Smriti Reddy Uravakonda
MS Computer Science @ Northeastern University
Software Engineer · ML · Data Science
I build systems that scale, models that ship, and sometimes both at the same time.
From fault-tolerant distributed stores to real-time legal translation pipelines — I've built across the stack. I build reliable systems, ship ML models end to end, and make data tell a story.
Projects
Fault-Tolerant Distributed Key-Value Store
Fault-tolerant replicated key-value store in C++ supporting concurrent reads/writes across a 5-node cluster. Implemented RAFT consensus from scratch — leader election, log replication, state machine replication — achieving 8,000+ ops/sec under 30% node failure. Reduced failover recovery to under 200ms.
Secure Payment Microservice
Dual-service microservices architecture — Spring Boot REST API for transaction management and Django fraud-scoring service — containerized with Docker, orchestrated via docker-compose. OAuth2/JWT auth, MySQL for transactions, MongoDB for session/audit logs, deployed on AWS EC2.
Distributed Client-Server Performance Analysis
Implemented a distributed client-server architecture to analyze performance metrics under varying loads. Conducted comprehensive benchmarking of throughput, latency, and resource utilization.
Image Manipulation Application
Developed a modular image-processing application using Java MVC architecture supporting CLI, GUI, and batch execution modes with advanced filters like blur, sharpen, resize, and dithering.
Alzheimer's Disease Detection with ML
Built binary classification models using clinical datasets to predict early-stage Alzheimer's disease. Compared five supervised learning algorithms with comprehensive evaluation metrics and statistical analysis.
Cardio Risk Predictor
Predicting heart disease risk using ensemble learning methods. Implemented multiple classification algorithms with comprehensive model evaluation and feature importance analysis for healthcare analytics.
Stellar Classifier
Predicting star types using supervised machine learning models. Built classification models to categorize stars based on astronomical features with multi-class classification and exploratory data analysis.
Convolutional AutoEncoders
Implemented convolutional autoencoders for unsupervised feature learning and dimensionality reduction. Explored deep learning architectures for image reconstruction and denoising.
Education
Master of Science
Computer Science
Northeastern University · Boston, MA
RELEVANT COURSEWORK
Bachelor of Technology
Computer Science
Dayananda Sagar University · Bangalore, India
RELEVANT COURSEWORK
Tech Stack
Certifications
Research Publications
Environmental Impact Analysis using Satellite Image Processing
IEEE 4th ASIANCON 2024
Developed automated workflows for environmental monitoring using satellite imagery, demonstrating applications in deforestation tracking and urban development analysis.
Optimising Computation Offloading for Mobile Edge Devices
ICAECT 2024
Researched and proposed optimization strategies for computation offloading in mobile edge computing environments, addressing latency and resource constraints.
Let's Connect
I'm actively seeking opportunities in Software Engineering, Machine Learning, and Data Science. Let's discuss how I can contribute to your team!