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Hotragn Pettugani

Boston, United States

I build production-grade software at the intersection of full-stack engineering and applied AI. Most AI projects die between the demo and deployment. I specialize in making sure they don't. From designing fuzzy matching algorithms that replaced 40+ hours of manual enterprise data work to building end-to-end systems with React frontends, cloud-native backends, and ML pipelines - I focus on shipping solutions that work at scale, not just in a notebook. What sets me apart is range.

I've architected across all three major clouds (AWS, Azure, GCP), led engineering teams as Tech Lead at Google Developer Group on Campus, captained the AWS Cloud Club, and done deep research in NLP and computer vision - all while building full-stack applications from the ground up. I don't just build models.

I build the systems around them. I care about the full picture: clean architecture, reliable data pipelines, thoughtful UX, and infrastructure that scales. I write about tech, system design, AI engineering, and the craft of building software that matters. Open to connecting with engineers, tech leaders, and teams solving hard problems.

Hotragn Pettugani Points
Academic 20
Author 3
Influencer 53
Speaker 0
Entrepreneur 0
Total 76

Points based upon Thinkers360 patent-pending algorithm.

Thought Leader Profile

Portfolio Mix

Company Information

Areas of Expertise

Agile 30.66
Analytics 30.04
Big Data
Careers 30.15
Design 30.51
eCommerce 30.23
EdTech
Engineering
Innovation 30.03
Project Management 30.85

Industry Experience

Publications & Experience

3 Article/Blogs
Optimizing the E-Commerce Shopping Cart: A UI/UX Design Plan for seamless shopping
Hotragn Pettugani
September 30, 2024

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Tags: Design, eCommerce

Data Science: Riding the Wave of Innovation
Hotragn Pettugani
June 19, 2023
In today's data-driven world, the field of data science is constantly evolving, with new advancements and techniques emerging at a rapid pace. Staying up to date with the latest trends and developments in data science is crucial for professionals in the field. In this blog post, we will explore the recent updates and advancements in data science, highlighting their significance and impact on various industries. By embracing these updates, you can enhance your skills, stay relevant, and propel your career forward in this dynamic field.

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Tags: Analytics, Innovation

Career Guidance System for Predicting the Job Role Using Machine Learning
Medium
April 18, 2023
This system is the guidance path that predicts the job role for people looking to join jobs and doesn’t know which is right for them. This Article provides an overview of the system that has been developed using Python(Machine Learning).

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Tags: Careers

1 Instructor
Teaching Assistant
Northeastern University
January 01, 2025
Support development and implementation of design-focused curriculum, integrating both traditional sketching methods and digital visualization tools to enhance student understanding of architectural concepts.

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Tags: Agile, Project Management

1 Miscellaneous
Graduate Research Assistant
Northeastern University
September 01, 2024
Spearheaded the optimization of merger and acquisition data matching processes using advanced fuzzy matching algorithms and high-performance computing techniques. Engineered a sophisticated text normalization pipeline that significantly improved company name matching accuracy by implementing:

• Developed an enhanced fuzzy matching algorithm incorporating token-sort-ratio analysis and weighted scoring mechanisms for company hierarchies
• Designed and implemented comprehensive text normalization techniques, including intelligent handling of company suffixes, special characters, and corporate entity variations
• Created a scalable matching framework that processes large-scale M&A datasets while maintaining high accuracy in identifying parent-subsidiary relationships
• Achieved improved match quality by implementing multi-stage verification processes and hierarchical scoring systems

This re-engineered approach significantly reduced false positives in company matching and enhanced the ability to identify complex corporate relationships across global datasets.

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Tags: Big Data, Engineering

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