Help & Supportcareers@gravityer.com
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
MTech, IIT Hyderabad | AI/ML & LLMs | Ex-WSAI Intern, IIT Madras
I am currently pursuing an MTech in Techno Entrepreneurship at IIT Hyderabad, where I am building a strong foundation in advanced technologies, innovation, and applied problem-solving. My academic training emphasizes the intersection of technology, entrepreneurship, and real-world impact. Previously, I have gained hands-on experience through internships at the Wadhwani School of Data Science and AI, IIT Madras, and ThirdEye Data, working on areas such as AI evaluation, natural language generation, and knowledge engineering. I have also contributed to projects like the Sansad AI Parliamentary Tracker, reflecting my interest in applying AI to high-impact, socially relevant use cases. Alongside my academic journey, I have been involved with the Office of Career Services at IIT Hyderabad, where I support initiatives connecting students with industry opportunities. I am motivated to explore the intersection of technology, innovation, and entrepreneurship, and aspire to contribute to the development of impactful AI-driven solutions.
Indian Institute of Technology Hyderabad
Master of Technology - MTech, Techno Entrepreneurship
July 1, 2024 – July 1, 2026
Indian Institute of Information Technology Dharwad
Bachelor of Technology - BTech, Data Science and Artificial Intelligence
December 1, 2020 – July 1, 2024
Aditya Junior College
Intermediate(11th & 12th)
January 1, 2018 – January 1, 2020
Aditya (EM) High School
10th
January 1, 2017 – January 1, 2018
Office of Career Services, IIT Hyderabad
Career Cell Coordinator
May 1, 2025 – April 1, 2026
Hyderabad
Wadhwani School of Data Science and AI, IIT Madras
Summer Intern
May 1, 2025 – July 1, 2025
Chennai, Tamil Nadu, India · On-site
ThirdEye Data
AI Intern
February 1, 2024 – May 1, 2024
Remote
DIGIOTAI Solutions
Summer Intern
May 1, 2023 – July 1, 2023
Remote
Chegg Inc.
Subject Matter Expert
November 1, 2022 – October 1, 2023
Remote
SIDALCEAS EduTech
Research Intern
October 1, 2022 – November 1, 2022
QWorld
Project Intern
July 1, 2022 – August 1, 2022
InMovidu Technologies Pvt Limited
Intern
December 1, 2021 – January 1, 2022
Hate Speech Detection Using Fine-Tuned BERT Models
July 1, 2024 – November 1, 2024
This project focuses on hate speech detection by fine-tuning individual BERT models on the Dhate dataset for three key tasks: Binary Classification: Column: label Classes: hate / nothate Achieved macro F1-score: 0.7640 Multi-Class Classification: Column: target (e.g., asian, black, etc.) Achieved macro F1-score: 0.135 Column: type (e.g., derogatory, animosity, etc.) Achieved macro F1-score: 0.475 Dataset The Dhate dataset was used for training and evaluation, providing diverse annotations for hate speech in terms of label, target, and type. Models and Methods Pretrained BERT models were fine-tuned individually for each task. Results show competitive performance compared to baseline models, with significant improvements in binary classification. Key Results Our BERT model outperformed RoBERTa (Dhate paper) for binary classification, achieving an F1-score of 0.7640 compared to 0.7538.
Prototyping GraphRAG with Neo4j, Langchain & Gemini
April 1, 2024 – May 1, 2024
[Solo Project]My recent interview related to the knowledge graphs pushed me to explore it a bit further. This project has a streamlit application performing GraphRAG, performing transformations on Local Neo4j graph database based on text inputs from the user.
Predictive Modelling for Lighthouse Locations with Classical and Quantum Approaches
May 1, 2023 – July 1, 2023
This project showcases a comprehensive data analysis and predictive modeling project aimed at optimizing site management and reliability in lighthouse operations. The dataset comprises 60,000 observations across 17 lighthouse locations, and advanced preprocessing techniques, feature extraction, and analysis were employed to identify influential factors. Classical machine learning algorithms were utilized to develop a robust model with an exceptional accuracy rate of 92%. Additionally, the project explores the cutting-edge realm of quantum computing by implementing a Variational Quantum Classifier (VQC) on AWS Braket, resulting in a significant accuracy improvement of 55%. The project's hypothesis revolves around leveraging historical data and quantum feature mapping to revolutionize the prediction and management of sensor malfunctions in lighthouse operations. Join us in exploring the potential of quantum computing and its applications in this exciting field.
Sign Language Recognition using CNN and GCN
January 1, 2023 – May 1, 2023
Sign language recognition serves as a vital medium of communication specifically designed for individuals who are deaf or hard of hearing. It plays a pivotal role in facilitating effective interaction within the deaf community, allowing individuals to express their thoughts, emotions, and ideas through visual gestures and movements. However, the lack of familiarity with sign language among hearing individuals often creates barriers in comprehending and interpreting these gestures, thus limiting effective communication between deaf and hearing individuals. To bridge this communication gap and promote inclusivity, sign language recognition technology has emerged as a promising solution. The primary objective is to develop sophisticated systems capable of automatically interpreting and translating sign language gestures into written or spoken language, thereby enabling seamless communication between individuals with hearing impairments and those without. This technology aims to break down barriers and create a more inclusive society where effective communication knows no bounds. The implementation of a sign language recognition system involves leveraging cutting-edge machine learning and computer vision techniques. With advancements in deep learning algorithms and image processing, models can be trained to accurately recognize and interpret a diverse range of sign language gestures.
Enterprise Design Thinking Practitioner
IBM
June 25, 2026 – Present
Generative AI in Action
IBM
June 25, 2026 – Present
Artificial Intelligence Fundamentals
IBM
June 25, 2026 – Present
Getting Started with Artificial Intelligence
IBM
June 25, 2026 – Present
MTA: Introduction to Programming Using Python - Certified 2021
Microsoft
June 25, 2026 – Present
Getting Started with Enterprise-grade AI
IBM
June 25, 2026 – Present
AI/ML applications using Python
Indian Institute of Technology Dharwad
June 25, 2026 – Present
Excel for Data & Analytics
Chegg Inc.
June 25, 2026 – Present
Cultural Fit Analysis
The candidate demonstrates a strong inclination towards research and cutting-edge technologies, particularly in AI, ML, and Quantum Computing. The diversity of personal projects and internships, including academic and industry settings, suggests adaptability and a proactive learning attitude. However, the current profile is heavily skewed towards research and data science, which may require a cultural adjustment for a pure backend engineering role focused on scalable systems, APIs, and infrastructure rather than model development and data analysis.
Soft Skills & Operational Fit
The candidate's experience as a Career Cell Coordinator suggests organizational and communication skills. Project descriptions indicate an ability to work independently (solo projects) and collaborate (internship teams). The role as a Subject Matter Expert at Chegg implies strong explanatory and problem-solving abilities. However, without direct assessment data, specific soft skill proficiency and operational fit cannot be definitively quantified.