Abhinav Singhal

Data Scientist

https://talent.gravityer.com/abhinav-singhal

CSE IITD '24

IndiaMember since June 13, 2026

Key Strengths

Demonstrated proficiency in Python and Jupyter Notebook, essential for Data Scientist roles.
Experience with deep learning models (LSTM for fake news detection) indicates practical application of machine learning.
Projects involving ZKP (Zero-Knowledge Proofs) and compilers show strong foundational computer science knowledge and problem-solving skills.
Exposure to various programming languages (C++, Java, Assembly, Standard ML) suggests adaptability and a broad technical base.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's personal projects demonstrate a strong inclination towards self-driven learning and exploration across diverse technical domains, including advanced topics like ZKP and compilers. This indicates a proactive and curious mindset, which can be a good cultural fit for innovative and research-oriented environments. The variety of projects also suggests an ability to work independently and tackle complex challenges.

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback provided.

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Projects

zkp_shared

April 2, 2023 – April 27, 2023

zkp_shared — GitHub repository

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ZKP

March 1, 2023 – April 2, 2023

ZKP — GitHub repository

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Multilingual-NLI

November 27, 2022 – November 30, 2022

Multilingual-NLI — GitHub repository

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fake-news-detection

July 18, 2021 – July 18, 2021

Trained LSTM based deep learning model to detect fake news from a given news corpus. This project can be practically used by any media company/government regulator to automatically predict whether the circulating news is fake or not without manual intervention.

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Compiler-for-dummy-lanuage

July 14, 2021 – July 14, 2021

Developed a compiler to perform lexing, parsing and generation of abstract syntax tree using ML-Lex and ML-Yacc. Implemented type checking, evaluation of boolean and integer expressions, and lambda and higher-order functions

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Dynamic-Memory-Allocator

July 14, 2021 – July 14, 2021

Implemented dynamic memory allocator using doubly linked list and optimized it using BST and AVL trees in Java to allocate / free memory blocks from RAM and efficiently defragment the RAM for best fit for memory blocks.

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semi-supervised-ladder-networks

June 30, 2021 – July 14, 2021

semi-supervised-ladder-networks — GitHub repository

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Traffic-Density-Estimation

February 21, 2021 – July 8, 2021

Traffic-Density-Estimation — GitHub repository

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COL216-Assignments

February 21, 2021 – July 8, 2021

COL216-Assignments — GitHub repository

View Project

Key Strengths

Demonstrated proficiency in Python and Jupyter Notebook, essential for Data Scientist roles.
Experience with deep learning models (LSTM for fake news detection) indicates practical application of machine learning.
Projects involving ZKP (Zero-Knowledge Proofs) and compilers show strong foundational computer science knowledge and problem-solving skills.
Exposure to various programming languages (C++, Java, Assembly, Standard ML) suggests adaptability and a broad technical base.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback provided.

Abhinav Singhal

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Projects

Key Strengths

Cultural & Operational Fit