SATHVIK

S RAO

ROLE FULL STACK & ML ENG

BASED BENGALURU, IN

STATUS AVAILABLE

CS UNDERGRADUATE• FULL STACK DEV• ML ENGINEER• IEEE RESEARCHER• FASTAPI & PYTORCH• SPRING BOOT & AZURE•

ABOUT ME

Final-year Computer Science undergraduate at SRM Institute of Technology (CGPA: 9.25) with hands-on experience building full-stack and applied machine learning systems, including computer vision pipelines and cloud-deployed backends. Published IEEE researcher and active technical community contributor.

JAVAPYTHONC++SPRING BOOTFASTAPIPYTORCHREACT NATIVEAZURE

0.00 CGPA (SRM IT)

0 IEEE PAPER

EDUCATION

SRM Institute of Technology — Tamil Nadu, India

Bachelor of Engineering in Computer Science and Engineering | CGPA: 9.25 (Jun 2023 – May 2027)

Relevant Coursework: Data Structures and Algorithms, Internet of Things

LEADERSHIP & COMMUNITY

Robothinkers Club — Member

Co-organized technical events and delivered a hands-on seminar on Arduino fundamentals to fellow students.

TECHNICAL SKILLS

Languages

JavaC++PythonJavaScriptSQLHTML/CSS

Frameworks & Libraries

Spring BootFastAPIPyTorchOpenCVReact Native (Expo)Redux Toolkit

Tools & Platforms

Git / GitHubMongoDB AtlasMicrosoft Azure

Core Expertise

Computer VisionFull-Stack BackendsREST APIsMachine Learning Pipelines

SELECT PROJECTS & RESEARCH

GITHUB ->

01 MOBILE / ML PLATFORM

POKEPRICE

End-to-end Pokémon card identification and live pricing mobile platform paired with an ML backend.

Architected React Native (Expo) mobile client with FastAPI backend using OpenCV perspective correction, ConvNeXt V2 classification, & EasyOCR for 100+ card classes.
Trained ConvNeXt V2 classifier in PyTorch on 20,000+ labeled card images (~90% recognition accuracy).
Tuned EasyOCR with character allowlisting for fast CPU text extraction; optimized image preprocessing with Expo Image Manipulator (cut payload size ~60%, API speed ~40%).
Designed RESTful API delivering card identification & live pricing in <2s average; cached scan history using Redux Toolkit & AsyncStorage (~50% API call reduction).

REACT NATIVEPYTHONFASTAPIPYTORCHOPENCVEASYOCRREDUX TOOLKIT

02 FULL STACK / AI GAME

BIG-TAC-TOE

Full-stack strategic game platform featuring MCTS AI opponent, Java Spring Boot, and Azure cloud backend.

Built single-player mode against an AI opponent using Monte Carlo Tree Search (MCTS) for strategic move selection.
Developed responsive, cross-browser frontend with HTML5, CSS3 (Flexbox/Grid), and ES6+ JavaScript.
Built and deployed RESTful backend APIs with Java Spring Boot on Microsoft Azure to manage multiplayer sessions and game logic.
Integrated MongoDB Atlas to persist user data and game history with high availability and scalability.

HTML5/CSS3/ES6+JAVA SPRING BOOTAZUREMONGODB ATLAS

03 IEEE PUBLICATION

CLIENT-SIDE vs SERVER-SIDE DBs

Published research paper in IEEE (2025) comparing database architectures and trade-offs.

Paper Title: “A Comparative Analysis on the Differences Between Client-Side Databases and Server-Side Databases”
Authors: Sathvik S Rao, Shayantan Bose, Ansh Baiju, Dr. Shajeena Elmo
Venue: Published by IEEE (2025)
Empirical performance analysis evaluating data storage paradigms, query performance, latency, and synchronization mechanics.

IEEE (2025)RESEARCHCLIENT-SIDE DBSERVER-SIDE DB

READY TO START?

LET'S TALK

EMAIL sathvik2416@gmail.com

PHONE +91 70229 25225

SOCIAL