About
I like understanding how software works, then making it easier to build on.
I'm a Software Engineer at Thermo Fisher Scientific, where I moved into a full-time role in July 2026 after completing a Software Intern position. I graduated from Amrita Vishwa Vidyapeetham in May 2026 with a B.Tech in Computer Science and Engineering.
My interests are in backend engineering: Java, Spring Boot, Python, APIs, and database design. My projects explore service workflows, messaging, and route planning. I value clear boundaries, readable code, and the practical work of debugging and maintaining an application.
Technical profile
- Core languages
- Java, PythonC, C++
- Backend & APIs
- Spring BootFastAPI, Spring Security, Hibernate / JPA, REST APIs, WebSockets
- Data & persistence
- MySQL, MongoDB, SQLAlchemy
- Frontend
- JavaScript, React, HTML, CSS, Thymeleaf, Tailwind CSS
- ML & AI integration
- scikit-learn inference, Gemini API integration
- Developer tools
- Git, GitHub, Vite, Jira
Experience
-
Software Engineer
Thermo Fisher Scientific
- Develop backend features for an internal project using Java, Spring Boot, and Python.
- Design databases and RESTful APIs, and monitor production incidents.
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Software Intern
Thermo Fisher Scientific
- Built frontend screens for application entities.
- Contributed to database and RESTful API design.
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Java Fullstack Developer Intern
Infosys Springboard / CarCaddy Project
- Developed REST services with Spring Boot, Hibernate, and MySQL for authentication, bookings, and customer feedback.
- Used a layered architecture and collaborated on features across Agile sprints.
- Participated in code reviews and tracked defects through Jira.
Projects
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MindBridge — AI-Assisted Behavioral Screening Platform
MindBridge combines behavioral questionnaires, cognitive tasks, and AI-assisted analysis in a React and FastAPI application. It supports structured screening and professional review, not medical diagnosis.
React · Python · FastAPI · MySQL · scikit-learn · Gemini
Screening, tasks & assisted analysis
Key features
- Questionnaire workflows: authenticated screening sessions, response scoring, and stored result history.
- Cognitive tasks: interactive React assessments backed by FastAPI session and result endpoints.
- Assisted analysis: scikit-learn model inference and Gemini integrations for journal analysis and recommendations.
- Professional review: role and consultation checks for record access, with PDF summaries generated using ReportLab.
Architecture & stack
- Frontend
- React, Vite, Axios
- Backend
- Python, FastAPI, REST APIs
- Persistence
- MySQL, SQLAlchemy
- Analysis & reports
- scikit-learn, Gemini, ReportLab
Scope
AI-assisted features depend on the saved model and configured Gemini access. Outputs are intended for professional interpretation.
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Kamiyapp — Skill Sharing Platform
A structured way to find and book local skilled workers. Requesters and workers move through booking, inspection reports, work tracking, and feedback in one role-based application.
Java · Spring Boot · Spring Security · Hibernate · MySQL
Booking workflow & backend
Problem
Local service work often has no structured booking process, no cost estimate before work starts, no record of progress, and no accountability through ratings.
How it works
- A requester searches for a worker by skill and creates a booking request.
- The worker accepts the booking and submits an inspection report with the problem, estimated cost, and estimated completion time.
- Once the inspection is submitted, work can begin; start and completion times are recorded.
- After completion, both parties leave ratings and feedback.
Backend implementation
- Layered architecture: Controller → Service → Repository
- Role-based authentication and authorization for requesters, workers, and admins with Spring Security
- JPA/Hibernate entity mapping on MySQL
- Booking lifecycle state handling
- Email notifications for booking updates and status changes
Stack
- Backend
- Java, Spring Boot, Spring MVC, Spring Security, JPA/Hibernate
- Database
- MySQL
- Frontend
- Thymeleaf, HTML, CSS, Tailwind CSS
Architecture and interface
System architecture 
Fig. 1a — Bookings 
Fig. 1b — Feedback -
Zero Trust Messaging Application
Real-time messaging and file transfer exploring a zero-trust model. The application combines email verification and multi-factor sign-in with message encryption and new-device alerts.
Java · Spring Boot · Spring Security · WebSockets · MongoDB
Messaging & authentication
Key features
- Email verification
- Accounts are activated through email verification.
- Multi-factor authentication
- Login requires a password and a one-time password sent by email.
- Message encryption
- Messages are encrypted with AES, and the AES key is encrypted with the recipient's RSA public key.
- File transfer
- Files are encrypted, chunked, and sent with per-file AES keys.
- Sensitive mode
- Messages and files marked as sensitive expire and are deleted after a short period.
- Anomaly detection
- Logins from a new device or IP address trigger email alerts.
- Admin dashboard
- Admins can review trusted devices and user activity logs.
Stack
- Backend
- Java 17, Spring Boot 3, Spring Security, Spring WebSocket, Spring Data MongoDB
- Database
- MongoDB
- Frontend
- Thymeleaf, Tailwind CSS
- Client-side crypto
- CryptoJS, JSEncrypt, TweetNaCl.js
Architecture and interface
System architecture 
Fig. 2a — Secure chat (sender addresses redacted) -
CarCaddy — Car Rental Automation
Built as a team project during the Infosys Springboard internship, CarCaddy manages car rentals, from availability and reservations to customer records and billing. My contribution focused on REST services for authentication, bookings, and customer feedback.
Java · Spring Boot · Hibernate · MySQL · REST APIs
My contribution & rental workflow
My contribution
- Developed RESTful backend services using Spring Boot, Hibernate, and MySQL.
- Delivered features including user authentication, booking management, and customer feedback across Agile sprints.
- Implemented a layered architecture to keep the codebase maintainable.
- Took part in code reviews and defect tracking through Jira.
Key features
- Booking management
- Car availability and reservations
- Inventory control
- Track car status and maintenance
- Customer management
- Store customer data and history
- Billing
- Automated invoice generation
Stack
- Backend
- Java, Spring Boot, Hibernate
- Database
- MySQL
- APIs
- RESTful APIs
- Frontend
- HTML, CSS, JavaScript
-
Delivery Route Optimizer
A desktop route planner for last-mile delivery. A KD-Tree selects the next delivery stop; Dijkstra’s algorithm finds the shortest path to it through a weighted road network.
Java · Swing · KD-Tree · Dijkstra’s algorithm
Route-planning algorithm
How it works
- The road network is modelled as a weighted graph of locations around Pulivendula, Andhra Pradesh, using real latitude and longitude coordinates and road distances in kilometres.
- A KD-Tree is built over the remaining delivery stops, and a nearest-neighbour search using great-circle distance selects the next stop.
- Dijkstra's algorithm computes the shortest path to that stop, and the process repeats until every stop has been visited.
- A Swing interface lets the user choose the start point and delivery stops, draws the route on the network, and reports the total distance travelled.
Stack
- Language
- Java
- UI
- Java Swing
- Data structures
- KD-Tree, weighted graph (adjacency lists), stack
- Algorithms
- KD-Tree nearest-neighbour search, Dijkstra's algorithm
Education
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Amrita Vishwa Vidyapeetham
B.Tech, Computer Science and Engineering
Graduated May 2026 CGPA 8.8
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Manimukunda Secondary School
Higher Secondary Education · Rupandehi, Nepal
GPA 3.57/4.0
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Jaycees KinderGarten High School
Secondary Education · Rupandehi, Nepal
GPA 3.40/4.0
Certifications
Contact
Questions about a project or my engineering work?
[email protected]Email me directly, or use the form.