Hello, I'm
Data Scientist
Get To Know More
4+ Years of Expertise
in Data Science & Software Development
PES University
Bachelor of Engineering in Computer Science
2015 - 2019
University of Maryland, College Park
Master of Science in Information Systems
2023 - 2024
I’m a data science enthusiast with over four years of experience turning data into actionable insights and building software solutions. With a Bachelor's in Computer Science and a Master’s in Information Systems from the University of Maryland underway, I combine data science expertise with a strong software engineering background. I’ve led projects across industries, leveraging machine learning, advanced analytics, and robust software development to drive business success. Passionate about innovation, I’m always learning and adapting in the ever-evolving world of data science and technology.
Browse My Recent
Built a multilingual QA system by translating a Hindi dataset and using fuzzy matching for accurate answers. Optimized preprocessing with lemmatization and batching, cutting training time by 20%. Trained a BERT model with AdamW, achieving 90% accuracy, 78% F1, and 65% EM, and deployed a Gradio app for 1-second response time.
Built an accessible hand gesture recognition system that converts images into text and speech for users with disabilities. Leveraged Python, OpenCV, and LabelImg for image processing and labeling. Trained an SSD MobileNet V2 model with TensorFlow Object Detection API, achieving 92% accuracy in static and real-time classification.
Analyzed over 500,000 global earthquakes with magnitudes greater than 4 to explore their correlations with mines and nuclear power plants. Utilized spatial analysis techniques within a 50-mile radius of epicenters to identify key risk factors and trends. Created detailed visualizations to present findings and provided strategic risk mitigation recommendations to five countries. The project employed advanced data processing methods to deliver actionable insights and enhance earthquake risk management.
This project optimized ad campaign performance by predicting success and improving ROI. I built a LightGBM model with 95% accuracy, tuned using GridSearchCV, and selected the top 20 features with RandomForestClassifier. By handling class imbalance with SMOTE and targeting predicted depositors, I increased ROI by 70%, demonstrating the impact of precision-targeted campaigns.
Read My
In this article, I demystify linear regression, breaking down its fundamental concepts and applications. Through a weather prediction example, I explain simple linear regression, illustrating how it can be used to model relationships between variables and make predictions.
Read More
In this beginner's guide, I introduce the concept of APIs, explaining how they enable communication between software applications. The article covers key concepts such as API endpoints, methods, and authentication, with practical examples to illustrate their usage. It’s crafted to provide a clear understanding for those new to APIs, making it easier to grasp their importance in modern software development.
Read More
In this article I explain essential text preprocessing techniques in NLP with practical code examples. This guide covers everything from tokenization to lemmatization, helping you prepare your text data for machine learning models effectively.
Read MoreGet in Touch
