Education
Work Experience
- New position, collaborating with researchers at MIT FMML to build and evaluate machine learning models for healthcare and women's health studies.
- Integrated a Rapidly-exploring Random Tree (RRT)-based motion planning algorithm into NVIDIA Isaac Sim using Python, interfacing with underlying C++ planning libraries to enable global path planning for a mobile-based robot.
- Designed and generated randomized maze-like simulation environments in Python to model real-world navigation constraints and evaluate planner success rates across diverse scenarios.
- Developed Python-based data processing pipelines to clean and structure patient monitoring datasets exported from REDCap systems, improving data quality and reducing manual workload.
- Evaluated patient-generated health data from a blood pressure telemonitoring study to identify trends supporting data-driven clinical decision-making, presenting findings and reporting statistical changes to the principal investigator.
- Guided development of student engineering projects by debugging code and assisting with implementation of web-based systems using Python, Bootstrap, and API integrations.
- Troubleshot technical issues across hardware and software workflows, including 3D printing, laser cutting, and CNC machining, ensuring successful project execution.
Education
Work Experience
- Reduced PLC license validation time by 30% by engineering a GSE mechanism for Unity M580 industrial controllers using C# and WPF with full unit test coverage, directly supporting factory automation workflows.
- Decreased carbon emission reporting latency for manufacturing plants by architecting a real-time edge computing pipeline using Python and FastAPI, improving operational visibility into production metrics.
- Accelerated vulnerability inspection workflows by building user management dashboards and RBAC-based access controls using Angular and ASP.NET.
- Reduced application load times by 20% by refactoring .NET, WPF, and Angular codebases supporting industrial automation software, with maintained unit test coverage across all modules.
- Accelerated database query execution by 40% by designing an ORM-based data architecture using SQLite and SQLAlchemy.
- Shipped production-ready RBAC system using C#, Angular, and .NET with zero vulnerabilities across Sonar and Coverity static analysis; delivered clean, well-tested code reviewed by senior engineers.
- Worked under Dr. Rimjhim Padam Singh as a research scholar and published a work on leveraging Spiking Neural Networks for fashion dataset classification — IEEE, 2024.
- Worked under Dr. Jyotsna C. as a research scholar and published a work on CNN-based neural networks for age estimation with diverse facial datasets — IEEE, 2024.
