Hi, I'm Barukula Snehitha
Actively seeking Full-Time & Internship opportunities | MS in CS at Northeastern University
View My Resume →2+
Years of Experience
10+
Completed Projects
5K+
Hours Worked
About Me
Hello, my name is Snehitha Barukula, and I am recent graduate from Master's in Computer Science at Northeastern University, Boston.
With a solid foundation in software engineering and data-driven solutions, I specialize in AI, Full Stack, Cloud Technologies, and Data Engineering.
My experience includes impactful projects where I designed and implemented scalable systems, leveraging technologies like AWS, Python, and SQL.
I’ve also contributed to meaningful academic research, with publications showcasing my ability to analyze and solve real-world challenges.
Beyond technical skills, I’m passionate about collaborative problem-solving and thrive in environments that prioritize innovation and efficiency.
My goal is to apply my expertise to develop cutting-edge technologies that make a tangible impact.
Education
I am recent graduate from Master of Science in Computer Science at Northeastern University, Boston, MA, Khoury College of Computer and Information Science, from September 2023 to December 2025. My coursework includes Algorithms, Machine Learning, NLP, Database Management Systems, Deep Learning, Patterns of computer vision, Web Development and Programming Design Paradigms. Previously, I completed my Bachelor of Technology in Computer Science Engineering at SRM University, Andhra Pradesh, India, from June 2018 to May 2022. During my undergraduate studies, I was awarded a $1,500 scholarship for the Study Abroad Program at UC Davis as a top performer among 3,000 students.
Experience
IDFC FIRST BANK, India – Software Engineer
- Designed and implemented 50+ REST APIs using Java and Mulesoft, enhancing system integration.
- Delivered end-to-end technical solutions for 2+ banking platforms (credit cards, SMS, OTP, loan services) in an Agile environment, ensuring system reliability.
- Deployed containerized microservices using Kubernetes, ensuring scalable and fault-tolerant infrastructure, and collaborated with the DevOps team to learn and implement CI/CD pipelines.
- Spearheaded the migration from SQL to Oracle databases, enhancing data management scalability and reliability.
- Conducted real-time monitoring of API traffic to ensure operational efficiency and troubleshooting.
WaveLabs, India – Data Engineer Intern
- One of the 6 interns hand-picked for the HR team that developed a Generative AI-driven HR Bot using Python, PyTorch, CNN, and NLP, automating job description generation and reducing HR query resolution times by 25%.
- Leveraged AWS S3 for real-time data warehousing and applied ML techniques using Pandas and NumPy to generate performance insights.
- Enhanced SQL query performance by optimizing query structure, improving data retrieval speed.
Minerva Forum, Amaravati, Teaching Assistant, India
- Graded and assisted the professors with "Probability and Statistics" and "Introduction to Programming with Python" offered to over 300 students.
- Assisted students in writing project reports, led course discussions and laboratory sessions.
Technical Skills
Java
Python
C
TypeScript
Spring Boot
Kubernetes
Docker
Jenkins
TensorFlow
PyTorch
AWS S3, Glue
React
Node.js
CSS
JavaScript
SQL
MongoDB
Git
OpenAI
Co-Pilot
Gemini
Projects
Real-Time Multilingual Handwritten Digit Recognition using CNNs (Apr 2025)
🔗 View DemoDeveloped a real-time digit recognition system for Hindi and Telugu scripts using a lightweight CNN model in PyTorch. Achieved 91.9% character accuracy and 99.5% script classification accuracy. Integrated OpenCV for live webcam-based predictions with visual overlay. Designed modular training and visualization pipeline with filter analysis, grid-based test display, and support for custom image inputs.
Tech Stacks: Python, PyTorch, OpenCV, NumPy, Matplotlib
Calibration and Augmented Reality (Apr 2025)
🔗 View DemoImplemented an augmented reality system by calibrating a camera using OpenCV to correct lens distortion and estimate pose with checkerboard targets. Projected 3D axes and virtual objects (cube, cylinder, pyramid) into real-world scenes in real-time. Enabled robust AR rendering through Harris corner detection and multi-target tracking. Developed and tested on MacBook with iPhone camera using C++ and OpenCV.
