AI/ML Engineer & Data Scientist
Master's student at Northeastern University specializing in Applied Machine Intelligence. Top 250 globally in RSNA Intracranial Aneurysm Detection Kaggle Competition. Passionate about leveraging AI to solve complex real-world problems in healthcare and beyond.
Enthusiastic Computer Science graduate specializing in AI and ML. Currently pursuing my Master's in Applied Machine Intelligence at Northeastern University (Expected 2027), building upon my B.Tech in Computer Science with AI&ML specialization from Jain University (CGPA: 8.76/10). Experienced in machine learning models, data analysis, and algorithm optimization. Skilled in problem solving and proficient in Python. Excited to apply my expertise to innovative ventures in healthcare AI, computer vision, and NLP.
Developed production-ready 3D medical imaging pipeline for aneurysm detection. Processed 4,000+ DICOM brain scans with optimized preprocessing. Built EfficientNet3D ensemble with SE attention and focal loss, reducing runtime from 25 min to under 30 seconds per series.
Built comprehensive healthcare queue management system using FastAPI and PostgreSQL. Implemented real-time patient tracking, appointment scheduling, and automated queue optimization algorithms to reduce wait times.
Developed full-stack AI app with Streamlit using RAG architecture. Integrated LangChain and FAISS for semantic search across 50+ arXiv papers per query with 99% accuracy. Reduced research reading time by 5+ hours per session.
Engineered LSTM model achieving 85.34% testing accuracy and 96.18% training accuracy on emotion classification. Integrated noise addition and pitch stretching for data augmentation. Used TESS, RAVDESS, CREMA, and SAVEE datasets.
Built full-stack AI application integrating document analysis and database querying. Implemented NLP capabilities for automatic SQL query generation from natural language, improving database query efficiency by 40%.
Comprehensive analysis of Department of Education's College Scorecard data. Created interactive visualizations comparing graduation rates, earnings, and debt across institutions. Built actionable insights for policy recommendations.
Analyzed NYC 911 service request data with focus on noise complaints. Identified temporal and spatial patterns, developed predictive models for resource allocation, and provided actionable policy recommendations for city planning.
Developed automated system for digitizing ECG signals from paper-based records. Implemented computer vision algorithms for signal extraction and deep learning models for arrhythmia classification.
Comprehensive evaluation of Walmart's enterprise information architecture and big data systems. Analyzed data warehouse design, real-time processing capabilities, and scalability strategies for retail analytics.
Built machine learning pipeline for real-time fraud detection using ensemble methods. Implemented behavioral pattern recognition with anomaly detection algorithms achieving high precision with minimal false positives.
IEEE Xplore, 2022 - 4th IEEE International Conference
Developed a virtual trial room program using OpenCV and Augmented Reality for real-time cloth simulation. The application identifies background and subject using color palette analysis and thresholding techniques.
Read on IEEE Xplore →Research Paper
Examined the incorporation of RPA and AI technologies within Industry 4.0. Explored integration with Neural Networks, Text Mining, and NLP for data extraction, classification, and process optimization.
Read Paper →Research Paper
Revolutionary paradigm giving voice assistants emotional intelligence using ML and audio preprocessing. Captures user emotions and generates contextually relevant responses with sentiment analysis.
Read Paper →Microsoft
January 2024
IIIT-B
2024
Deep Learning AI (Coursera)
August 2023
Cognitive Class (IBM)
September 2023
Futurense Technologies
February 2024
Udemy
January 2023
Futurense Technologies
January 2024
UC Irvine (Coursera)
December 2022
Daydream (Coursera)
July 2023
Northeastern University, Boston, MA
Futurense Technologies, Bangalore
Jain (deemed to be) University, Bangalore
CGPA: 8.76/10
A comprehensive guide to beginning your journey in data analysis with Python. Learn about essential libraries like Pandas, NumPy, and Matplotlib, and how to set up your environment for success.
Read MoreEssential techniques for ensuring your data is accurate, consistent, and ready for analysis. Learn how to handle missing values, outliers, and data transformation strategies.
Read Moreprathamchopra.me@gmail.com
Phone
+1 (781) 805-0647
GitHub
github.com/prathamchopra001