault-DNN-Debugging
July 11, 2024 – Present
This repository provides all necessary code and data to reproduce the experiments from the ICSE - 2025 accepted paper: "Improved Detection and Diagnosis of Faults in Deep Neural Networks using Hierarchical and Explainable Classification."
View Projectbugsplorer-replication-package
July 17, 2023 – July 17, 2023
bugsplorer-replication-package — Dev.to repository
View Projectbugsplainer-icse23
January 12, 2023 – February 16, 2023
Replication package for the Bugsplainer tool published in ICSE 2023
View Projectbugsplainer-webapp
September 22, 2022 – December 5, 2023
Web application version of the Bugsplainer tool to explain bugs in software code in a human-friendly way
View Projectstripe-connect
December 3, 2019 – November 24, 2022
A tryout to integrate Stripe payment to a book selling service
View Projectparvezmrobin.github.io
November 4, 2017 – April 26, 2023
Personal profile of Parvez M Robin.
View Projectweb-school
April 8, 2017 – November 4, 2017
School Marking System including year, class, section, subject, teacher, student, mark portion, mark CRUD
View ProjectDigital-School
August 31, 2016 – December 28, 2016
School management application built with ASP.Net
View ProjectCultural Fit Analysis
The candidate's projects show a strong inclination towards academic research and personal development, with a diverse set of technologies. However, the projects are predominantly personal and lack explicit team collaboration or large-scale industry application details. The target role is 'Data Scientist', and while some projects align, the overall breadth includes web development and numerical methods in C++, which might indicate a broader interest rather than a focused alignment with a pure Data Scientist role. The candidate's experience level is 0, which contradicts the listed 'Data Scientist' role at Dalhousie University starting in 2026, suggesting a potential future or academic role rather than current industry experience.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions are concise, but there is no direct evidence of communication clarity, grammar, professional language usage, logical reasoning, work attitude, stress handling, or team collaboration from the provided data.