Tech Stacks: C++, OpenCV, CMake, iPhone Camera (Continuity)
ContrastiveBERT: Sentence-Level Pretraining Beyond NSP (Mar 2025)
🔗 View DemoProposed a BERT-based model replacing Next Sentence Prediction (NSP) with a contrastive triplet loss to enhance sentence-level semantic representations. Introduced hard negative sampling, mean pooling, and a projection head for better embedding separation. Fine-tuned the model on MNLI for Natural Language Inference and adapted it for Named Entity Recognition (NER) using CoNLL-2003, achieving 93% F1. Visualized performance using t-SNE plots and similarity scores, outperforming baseline BERT on semantic coherence.
Tech Stacks: Python, PyTorch, HuggingFace Transformers, scikit-learn, Google Colab, t-SNE, Matplotlib, Wikitext-2, CoNLL-2003
Image Manipulation Tool (Sep 2024)
Designed an advanced Java Swing application supporting 10+ operations like flipping, brightening, and applying a sepia effect. Implemented real-time RGB histogram visualization and Haar Wavelet Transform for image compression.
Tech Stacks: Java, Swing, Haar Wavelet Transform, MVC Architecture
Image Classification with Regularization and Optimization (Mar 2025)
🔗 View DemoImplemented a neural network for image classification using CIFAR-10, experimenting with L1, L2, and ElasticNet regularization to prevent overfitting. Compared performance across SGD, Adam, and RMSProp optimizers. Visualized training dynamics, learning curves, and class-specific accuracy. Identified best-performing combinations for model generalization and robustness.
Tech Stacks: Python, NumPy, Matplotlib, PyTorch, CIFAR-10
Survey on RNN & LSTM Architectures (Jan 2024)
🔗 View DemoConducted a comprehensive survey of recent advancements in RNN and LSTM architectures, including novel models like RWKV, E-LSTM, ∞-former, and Liquid Time-Constant Networks. The study analyzed their applications across domains like cybersecurity, healthcare, agriculture, and video analysis, highlighting improvements in scalability, efficiency, and interpretability.
Tech Stacks & Resources: Python, LaTeX, IEEE Xplore, arXiv, Springer, Google Scholar
N-gram Models in NLP (Jun 2024)
🔗 View DemoPerformed a literature survey exploring the evolution and hybridization of n-gram models in NLP. Covered applications in sentiment analysis, chatbots, malware detection, minority languages, and quantum computing integration. Evaluated comparative effectiveness across tasks and proposed future research directions in scalability, multilingual NLP, and data efficiency.
Tech Stacks & Resources: Python, Naive Bayes, CNN, Bi-LSTM, Quantum NLP (conceptual), Google Scholar, IEEE Xplore
AI Patient Risk Prediction (Jun 2024)
🔗 View DemoDeveloped an AI-driven system to identify high-risk patients for diabetes, hypertension, and stroke. Achieved accuracies of 74.6%, 85.7%, and 89.6% using Python and machine learning techniques.
Tech Stacks: Python, Machine Learning, Pandas, Scikit-learn
Data Analysis Dashboard (Jun 2024)
🔗 View DemoDeveloped a user-friendly, interactive web-based dashboard for dynamic data analysis and visualization, enabling users to explore datasets and generate insights.
Tech Stacks: Python, Machine Learning, Pandas, HTML, CSS, JavaScript, Flask, Matplotlib
Awards & Publications
Awarded a $1,500 scholarship for the Study Abroad Program at UC Davis as a top performer among 3,000 students.
Research Publication: "Human Activity Detection from Still Images using Deep Learning Techniques," IEEE CAPS 2021.
Patent: "A Deep Learning Based Human Action Recognition System," Patent No. 202241041334, Issued Jul 2022.
Book: "Automated Student Emotion Analysis During Online Classes using CNN," Springer SocProS 2022.
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