Name: Vaibhav Sankaran
Current: Graduate CS Student @ Northeastern University
Experience: 2+ Years
Address: Boston, MA, US
Interest: Playing Cricket, Traveling, Cooking
Main Skills
Results-driven Software Engineer with 2+ years of experience in backend development, full-stack application design and development, distributed systems, and cloud computing. Proficient in Java, Python, and Node.js, with expertise in building scalable REST/gRPC APIs, database optimization (MySQL, PostgreSQL), and high-performance system architecture. Experienced in designing and implementing robust software solutions, focusing on code efficiency, design patterns, and maintainability. Former SDE II at Verizon, leading high-impact projects in Agile environments, with a strong focus on software scalability, system optimization, and DevOps best practices.
Languages: Java, Python, Go, Django, React.js, Node.js, JavaScript,
HTML/CSS, XML, TypeScript, C, C++, C#, Matlab, Linux
Frameworks & Tools: Git, Unit Testing (JUnit), Rest APIs, Spring
Boot, Maven, Eclipse, Android Studio, VSCode, Postman
Databases: SQL, MySQL, MongoDB, NoSQL (Redis), PostgreSQL
Methodologies & APIs: Agile, Kanban, Scrum, REST, gRPC, GraphQL
Python Frameworks: Scikit-learn, Numpy, Pandas, Plotly, Matplotlib,
Pytorch
Cloud & DevOps: Kubernetes, Docker, AWS, Jenkins, CI/CD pipelines,
Microsoft Azure, GCP, Terraform
Other: AI, Algorithms, Data Structures, Object Oriented
Programming, Software Development, MS Office Suite, Google Suite
Soft Skills: Problem-solving, Effective communication,
Cross-functional collaboration, Flexible, Effective decision-making
Software Developer with 2+ years of experience in developing and leading high-impact projects in Agile environments with a strong focus on system optimization. Proven expertise in software development, data science, data structures and algorithms, and machine learning algorithms.
Location: Boston, US
Location: Chennai, India
Below are my projects mainly on Software development, Machine Learning, Data Analytics, and Artificial Intelligence
Full-stack deployed production level real-estate management application that has clients, agents, and admin; Agent can add properties, manage viewings, sales, and transactions; Client can view properties, schedule viewings, write reviews on properties and agents, start a transaction for a property; Admin can manage the entire application and has an overall view. View Code →
A machine learning system that classifies accidents as Lethal vs Non-Lethal using rich road, vehicle, user and environment data. XGBoost demonstrated the best sensitivity to Lethal cases while maintaining stable performance across folds. Ended up in the 14th position amongst 980 teams in the Kaggle competition.
A comparative analysis of regression-based machine learning models for predicting property market valuation using the New York City Property Valuation and Assessment dataset. The study evaluates three regression models—Linear Regression, Random Forest Regressor, and Gradient Boosting Regressor—to determine their predictive effectiveness. The tuned Random Forest model achieved the strongest overall balance between bias, variance, and interpretability.
A RL-based multi-agent game that represents a heist scenario where a thief attempts to steal a cash bag from one of the rooms in the bank without being detected by the security camera or the security guard.
Using design patterns in Java, created an MVC model with 3 modes (GUI, text-based, and script file ) where an image can be loaded, and various operations like save, blur, sharpen, sepia, etc. can be performed on an image.
Below are my contributions/publications to the field of Computer Science
Below are the details to reach out to me!
Boston, MA, USA - 02119