Hello, I'm Mayank Vyas
Brewing Software with AI Solutions.
Work Experience
Software Engineer, Research at Coral Labs
Tempe, Arizona
- Engineered a scalable and fault-tolerant data ingestion pipeline on AWS using Apache Spark, processing 1.2 TB of data (NQ tables) while reducing system latency by 3x
- Optimized system performance by designing pruning algorithms to discard irrelevant data segments, improving information retrieval recall and reducing resource consumption
- Developed and tested a distributed, 3-stage meta-reasoning engine, achieving an 11% performance improvement over existing baselines on temporal-reasoning benchmarks
Founding Software Engineer at Job-Hunt AI
Tempe, Arizona (Self-Employed)
- Architected an end-to-end AI automation pipeline using Elasticsearch for high-speed semantic search and a knowledge graph to map complex relationships between job requirements and user skills
- Developed an LLM-based agentic workflow that autonomously parses job descriptions and aligns them with candidate resumes, improving job match relevance by 92% and reducing manual search time by 98%
Software Engineer, Machine Learning Architecture at Indian Institute of Information Technology
Chennai, TamilNadu
- Architected and deployed a resilient end-to-end IoT system on resource-constrained hardware (Raspberry Pi), automating deployment and monitoring processes
- Optimized C++ inference kernels to achieve 35% lower latency, enabling real-time anomaly detection and data streaming to AWS
- Designed an on-device predictive filtering algorithm that reduced sensor data transmission by 95%, significantly lowering operational costs and network load
Projects
Transform educational questions into interactive, story-based visualizations using AI. Features a 4-layer pipeline that intelligently routes content from documents (PDF/DOCX) to 18 distinct game templates with intelligent caching and real-time progress tracking.
Research project investigating efficiency, scalability, and linguistic adaptability of Fine-Tuned LLMs for code generation. Explores LoRA rank optimization, data scaling effects, and cross-language generalization using GPT-2.
Python pipeline to convert inspection JSON data into populated TREC (Texas Real Estate Commission) HTML reports. Features smart mapping across 6 TREC sections, automatic empty section removal, and proper formatting for comments, images, and videos.
Automated data extraction and real-time visualization pipeline for Intel's retail edge computing platform. Built Python scripts to extract metrics from results logs and publish to an MQTT broker, integrated with Grafana dashboards via the MQTT plugin. Created custom Docker images for Grafana and MQTT configured to communicate on the same Docker network using Docker Compose.
This project is part of a Bachelor's Research Thesis, aiming to detect and segment primary roots in plant images using a customized version of the Mask R-CNN model adapted for TensorFlow 2.0 and Keras 2.2.8. The original codebase from Matterport's Mask R-CNN was modified for compatibility and to support training and inference on annotated root datasets.
This projects implementation of a Multi-Layer Perceptron (MLP) from scratch using Python. It demonstrates the fundamental concepts of building and training a neural network, including forward propagation, backward propagation, and parameter optimization.
About Me
A glimpse into my journey, passions, and the adventures that shape who I am
Hey there! I'm Mayank, a Master's student in Data Science at Arizona State University. My story is one of curiosity-driven pivots and bold decisions.
I started my academic journey with a Bachelor's in Electrical Engineering from IITRAM, where I got hands-on experience with electrical machines and power systems. But somewhere along the way, I found myself increasingly fascinated by Machine Learning, AI, and distributed systems.
Before ASU, I spent one and a half years at IIITDM Kancheepuram as a research intern, diving deep into computer vision and deep learning. Then came a crossroads: a full-time offer from Micron as a Process Engineer. It was a secure path, but my heart was set on something different.
I took the leap—declining the offer to pursue my Master's at ASU, betting on myself to validate and deepen my expertise in the AI/ML domain. And honestly? It's been the best decision I've made.
Languages
AI/ML
Web & Frameworks
Infrastructure
Databases
Tools
As a Data Science student at ASU, I architect intelligent systems by specializing in RAG (Retrieval-Augmented Generation) pipelines for LLMs and developing sophisticated AI Agents. My core expertise lies in Natural Language Processing, where I design high-performance retrieval algorithms to power next-generation AI applications.
I translate complex theory into real-world impact. My projects include analyzing Time Series data for robust IoT Pipelines in smart agriculture, and engineering a production-ready, dockerized pipeline for Intel's automated self-checkout system with Grafana visualization.
I also engineered a Masked R-CNN pipeline to detect the primary root length of plant species like wheat, brassica napus, and arabidopsis thaliana—helping biologists study the root phenome more effectively.
Building innovative solutions under pressure - here are some memorable hackathon moments.
Gamify
Zoom App Hackathon
Developed a Zoom application leveraging real-time transcription to automatically generate interactive quizzes using Gemini AI with seamless platform integration.
TwinGenius
Devils Invent - Honeywell & ASU
Revolutionized industrial digital twin creation by generating complete environments from natural language prompts in under 60 seconds using Gemini AI and AWS IoT TwinMaker.
Life isn't just about algorithms and neural networks (though I do love those!). I believe in living fully and finding joy in diverse experiences.
Hiking & Trekking
Arizona's trails are my weekend therapy
Pool & Golf
Precision sports that clear my mind
Photography
Capturing moments and landscapes
Road Trips
Exploring the American Southwest
Golf days
8-ball enthusiast
Mountain adventures
Good times with great people
"The best way to predict the future is to create it."
— My guiding philosophy
When I'm not coding, I'm exploring the beautiful landscapes of the American Southwest. From the majestic Grand Canyon to the iconic Golden Gate Bridge, every destination teaches me something new.
Grand Canyon, Arizona
That's me!
San Francisco, California
Walking the iconic bridge
Water Wheels Bridge, Payson
GitHub Contributions
contributions in 2026
Education
Master of Science in Data Science
Aug 2024 - May 2026
Tempe, Arizona
Bachelors of Science in Electrical Engineering
Aug 2020 - May 2024
Ahmedabad, India