My Experiences

Fullstack Developer Volunteer

CuraJOY - New York

• Built React and Node.js microservices on AWS Amplify, scaling throughput by 35% for 3,000+ monthly active users.
• Optimized PostgreSQL queries and Redis caching, reducing API latency by 30% and improving global data consistency.
• Automated CI/CD pipelines with GitHub Actions, reducing deployment failures by 40% and accelerating release cycles by 25%.
• Conducted WCAG/508 accessibility testing, cutting compliance issues 40% and improving user adoption across devices.
• Led peer code reviews and regression testing, raising code reliability and reducing defects by 35%.

Software Developer Intern

Accenture - Mumbai

• Built Java-based microservices with SQL backends, improving service uptime by 20% and streamlining workflows.
• Automated monitoring using Python and Linux CRON jobs, cutting manual workload by 40% and SLA response time.
• Integrated REST APIs into cloud apps, reducing sync failures by 25% and increasing API success rates by 30%.
• Designed structured logging pipelines, reducing error resolution time by 30% for production support teams.

Software Engineering Intern

Vidyalankar Institute of Technology - Mumbai

• Built real-time dashboards with JavaScript and Firebase, improving accessibility and adoption by 50% across users.
• Designed responsive UI components and integrated REST APIs, reducing bug reports by 20% and boosting retention by 30%.
• Applied MVC design patterns and modular architecture, reducing integration complexity by 25% for future projects.
• Optimized backend queries and caching, improving response speed from 3.2s → 1.8s across multiple endpoints.

Research Assistant | ML for 2D Material Discovery

Stevens Institute of Technology - Hoboken, New Jersey

• Contributed to research on accelerating 2D materials discovery using ML models for electronics, optoelectronics, and quantum computing.
• Conducted literature review on deep generative approaches (CDVAE, MTG pipeline, GANs) for TMD characterization.
• Identified and evaluated Computational 2D Materials Database (C2DB) as a primary dataset for ML model training.
• Analyzed feasibility of ML pipelines (CDVAE, MTG) for generating novel 2D material structures.
• Implemented CDVAE locally to generate stable 2D materials, validated with Density Functional Theory (DFT).
• Applied computational techniques including Crystal Structure Prediction (CSP) and Phonon Dispersion Analysis.
• Tools & Technologies: Python, PyTorch, TensorFlow, C2DB, 2DMatPedia, MC2D, V2DM, DFT

Stevens Institute of Technology

Masters of Science in Computer Science

3.71 / 4.00

• Data Structures and Algorithms
• Cloud Computing
• Web Development
• Database Management Systems