About
Detail-oriented and solutions-driven Computer Science graduate student with over 1.5 years of research and internship experience in designing, developing, and automating healthcare data workflows. Strong foundation in data structures, algorithms, and system design, with proficiency in Python, JavaScript, and C#. Experienced in clinical data analysis, workflow automation, and secure healthcare data processing. Passionate about leveraging technology to solve real-world problems efficiently and ethically.
Junior Software Developer &AWS Cloud Practitioner
- Birthday: 20 April 2001
- Phone: +1 (656)-565-9217
- City: Tampa, FL, USA
- Age: 24
- Degree: Master's
- Email: aishurao2021@gmail.com
I design and develop automated healthcare data processing workflows, specializing in backend services with C#, .NET, and Python. With expertise in RESTful APIs, workflow orchestration (Elsa Workflows), and data integration, I build scalable solutions that streamline healthcare operations. I leverage AWS services such as Lambda, S3, Textract, and Step Functions to process clinical data efficiently and ensure HIPAA compliance. My strong foundation in data analysis, ETL processes, and database management (SQL Server, PostgreSQL) enables robust data pipelines and secure healthcare applications. Additionally, I have experience with Docker, Kubernetes, and Git for containerization, orchestration, and version control, as well as cybersecurity fundamentals to ensure optimized and compliant system designs.
Skills
My skills as a Junior Software Developer mainly comprises of the skills listed below. Additionally, there are other skills which are listed in my resume.
Experience
I have 1.5 years of research and internship experience in designing, developing, and automating healthcare data workflows.
Education
Master of Science in Computer Science
2023 - 2025
University of South Florida, Tampa, FL
Bachelor of Technology
2019 - 2023
Kakatiya Institute of Technology and Sciences,Warangal, India
Professional Experience
Graduate Research Assistant - University of South Florida
Aug 2024 - Present
Tampa, FL, USA
- Preprocessed large-scale medical image datasets using Java-based pipelines deployed on AWS Lambda and S3, applying normalization, augmentation, and feature extraction to improve machine learning model performance on Amazon SageMaker.
- Utilized Amazon Textract via Java SDK for PDF data extraction, implementing custom dictionary and post-processing logic to enhance text recognition accuracy.
- Developed an automated staging pipeline with Java and AWS Step Functions to parse pathology reports, supporting medical data classification workflows.
- Re-architected a C# .NET medical workflow solution into a Java Spring Boot application, integrating AWS SWF for scalable and fault-tolerant health data pipelines.
Research Assistant - Moffitt Cancer Center
May 2024 - July 2024
Tampa, FL, USA
- Conducted cell culturing, fixing, and feeding for melanoma and breast cancer research to observe cellular reactions under varying conditions.
- Supported development of the department’s lab website and portfolio to showcase research activities.
- Collaborated with the team to explore collagen development mechanisms, contributing to potential cancer treatment insights.
President - USF Squirrel Club
Jan 2024 - Present
Tampa, FL, USA
- Initially served as Treasurer, managing club finances transparently and efficiently.
- Coordinated support for international students, including accommodation, transportation, and insurance guidance.
- Enhanced community building for international students to ensure a welcoming environment at USF.
Projects
These are some of my projects
- All Projects
Elsa Workflows Automation Project
Worked on a modular workflow automation system using Elsa 3.5, a lightweight .NET-based workflow engine. Designed and implemented custom workflows to orchestrate background tasks and automate business logic. Integrated Elsa Server and Elsa Studio for managing and visualizing workflows, supporting HTTP endpoints, timers, and custom activities. Contributed to backend development in C# and .NET Core, handled API routing, and ensured seamless execution and persistence of workflows. Enabled extensibility and reusability for enterprise-grade workflow solutions.
Cancer Restaging Classification Pipeline
Developed a rule-based NLP pipeline to automate cancer restaging using TCGA pathology reports. Classified cases into upstaged, downstaged, likely downstaged, no change, or clinical review by extracting clinical indicators and invasion metrics. Improved staging workflow accuracy and prepared the system for integration with future AI-based stage prediction models.
This project enhanced my understanding of clinical text mining and oncology guidelines, and showcased the potential of combining regex-based pipelines with future machine learning models for scalable healthcare solutions.
Disease X Detection Pipeline
Built an end-to-end machine learning pipeline to detect Disease X using a dataset of 110,000 samples with 90 features. Explored multiple models including Logistic Regression, Random Forest, and MLP Classifier. Achieved 75% accuracy with minimal false negatives using MLP, ensuring better clinical reliability. Applied PCA for dimensionality reduction and SMOTE for class balancing to enhance model performance.