Aryan Varmora

Full-stack software engineer and M.S.

Computer

Science candidate at Fordham University (GPA: 3.8) with 2+ years of experience building scalable web applications, RESTful APIs, cloud-deployed systems, and applied ML pipelines. Reduced GPU pipeline runtime by 22% across 120+ datasets and shipped production features serving 500+ users at Neev Infosoft. Skilled in React, Node.js, Python, C#, SQL/NoSQL, Docker, and GCP — focused on shipping reliable, end-to-end software systems.

Graduate Research Assistant at Fordham University (2024-08 – Present)

• Engineered GPU-accelerated Python pipelines for 3D brain atlas segmentation across 120+ datasets using CuPy, NumPy, and OpenCV; migrated MATLAB workflows into modular, reusable Python components.
• Optimized vectorized computation and data-processing logic, reducing pipeline runtime by 22% and improving reliability by 18% through root-cause debugging of multi-stage failures.
• Converted experimental computer vision and deep learning workflows into reproducible software modules with Git-based version control; cut dataset onboarding time by ~40% through checkpointing and modular design.

Teaching Assistant – Data Mining at Fordham University (2026-01 – Present)

• Supported 30+ graduate students across 8 assignments on Decision Trees, Naive Bayes, K-means, Apriori, and SVM; reviewed ML implementations, validated model outputs, and maintained a zero re-grade request rate through structured rubric-driven feedback.
• Held weekly office hours responding to 50+ student queries on algorithm implementation and debugging; improved average assignment submission quality across successive iterations.

Software Engineering Intern at Neev Infosoft (2022-09 – 2024-02)

• Shipped full-stack features for DataZaap, a production SaaS platform serving 500+ users, using ASP.NET, C#, React.js, and MySQL across 5+ release cycles; integrated OpenAI ChatGPT API into a live chatbot, reducing average support query resolution time by ~35%.
• Owned end-to-end feature validation across frontend behavior, backend API responses, database queries, and data integrity; reduced post-release incidents by ~30% through systematic pre-production regression checks.
• Improved application reliability by debugging frontend/backend integration issues, resolving MySQL data inconsistencies, and coordinating fixes through senior review and stakeholder sign-off.

M.S. in Computer Science – Fordham University (2024-08 – 2026-05)

B.Tech in Computer Engineering – Silver Oak University (2020-09 – 2024-05)