Crafting scalable systems and AI-driven solutions with clean code for building innovative tech.
I am currently looking for full-time roles in Software Engineering and Machine Learning in the USA.
I'm a Master's Graduate from Oregon State University, majored in Computer Science, and coursework focused in Artificial Intelligence. I have 3 years of professional experience as a Software Engineer at IBM and a four-month internship with Tech-Amplifiers.
I'm currently involved in a research effort with Dr. Manish Motwani, working on a project that aims to analyze how effective are the modern ML-based REST API testing and debugging techniques in detecting real-world defects.
I am passionate about software development and machine learning, with a proven track record of delivering high-quality solutions. I enjoy solving real-world problems and believe in continuous learning and upskilling.
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Python, JavaScript, Golang, Java, TypeScript, C++, HTML, Shell
SQL (MySQL, PostgreSQL, Oracle), NoSQL (MongoDB, AWS DynamoDB)
React.js, Node.js, Express.js, Spring Boot, Flask, Redux, CSS
Docker, Kubernetes, Jenkins, Terraform, OpenShift, AWS EKS, ECS, Lambda, SQS
NumPy, Pandas, PyTorch, TensorFlow, TensorBoard, GenAI LLMs
Git, GitHub, Jira, ServiceNow, Splunk, Postman, IntelliJ, YAML, Linux
Agile, Object-Oriented Design, SDLC, TDD, Microservices, SOA, Distributed Systems
Model Fine-tuning, Time-Series Forecasting, Tokenization, Langchains, LLMs, Model Compression, CNN, RNN
"It's not the ideas; it's design, implementation, and hard work that make the difference." - Michael Abrash
Introduced Defects4REST, the first public benchmark of REST API defects systematically mined from open-source repositories. Using a semi-automated approach with NLP techniques and manual validation, the project classifies defects into a novel taxonomy of categories.
Applied machine learning techniques to analyze silicon concentration in rivers, improving accuracy by 22%. Collaborated with domain experts to validate insights and enhance ecological understanding.
A cloud-based interactive app built with the MERN stack, enabling users to securely manage notes, reminders, and themes with JWT authentication.
A multi-tier GPS-based solution for emergency response, reducing response time to under 45 seconds. Optimized police force deployment using classification techniques, cutting response time by over 50%.
Modified PostgreSQL source code for join operations, reducing execution time by over 30%. Automated ETL processes for large-scale databases and optimized join operations.
Built a React.js web portal serving curated news articles, providing users with a personalized experience.
Developed a predictive system to forecast lead conversions for term deposits. Achieved 96.73% recall using cost-sensitive learning with penalized SVC and Random Forest classifiers.
Developed a Research Lab Management application using Vue.js, Spring Boot, and PostgreSQL, simplifying well-organized logging of progress timelines, outcomes, and feedback while ensuring secure role-based access policies.
Engineered GANs to augment a skin lesion dataset, increasing training samples by 180%. Improved classification accuracy by resolving class imbalance and reducing model bias, enhancing real-world applicability.
Developed a data-driven approach to neighborhood recommendation using clustering algorithms like K-means and DBSCAN. Enhanced understanding of neighborhood characteristics to address resident preferences.
Developed a library to decrypt passwords encrypted with SHA-256 algorithms. Implemented a public API for seamless integration, documented with Swagger.
Oregon State University, Corvallis, OR
GPA: 3.75/4.0
Savitribai Phule Pune University, Pune
GPA: 3.44/4.0
ANSWER LAB, Oregon State University, Corvallis, OR
Oregon State University, Corvallis, OR
IBM, Bangalore, India
TechAmplifiers, Pune, India
I am actively seeking for full-time opportunities in the field of Machine Learning and Software Engineering.