Data Science · AI Engineering

Sahil Devulapalli

Building AI pipelines and data systems that turn raw signal into decisions.

B.S. Data Science candidate at the University of Michigan, currently shipping enterprise AI applications at AThingz. I work across the stack — from anomaly detection models to the dashboards that make them usable.

Email me → LinkedIn GitHub

Ann Arbor, MI / 248-525-0417

Experience

Where I've worked

AThingz Southfield, MI
May 2026 – Aug 2026

AI Software Engineering Intern

Developed enterprise AI applications using Python, Django, Azure AI Foundry, Azure OpenAI, Microsoft Graph API, SharePoint API, Azure SQL Database, Azure Blob Storage, Pandas, and Parquet to automate supply chain and logistics operations.
Designed end-to-end AI pipelines that extracted, validated, transformed, and stored structured shipment data from client emails and attached documents, integrating LLMs, SQL databases, cloud storage, and ETL workflows for automated processing and analytics.
Built a full-stack shipment management platform with Django featuring secure authentication, searchable shipment records, analytics dashboards, REST API integration, and real-time operational insights, improving shipment visibility and workflow efficiency across internal teams.

Projects

Things I've built

Cyber Threat Detection using Machine Learning

Implemented anomaly detection pipelines using Isolation Forests and PCA to identify suspicious behavior in 1M+ network log events, achieving 92% recall on attack patterns.
Engineered temporal features including rolling event counts and anomaly rates to improve detection sensitivity.
Built a Streamlit dashboard to visualize risk scores, anomaly trends, and alert thresholds for rapid incident triage.

Isolation Forests PCA Streamlit Python

Personal Finance Tracker

Processed and standardized 5,000+ nonprofit financial transactions into clean, structured datasets with normalized categories and timestamps for anomaly detection and spending insights.
Implemented ARIMA and Prophet models to forecast monthly expenses, reducing prediction error by 22%.
Designed dashboards using monthly spend timelines, category-wise variance plots, and anomaly flags to identify outliers and long-term budget risk.

ARIMA Prophet Data Cleaning Forecasting

Leadership

Outside the classroom

Michigan Sports Analytics Society

Data Analyst · Ann Arbor, MI · 2024 – Present

Analyzed player and team performance data using Python (Pandas, NumPy) to identify trends and predictive metrics across multiple seasons, generating actionable insights for strategy and player evaluation.

Collaborated with peers to build visualizations in Tableau and Matplotlib, communicating insights to audiences.

Michigan AI Strategy Club

Vice President · Ann Arbor, MI · 2024 – Present

Lead initiatives to explore real-world applications of AI across industries including finance, healthcare, and logistics.

Organize workshops and events to help members build practical AI skills and stay updated on emerging trends.

Investing4Youth

Co-President, Co-Founder · Novi, MI · 2020 – Present

Co-founded a nonprofit promoting educational equity; raised $3,500+ by analyzing donor outreach data, extracting actionable insights, and optimizing fundraising strategy for maximum impact.

Built the organization's website with analytics dashboards, increasing traffic 40% and securing 5+ partners and 10+ fundraisers.

Skills

Toolkit

Programming & Software Development

Python Java C++ SQL MATLAB Django OOP Data Structures Algorithms Full-Stack Development Backend Development REST APIs API Integration JSON Authentication Git GitHub

AI, Data & Cloud Technologies

Azure AI Foundry Azure OpenAI Prompt Engineering LLM Applications Pandas NumPy scikit-learn Azure SQL Database Azure Blob Storage Microsoft Graph API SharePoint API Parquet ETL Pipelines Data Engineering Database Design Data Validation Tableau Power BI

Education

Academic background

University of Michigan — College of Literature, Science & Arts

B.S. in Data Science, Minor in Computer Science · Ann Arbor, MI · Aug. 2024 – May 2028

Certified in Cybersecurity (CC) – (ISC)², July 2026.

Cybersecurity Knowledge: Security Principles, Business Continuity, Disaster Recovery & Incident Response, Access Controls, Network Security, Security Operations.

Relevant Coursework: Data Structures & Algorithms, Discrete Mathematics, Probability and Statistics, Software/Hardware/IoT, Linear Algebra, Calculus III, Programming & Data Science.

GPA
3.66 / 4.0

Off the Clock