Java, SQL, Mysql, Javascript, Machine Learning, Computer Vision

SAYEERA SHAIK

573-***-**** **************@*****.*** LinkedIn GitHub

EDUCATION

University of Missouri Columbia Columbia, MO

Master of Science in Computer Science 8/2022 - 07/2024 Machine Learning Data Structures Object-Oriented Programming TECHNICAL SKILLS

Programming & Backend: Java Programming, Python & Django, SQL, Machine Learning, Data Visualization, Computer Vision Databases: MYSQL, MongoDB, MSSQL

Cloud & DevOps: AWS (Lambda, EC2, API-Gateway, RDS, IAM, S3), Azure, GCP, Docker, Jenkins, Linux, Kubernetes Frameworks & Tools: React, Flask, Spring Boot, HTML, JavaScript, Node.js, Kafka, RESTful APIs, Postman, Git WORK EXPERIENCE

University of Missouri Columbia, MO

Research Software Developer May 2024 – present

• Built a Django-based web platform integrated with JavaScript, AWS Lambda, and MSSQL to streamline agricultural data collection and experiment tracking, improving data visibility for 50+ researchers and reducing manual entry time by 40%.

• Designed and trained a YOLOv8 deep learning model in Python to detect plant stem nodes with 94% precision, enabling automated internode analysis for 150+ agricultural samples.

• Developed a computer vision post-processing pipeline using OpenCV and NumPy to compute stem diameters and node spacing, integrating outputs into the database for scalable research workflows. Tata Consultancy Services Hyderabad, IND

Software Engineer May 2019 – Aug 2022

• Integrated enterprise-grade SFMS with Core Java, JSP, and MySQL to optimize message processing, reducing latency and improving the processing speed by 40% across banking systems.

• Designed and implemented RESTful APIs for NEFT and RTGS systems using Java, enhancing transaction security and integration reliability.

• Tuned complex SQL queries and restructured MySQL database schemas to reduce data access latency and improve financial reporting performance by 25%.

• Built reusable service-layer components and utility classes in Java to streamline core transaction logic and significantly reduce code duplication. Integrated exceptional handling, custom logging, and error recovery mechanisms to increase backend system stability and traceability.

ACADEMIC PROJECTS

Corn & Soybean Stem Analysis Pipeline Python, OpenCV, YOLOv8, Computer Vision May 2025- Present

• Designed a complete image-processing pipeline for node detection, diameter measurement, and internode length calculation using skeleton tracing and edge-based diameter estimation.

• Automated batch processing, annotated result generation, and Excel summary reporting for large-scale phenotyping experiments using Pandas, NumPy, Matplotlib, and Scikit-Image. Nitrogen Trail Web Application & Automation Python, Django, JavaScript, Docker, AWS May 2024 – May 2025

• Developed a field-level water–nitrogen decision-support web app with dynamic dashboards, real-time data visualization, and IoT-driven recommendations.

• Automated end-to-end workflows, containerized using Docker, and deployed on AWS for scalable cloud-based precision agriculture simulations.

Single-Cell Protein Analysis Platform React, Flask, Docker, Cloud Deployment Dec 2023- July 2024

• Built an interactive React-based platform integrating machine learning for single-cell sequencing data analysis.

• Automated workflows with Docker and deployed on cloud platforms, ensuring reproducibility, scalability, and seamless Git- based version control.

P3DB – Protein Structure Analysis Platform Angular, TypeScript Jan 2022 – Aug 2023

• Developed an interactive web application for visualizing and analyzing protein structures, improving usability for researchers.

• Implemented dynamic data visualization features to support protein interaction and molecular structure studies. Digital Sign Boards (IoT) Raspberry Pi, OpenCV, LoRa May 2018- May 2019

• Built a smart traffic signboard to detect license plates, estimate traffic density, and display travel time updates on an LCD — all without internet.

• Designed for real-time, low-latency computation, enabling decision-making and data display in remote environments using embedded systems and lightweight C++/MATLAB routines.

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