Vignesh Shanmugasundaram

I am a Master's student in Computer Science at New York University (NYU Tandon). Most recently, I completed a Software Engineering internship at Amazon, where I built automated A/B testing workflows for Amazon Ads.

My interests span full-stack development, AI/ML applications, and cloud-native solutions. I enjoy building systems that solve real-world problems — from high-performance search engines to accessibility tools for the visually impaired. My broader interests include distributed systems, data engineering, and applying machine learning to practical applications.

Previously, I worked as a Software Engineer at Zoho Corporation where I optimized search efficiency by 75% and migrated legacy applications to modern architectures. During my undergrad at Anna University, I published research on IoT-based wildlife protection systems and security protocols.

Beyond tech, I enjoy playing cricket, exploring new cuisines, and working on creative side projects that combine design with engineering.

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Vignesh Shanmugasundaram

News

[Feb 2026] Paper on Efficient Sparse Neural Retrieval in preparation for submission
[Sep 2025] Completed Software Engineering Internship at Amazon
[Jun 2025] Started as Software Engineering Intern at Amazon, working on Ads A/B testing
[Apr 2025] Won 1st place at AI Agents Hackathon for video generation platform
[Mar 2025] Featured by NYU Tandon Engineering for AI research work
[Feb 2025] Won Renewable Energy AI Hackathon with ESG optimization framework
[Sep 2024] Started MS in Computer Science at NYU Tandon School of Engineering
[Jul 2024] Completed 2+ years as Software Engineer at Zoho Corporation
[Feb 2022] Published IEEE paper on Forest Fire Detection using Sensor Networks

Current Focus

Graduate Studies: Completing my Master's degree in Computer Science at NYU Tandon, with focus on AI/ML, distributed systems, and cloud computing.

Research: Working on efficient sparse neural retrieval methods for large-scale document search, exploring applications of machine learning in information retrieval systems.

Projects

Selected projects are highlighted. See GitHub for a full list.

High Performance Search Engine
High-Performance Search Engine with BM25 Ranking
Vignesh Shanmugasundaram
C++, Information Retrieval, 2024
GitHub
A high-performance search engine built with C++ featuring BM25 ranking algorithm, inverted indexing, and efficient document retrieval achieving sub-millisecond query times.
MindSentinel AI
MindSentinel: AI-Powered Mental Health Content Analysis
Vignesh Shanmugasundaram, Team
Python, Kafka, PySpark, 2024 78% Accuracy
GitHub
Real-time streaming pipeline analyzing mental health content using Kafka, PySpark, and KoalaAI. Processes data at scale with distributed computing for content moderation.
Audio Environment Simulator
Audio-Based Environment Simulator for the Visually Impaired
Vignesh Shanmugasundaram, Team
Python, TensorFlow, OCR, 2021 Runner-Up
GitHub
Accessibility tool using real-time object detection and OCR to provide audio-based environmental awareness for blind users. Features directional audio cues and modular architecture.
AI Video Generation
AI-Powered Video Generation Platform
Vignesh Shanmugasundaram, Team
AI Agents Hackathon, 2025 1st Place
GitHub
Content creation platform combining diffusion models and local LLMs to create realistic, customizable videos with automated lip-sync and companion AI behavior.

Publications

Sparse Neural Retrieval
Efficient Sparse Neural Retrieval for Large-Scale Document Search
Vignesh Shanmugasundaram
In Preparation, 2026 Preprint
ArXiv (Coming Soon)
A novel sparse neural retrieval framework combining learned sparse representations with efficient indexing structures for scalable document search, achieving state-of-the-art performance on standard IR benchmarks.
Forest Fire Detection
Forest Fire Detection and Guiding Animals to a Safe Area by Using Sensor Networks and Sound
Vignesh Shanmugasundaram, Co-authors
IEEE ICAISS, 2022
Paper
Wireless sensor network system for early wildfire detection using deep learning, combined with an innovative audio-based animal guidance system to protect wildlife during emergencies.
PUF Security
Key Digitalization Using Physically Unclonable Function and SHA-512
Vignesh Shanmugasundaram, Co-authors
Technical Report, 2021
PDF
Novel security approach using PUF hardware fingerprints and SHA-512 cryptographic hashing for generating unclonable digital keys and time-based OTPs for home access control.

Experience

Software Engineering Intern, Amazon.com Inc.
Jun 2025 – Sep 2025
Building automated A/B testing workflows for Amazon Ads. Designed metrics dashboard eliminating 10+ hours of manual queries. Implementing cloud-native data workflows with AWS (S3, Lambda, CloudWatch).
Software Engineer, Zoho Corporation
May 2022 – Jul 2024
Optimized search efficiency by 75% (60ms to 15ms per 1000 records). Migrated legacy calendar app to component-based architecture, reducing loading time by 50%. Built full-stack features using Java, JavaScript, and SQL.
Software Engineer Intern, Zoho Corporation
Sep 2021 – Apr 2022
Designed and launched Monthly Budget Management tool for web/mobile. Integrated visual analytics and automated reminders for personal finance tracking.
Full Stack Developer Intern, AB Plastomech
May 2021 – Aug 2021
Built secure full-stack application with authentication, RESTful APIs, and interactive dashboards for real-time production monitoring using Node.js and React.

Awards & Achievements

Hackathon Wins

Academic & Professional

Education

Master of Science in Computer Science, New York University
Sep 2024 – May 2026
NYU Tandon School of Engineering, New York, NY. Focus: AI/ML, Distributed Systems, Cloud Computing.
Bachelor of Engineering in Computer Science, Anna University
Aug 2018 – May 2022
Tamil Nadu, India. Projects in full-stack development, security systems, and mobile applications.

Technical Skills

Languages

Python, C, C++, Java, JavaScript, SQL, HTML, CSS

Frameworks & Libraries

FastAPI, React, Node.js, Flutter, LangChain, PyTorch, TensorFlow, Pandas, NumPy

Cloud & Infrastructure

AWS (EC2, S3, Lambda, CloudWatch), Google Cloud (GCS, Pub/Sub, DataFlow), Firebase

Databases & Tools

MySQL, PostgreSQL, MongoDB, Redis, ElasticSearch, Docker, Git, Kafka, Spark

Media Coverage

My work has been featured in: