Air Pollution Monitoring System using Raspberry Pi
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Summary
Designed and built a comprehensive air quality monitoring solution using Raspberry Pi, integrating real-time data collection and an alert system with mobile/web notifications.
About
Highly analytical Data Science Professional with a strong foundation in machine learning, data processing, and visualization. Proven ability to develop and deploy advanced ML models, including anomaly detection systems and computer vision algorithms, to solve complex problems and drive predictive insights. Eager to leverage expertise in Python, R, and data visualization tools to deliver data-driven solutions and contribute to informed decision-making in a dynamic data science environment.
Work
International Space Research Organisation (ISRO)
|Data Science Intern
Bengaluru, Karnataka, India
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Summary
Led the development of an advanced anomaly detection system for spacecraft electrical power systems, significantly enhancing mission reliability through predictive maintenance.
Highlights
Conducted advanced anomaly detection in spacecraft Electrical Power Systems (EPS) using unsupervised machine learning techniques, improving system robustness.
Built predictive models with Vector AutoRegression (VAR) to forecast subsystem failures, enabling proactive preventive maintenance strategies.
Analyzed extensive real telemetry data from the RAAVANA satellite mission, utilizing Python (Pandas, NumPy, Scikit-learn) for comprehensive preprocessing and feature extraction.
Successfully implemented a critical anomaly detection system for spacecraft, directly contributing to enhanced space mission reliability.
Gained specialized expertise in advanced time-series analysis and aerospace applications, applying cutting-edge data science methodologies.
Hindustan Aeronautics Limited (HAL)
|Software Design Intern
Bengaluru, Karnataka, India
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Summary
Developed and deployed functional machine learning models for aircraft type identification, applying computer vision algorithms and industry-standard software development practices.
Highlights
Developed and implemented machine learning models for aircraft type identification, leveraging computer vision algorithms for enhanced accuracy.
Optimized algorithms and model training to significantly enhance image recognition accuracy in aerospace applications.
Applied industry-standard software development practices within the aerospace domain, ensuring robust and scalable solutions.
Successfully deployed a functional aircraft recognition system, demonstrating practical application of advanced ML techniques.
Gained expertise in industry-specific machine learning applications, contributing to specialized aerospace projects.
Education
Presidency University
Bengaluru, Karnataka, India
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Bachelor of Technology
Computer Science
Grade: 8.13/10 CGPA
Certificates
Skills
Programming Languages
Python, R, C#, HTML.
Data Analysis & Visualization
Power BI, Tableau, MATLAB, Excel, R Studio, Data Preprocessing, Feature Extraction, Telemetry Data Analysis.
Databases
SQL, NoSQL.
Machine Learning
Unsupervised Learning, Predictive Modeling, Time-Series Analysis, Anomaly Detection, Computer Vision, Algorithm Optimization, Model Training.
Project Management & Soft Skills
Leadership, Project Management, Effective Communication, Team Coordination, Time Management, System Design, Problem Solving, Analytical Skills.
Hardware & Embedded Systems
Raspberry Pi, Arduino, IoT, Hardware-Software Integration.
Projects
Solar-Based Mobile Charger on Coin Insertion using Arduino
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Summary
Engineered an innovative solar-powered charging station with a coin-operated activation system, programmed with an Arduino microcontroller for intelligent power management based on solar availability.