About
I’m a Computer Science undergraduate specializing in Artificial Intelligence & Machine Learning, with a strong interest in Backend Development, Machine Learning, AIoT, and data-driven applications. I enjoy building practical solutions that combine software engineering with intelligent technologies. My technical experience includes Java, Python, SQL, Spring Boot, Hibernate, REST APIs, Flask, FastAPI, Scikit-learn, TensorFlow, React, MySQL, Git, Docker, and AWS. During my Data Analyst Internship at IBM SkillsBuild & CSRBOX, I worked on a heart disease prediction system, developing an end-to-end pipeline from data preprocessing and ETL to machine learning inference and integrating prediction capabilities into a web application. I have also worked on an AIoT Occupancy Detection & Estimation System, combining STM32, VL53L0X ToF sensors, UART/WiFi communication, machine learning, FastAPI, and React to develop a real-time monitoring and people-estimation solution. Some of my key projects include: TomatoCare — CNN-based tomato maturity detection and harvest recommendation system AIoT Occupancy Detection & Estimation System — real-time occupancy detection and people estimation Employee Management System — Java, Spring Boot & MySQL backend application NLP Grammar & Spelling Checker — NLP-based grammar correction system I’m continuously developing my skills in backend engineering, artificial intelligence, machine learning, and scalable software development, while looking for opportunities to work on meaningful technology-driven solutions. Portfolio: https://sinchana1408.github.io/sinch_portfolio/ GitHub: https://github.com/sinchana1408 Kaggle: https://www.kaggle.com/sinchanashivanand LeetCode: https://leetcode.com/Sinchana_sinch/ Email: sinchanashivanand1408@gmail.com
Work experience
AIOT intern at DigiToad Technologies, Jan 2026 - May 2026 · 5 mos, Bengaluru, Iot, STM32,ML
Data Analyst at IBM SkillsBuild & CSRBOX, Jun 2024 - Aug 2024 · 3 mos, Developed and integrated a heart disease prediction module into a web application using Python, Scikit-learn, and REST APIs. Designed end-to-end data pipeline (ETL to inference) and led a 4-member team following Agile practices and Git-based workflows. Focused on backend logic optimization, ensuring accurate real-time risk classification with clean, maintainable code.
