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Fajr Naveed

FAST · 2023 · i19 - 0436
Email
Phone
LinkedIn
GitHub

Academic

Program
BSCS
CGPA
Year
2023
Education
SEECS
Address
DOB

Career

Current role
Target role
Skills
React, MongoDB, Express, NodeJS, FLASK, PyTorch, Web Scraping, Dataset Creation, Semantic Analysis, Topic Modeling, Text to Voice API, Video Recording

Verbatim text

The exact text the LLM saw on the page (or the booklet text from the old import). This is what powers semantic search.
Group Members:
Muhammad Sameer Khan (i19 - 0570)
Muhammad Zohaib (i19 - 0558)
Fajr Naveed (i19 - 0436)

InTrivia
Score your dream job
An interview training platform

Architecture
Web Scraping -> Dataset Creation -> Database -> User Interface -> Interviewee
SCORE -> Report Generation <- Semantic Analysis <- Topic Modeling

Timeline
Sept-Oct: Web scraping for dataset creation, Initial Front-end and Back-end development
Nov-Dec: Data cleaning and tagging, Models Implementation, Further Front and Back-end development
Feb-Mar: Web and models integration, Completion of web, Testing and Improvements, Text to voice API feature implementation, Semantic analysis, Video recording feature implementation
Apr-May

Tools
React, MongoDB, Express, NodeJS, FLASK, PyTorch

Technology Used:
React, MongoDB, Express, NodeJS, FLASK, PyTorch
Supervisor Name:
Mr. Adil Majeed

AI enrichment

Fajr Naveed is a BSCS student who collaborated on a capstone project called InTrivia, an interview training platform utilizing web scraping, topic modeling, and semantic analysis. The team developed a full-stack application using the MERN stack and Python libraries to generate interview reports and score candidates.
Skills (AI)
["React", "MongoDB", "Express", "NodeJS", "Flask", "PyTorch", "Web Scraping", "Topic Modeling", "Semantic Analysis", "REST API Development"]
Status: ai_done
Provenance
Source file: FAST - School of Computing -Graduate Directory-2023.pdf
From job #14 page 294
Created: 1778112745