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Bhavya Gaur

Computer Science student · Machine Learning & Software Development Intern

Chennai, India

@bhavya_gaur

LinkedIn GitHub

0 followers

🎓 Bachelor of Technology in Computer Science Engineering at SRM University · Graduating 2026

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About

Computer science student with internship experience in software development and machine learning research. Built ML pipelines, refactored enterprise logging systems, and delivered measurable improvements in accuracy, observability, and maintainability.

Experience

  • Software Developer Intern
    The Bank of New York Mellon (BNY) · Pune, India
    Jun 2026 – Aug 2026

    Refactored Log4j2-based logging across 294+ DAO, Service, and application files, separating payload, SQL, MQ, and operational logs into four dedicated loggers; reduced primary log-file size by 85%+ without data loss. Modified 4 core XML configurations and automated logger discovery using PowerShell, enabling consistent adoption across a 3,500+ module enterprise application and improving observability and maintainability. Resolved 324+ SonarQube issues across duplication, test coverage, and maintainability; built a live monitoring dashboard backed by 3 REST APIs to improve application troubleshooting and support.

  • Machine Learning Intern
    Indian Institute of Technology, Hyderabad · Hyderabad, India
    Mar 2026 – May 2026

    Independently implemented KgCoOp vision-language prompt tuning architecture from scratch, adapting it for federated learning across distributed clients. Redesigned centralized VLM training into a client-server pipeline, achieving 95.01% accuracy on IID and 58.42% on non-IID data; built PyTorch monitoring pipelines for distributed training.

  • Machine Learning Research Intern
    Indian Institute of Science, Bangalore · Bangalore, India
    May 2025 – Jul 2025

    Built an end-to-end audio ML pipeline processing 250+ clinical voice recordings using signal segmentation, MFCC feature extraction, and SVR, Random Forest, and XGBoost regression. Diagnosed and fixed a systematic data-corruption bug in label computation, bringing corrected values 50%+ closer to ground truth; cross-validated outputs in R using the rspiro library.

Education

  • Major in Artificial Intelligence
    Indian Institute of Technology, Ropar
    Artificial Intelligence · Nov 2024 – Jun 2026
  • Bachelor of Technology in Computer Science Engineering
    SRM University
    Computer Science · Aug 2023

Skills

2 to 5 years 2 to 5 years Several years of experience.
C Oop Python Debugging Deep Learning Convolutional Neural Networks Data Structures and Algorithms
1 to 2 years 1 to 2 years A year or two of steady use.
Flask PyTorch TensorFlow Transformers API Integration Understanding
3 to 6 months 3 to 6 months A few months of practice with it.
SQL Java Unit Testing

Tools / apps / platforms

3 to 6 months 3 to 6 months A few months of practice with it.
SonarQube Microsoft PowerShell
<3 months <3 months Just getting started - under three months. This is also what shows when a level has not been set.
Git Docker Atlassian JIRA Splunk Enterprise Atlassian Confluence

Projects

  • PETVET ↗
    Random Forest, Stacking Classifier

    Co-developed a livestock disease-prediction web application with an integrated emergency chatbot for critical scenarios.

  • SAARTHI ↗
    NLP, computer vision, YOLO, Sentence Transformers, K-Means, Flask

    Built a real-time emotion-aware recommendation system combining NLP embeddings, clustering, and computer vision; trained YOLO achieving 80.5% mAP@0.5 and 75.9% recall. Implemented media recommendation using Sentence Transformers and K-Means; refactored the Flask backend using Blueprints and Application Factory patterns for modularity and scalability.

🏆 Achievements & awards

  • LeetCode Rating 1612

    Top 22.47% of users; secured Top 25 in Semicolon 10.0 DSA contest.

  • HACKUPC 2025 Selection · 2025

    Selected among 700+ global participants in Spain.

  • Top 10 Projects in Red Bull Basement University Round

    Ranked among the top 10 projects in the university round.

  • Peer-reviewed paper published at OITS International Conference · 2025

    Co-authored "Exploring Sentiment Dynamics in the Bhagavad Gita Using Zero-Shot Learning and BART," indexed in IEEE Xplore and Scopus.

📚 Publications

  • Exploring Sentiment Dynamics in the Bhagavad Gita Using Zero-Shot Learning and BART · 2025

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