Click here for a full pdf copy of my Resume/CV:
Education
2023 - Present
Candidate for Master of Science in Data Science
Northeastern University
GPA: 4.0/4.0
2016-2020
Bachelor of Engineering in Information Science Engineering
BMS College of Engineering, Bangalore, India
GPA: 8.8/10
Professional Experience
2020 - 2022
Data Engineering
Dataweave (Infoweave Analytics Pvt Ltd), Bangalore, India
- Collaboratively automated more than 10 end-to-end data science pipelines using Apache Airflow, Python, and AWS to integrate web crawlers, data sources, APIs and internal ETL frameworks resulting in enhanced project outcomes.
- Programmed complex SQL queries to handle large datasets using AWS Athena and S3 to generate business data for reports and interactive dashboards, empowering data-driven decision-making and enhancing business value for clients.
- Attained 50% reduction in text/image batch processing in the company's clustering algorithm by implementing dask library.
- Developed and deployed over 15 Selenium browser automation data crawlers and 200+ Python-based deep crawler bots to efficiently mine data and insights from e-commerce websites, bolstering the company's product offerings.
2020 - 2022
Data Engineering Intern
Dataweave (Infoweave Analytics Pvt Ltd), Bangalore, India
- Performed data analysis and brand analysis to identify counterfeit products, ensuring brand protection and compliance with price benchmarks for enhanced market competitiveness.
- Led the successful delivery of structured data by employing data-wrangling methods that unlocked new business for clients.
Academic Projects
US Air Pollution Time Series Analysis
Northeastern University, DS 5110
- Applied time-series analysis techniques to the US pollution dataset, by focusing on significant pollutants.
- Leveraged advanced time-series forecasting approaches (SARIMAX, LSTM) to predict future air pollution trends in California, providing valuable data-driven insights for environmental monitoring and strategic decision-making.
Trending News Prediction using NLTK and Web Scraping
- Developed a web scraper to gather news articles from a specific website and processed the data using NLP techniques.
- Employed various classification machine learning models (logistic regression, k-nearest neighbors, decision tree, random forest, xgboost) to determine the optimal model for predicting and analyzing news trends.
Deep Learning Approaches to Detect Pneumonia
BMS College of Engineering
- Ran a comparative analysis of three machine learning models (CNN, U-Net, Mask-RCNN) for pneumonia detection.
- Achieved accurate identification and precise localization of pneumonia infection regions in Chest Radiographs by leveraging the superior performance of the Mask-RCNN model.
Foliar Disease Detection using CNN
- The Objective of the project was to train a model using images of the training dataset to accurately classify a given image from the testing dataset into different diseased categories or a healthy leaf.
- A vanilla CNN model served as an optimum solution for the problem statement and use case. After implementation, the model was accurately able to differentiate the test images into a diseased category or a healthy leaf.
Deep Learning approach to detect distracted drivers
BMS College of Engineering
- Developed and evaluated multiple variations of a CNN deep learning model to detect distracted drivers, achieving accurate results and high efficiency through optimization and transfer learning techniques.
- Successfully implemented a final model that accurately identified the driver's activity with high accuracy using the optimized CNN model and transfer learning approach.
Publications
E-waste management and energy conservation in industries, 2021
K.Rakshak et al.
A two-phase model is proposed that deals with the e-waste effectively. The end goal is to use technology on both the hardware and software side to minimize pollution, increase energy efficiency, and also encourage material recycling. The usage and benefits of Eco-ATMs are explored in this paper.
Awards and Honors
Spot Award winner and Value Champion for AMJ’ 21 quarter at Dataweave for efficient performance across projects.
Winner of Start-Up week conducted by the Center for Innovation, Research and Development (ICRD), BMSCE.
Finalist in Smart India Hackathon (SIH) 2020, conducted by the Government of India.
Extracurriculars
Data Science Hub, Northeastern Graduate Student Government, Volleyball, Badminton, Hiking, Video Games, E-Sports
Service and Outreach
Volunteer in the Rotaract club’s I-Teach initiative-
Helped underprivileged students by teaching them elementary subjects.