About
A highly motivated and results-driven Computer Science and Engineering student with a strong academic record (CGPA 8.47), specializing in AI/ML and Full-Stack Development. Proven ability to design, develop, and deploy complex systems, evidenced by published research in Voice-Based Stress Detection and successful full-stack projects in log analytics and e-learning. Eager to leverage expertise in machine learning, data pipelines, and robust software architecture to contribute to innovative technological solutions.
Work
Bangalore, Karnataka, India
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Summary
Conducted cutting-edge research at CDSAML, developing novel AI models for Voice Based Stress Detection and contributing to a SCOPUS indexed publication.
Highlights
Developed a novel approach for Voice Based Stress Detection utilizing CNN and LSTM models to classify stress into low, medium, and high levels from audio samples, analyzing features such as MFCC, ZCR, and RMSE.
Authored and published a research paper on the developed stress detection methodology, accepted to the 9th Edition ICTIS Bangkok 2025 (SCOPUS Indexed), showcasing significant research contribution.
Education
Awards
CNR Scholarship
Awarded By
PES University
Awarded twice for academic excellence, placing in the top 20% of the batch for the 5th and 6th semesters with SGPA of 9.25 and 9.08 respectively.
Languages
English
Skills
Programming Languages
Python, Java, C/C++, SQL (MySQL, PostgreSQL), JavaScript, HTML/CSS, R, iverilog, ARM.
Frameworks & Libraries
NumPy, TensorFlow, Flask, MERN Stack, Kafka, Apache Spark, Grafana, Gradio, Librosa, Scikit-learn, Lex & Yacc.
Developer Tools
Git, Docker, Docker Compose, VS Code, Visual Studio, IntelliJ, Jupyter Notebook.
Soft Skills
Problem-solving, Teamwork, Communication, Adaptability, Attention to Detail, Time Management, Research Skills.