Aashrith Devulapally

Student Assistant @ Arizona State University

About

Driven by a passion for leveraging data to solve complex challenges, I am a Cloud & Data Engineer specializing in AWS, Python, and Snowflake. My mission is to architect and implement data-driven solutions that empower organizations to make informed decisions and achieve tangible results. Who I Am: A master’s candidate in Information Technology at Arizona State University, I've cultivated a robust foundation in data analytics, security, and project management. My academic pursuits are complemented by hands-on experience applying these skills in both research and industry settings. My Expertise: My core competencies include: * Cloud Computing (AWS) * Data Engineering (Snowflake, ETL) * Data Analysis (Python, SQL, Power BI) * Machine Learning I excel at designing and implementing end-to-end data pipelines, developing insightful visualizations, and building predictive models. I'm adept at utilizing Python for data manipulation, SQL for database management, and Power BI for creating interactive dashboards. Measurable Impact: I'm proud of designing and executing a data preprocessing and augmentation pipeline that enhanced model robustness by 30%. This work was presented and published at the IEEE ICONAT Conference, showcasing my commitment to innovation and impactful research. I have experience analyzing EEG data for cognitive science studies and developing AI-powered diagnostic systems. My Goals: I am actively seeking opportunities to contribute my expertise to a forward-thinking organization where I can drive data-driven innovation and make a significant impact. I am eager to collaborate with fellow professionals who share a passion for data and technology. Let's connect and explore how we can leverage the power of data to achieve remarkable outcomes! #DataEngineer #CloudComputing #AWS #Python #DataAnalytics

Country

City

United States

Industry

Computer Software

Skill

GitHub, Github enterprize, Flask, Splunk, CI/CD Pipelines, Jenkins, Azure DevOps, AWS, AutoML Platforms, Explainable AI, ML for Supply Chain Optimization, Apache Kafka, Artificial Intelligence (AI), Cognitive Science, Software Development, Research Skills, Microsoft Power BI, Data Cleaning, Data Modeling, Statistical Analysis

Experience

Student Assistant

Arizona State University

2024-12 - Present · 1 yr 10 mos

Engineered a multi-agent framework using Large Language Models (LLMs) to automate research workflows and enhance predictive accuracy in clinical trial outcome predictions by an impressive 20%, optimizing cloud operations and performance tuning. • Directed the application of prompt engineering and LLM fine-tuning techniques within domain-specific models, achieving a 15% reduction in hallucination rate during multi-system agent coordination. • Constructed high-performance anomaly detection models that identified key features, contributing to a 22% boost in prediction accuracy, enabling more efficient resource allocation. • Accelerated data workflows by orchestrating 8+ ETL pipelines utilizing Azure Data Factory, Synapse, and Databricks is compressing data ingestion and processing time by 30%. • Spearheaded incident management protocols, reducing system downtime by 95% through proactive monitoring and automated alerts.