Aanchal Gupta

Software Engineer

Delhi, India2 yrs 8 mos experience

Key Highlights

Strong foundation in problem-solving and algorithms.
Hands-on experience as a Software Engineering Intern at LinkedIn.
Research on knowledge graph quality assessment.

Stackforce AI infers this person is a Software Engineer with a focus on research and development in knowledge representation.

Contact

Skills

Core Skills

Knowledge Representation

Other Skills

Algorithm DesignAndroid StudioAzkabanC (Programming Language)Cascading Style Sheets (CSS)CommunicationData StructuresEmber.jsHTMLJavaJavaScriptJupyterKnowledge GraphsKotlinLeadership

About

I am currently pursuing my B.Tech in Computer Software Engineering with a specialization in Applied Mathematics at Indraprastha Institute of Information Technology, Delhi, one of the leading institutes in the country. I have a strong foundation in problem-solving, data structures, and algorithms and am eager to apply my skills to real-world challenges and projects. I am passionate about creating innovative and impactful solutions that can make a difference in people's lives and careers. As a Software Engineering Intern and a mentee at LinkedIn, I had the opportunity to learn from some of the best in the industry, gaining valuable insights and hands-on experience in software engineering. I look forward to expanding my network, enhancing my knowledge, and developing my career as a software engineer.

Experience

2 yrs 8 mos

Total Experience

11 mos

Average Tenure

10 mos

Current Experience

2 roles

Software Engineer

Jul 2025 – Present · 10 mos · Bengaluru, Karnataka, India · On-site

SDE Intern

May 2024 – Aug 2024 · 3 mos · Bengaluru, Karnataka, India · On-site

Indraprastha institute of information technology, delhi

3 roles

Teaching Assistant

Jan 2024 – May 2024 · 4 mos

Differential Equations (M-IV)

Mentor (Student Mentorship Program)

Aug 2023 – Mar 2024 · 7 mos

Teaching Assistant

Aug 2023 – Dec 2023 · 4 mos

Real Analysis-1

Kracr lab

Undergraduate Researcher

Aug 2023 – Jun 2025 · 1 yr 10 mos · IIIT Delhi

In the field of knowledge representation, the construction and maintenance of high quality knowledge
graphs (KG’s) play a pivotal role in ensuring the accuracy and reliability of information. This
research endeavours to establish a comprehensive framework for assessing the quality of knowledge
graphs, introducing novel matrices and metrics tailored to capture the intricacies of knowledge
representation. Our approach involves the development of quantifiable measures that evaluate
aspects such as completeness, consistency, accuracy, and contextual relevance within a knowledge
graph.