Summary
Skills
Work History
Education
Overview
Projects
Generic

Madhav Mangalagiri

blacksburg,Virginia

Summary

Computer Science student at Virginia Tech with experience in software engineering, AI, and machine learning. Skilled in prompt design, LLM evaluation, and building practical projects using Java, Python, and Kotlin. Strong background in algorithms, data structures, and UI/UX collaboration. Passionate about improving AI reasoning and producing high quality, domain specific insights.

Skills

  • Programming: C, C, Java, Python, JavaScript, SQL
  • Software Development: Object-Oriented Design, Data Structures & Algorithms, Multi-Threading,
    Debugging, Performance Optimization
  • Web & Cloud: JSF, PrimeFaces, React, FastAPI, HTML/CSS, AWS (EC2/S3)
  • AI & ML: LangChain, OpenAI APIs, Chatbot Design, TensorFlow (Basics)
  • Tools: Git, Docker, VS Code, IntelliJ, Linux (rlogin)
  • Soft Skills: Problem Solving, Team Collaboration, Time Management, Adaptability

Work History

EchoMe Project- Independent

Virginia Tech
Blacksburg, South Carolina
10.2025 - Current
  • Designed a high fidelity prototype for a real-time emotion and tone feedback tool using Figma.
  • Contributed to prompt based tone analysis logic and evaluated model feedback for accuracy and user clarity.
  • Conducted user persona creation, problem definition, and interface design to improve user communication experience.

AI Researcher- Virginia tech

Independant
Blacksburg, Virginia
08.2025 - Current
  • Researched how AI systems impact modern game design, including NPC behavior, procedural content generation, and adaptive difficulty.
  • Designed structured prompts and evaluated LLM outputs for correctness, clarity, and reasoning quality.
  • Synthesized technical findings into clear explanations for non-expert audiences, demonstrating strong analytical and communication skills.

Software Engineering Experience- Independent

Virginia Tech
Blacksburg, Virginia
01.2025 - Current
  • Built complex data structures including PR Quadtrees and Skip Lists to support spatial and name-based queries.
  • Improved code reliability through advanced debugging, unit testing, and mutation testing across multiple algorithms.
  • Developed full-stack and systems level applications using Java, Python, Kotlin (Android), and RISC-V assembly.
  • Implemented external-memory Quicksort with an LRU buffer pool, optimizing disk I/O and recursive partition logic.

Teaching Assistant

University of North Carolina at charlotte
Charlotte, North Carolina
01.2023 - 05.2023
  • Led problem solving sessions and helped students improve in calculus.
  • Tracked attendance and grades to maintain accurate academic records.
  • Communicated regularly with faculty about student progress and support.

Education

Bachelor of Science - Computer Science

Virginia Tech
Blacksburg, VA
07-2026

Bachelor of Science - Computer Science

University of North Carolina At Charlotte
Charlotte, NC
05-2024

Overview

3
3
years of professional experience

Projects

PR Quadtree + SkipList spatial database — Java, data structures, algorithms, JUnit

  • Built a spatial database supporting fast region searches and key lookups using PR Quadtrees and Skip Lists
  • Implemented insertion, deletion, duplicate handling, and geometric boundary checks
  • Improved reliability with detailed unit tests and edge-case debugging.

Mutation Testing Framework for PRQuadTree System — Java, PIT Mutation Testing, JUnit

  • Designed mutation tests to expose hidden logic errors and weak branches in PRQuadTree and SkipList modules.
  • Increased mutation coverage by creating targeted, high-precision test cases.
  • Strengthened system robustness by validating critical decision paths.

External-Memory Quicksort with LRU Buffer Pool — Java, File I/O, Systems Programming

  • Implemented Quicksort on large binary files using a custom LRU buffer pool for optimized block access.
  • Reduced disk I/O by tuning recursion depth, partition logic, and block caching.
  • Improved runtime performance by identifying and resolving major bottlenecks.

MovieDB Android App (TMDB API + Room) — Kotlin, Jetpack Compose, TMDB API, Room

  • Built an Android app that fetches movie data from the TMDB API with modern Compose UI screens.
  • Added local caching using Room to store favorites and minimize repeated network calls.
  • Created responsive UI layouts with loading states, pagination, and smooth navigation.

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