Business Analytics with Information Technology & Finance major at Rutgers, exploring the intersection of fashion, data, consumer behavior, and strategy.
Finding stories where others see information
How aesthetics predict markets. Trend signals as financial data.
Forecasting, data modeling, and the stories numbers tell.
Equity markets, investor behavior, capital allocation and risk.
Why people buy, what they signal, how culture drives spending.
Business models, competitive positioning, and market thinking.
How platforms, algorithms, and online aesthetics shape the world.
Artificial intelligence in fashion, finance, and beyond.
The visual world — moodboards, fashion, travel, design, beauty.
This project investigates the relationship between fashion trend signals and their downstream impact on consumer demand and financial markets. The research combines Google Trends, publicly available stock market data, and time series modeling to examine how digital attention evolves before measurable business outcomes occur. Using Python for data collection, preprocessing, visualization, and predictive analysis, the study applies statistical and machine learning techniques to identify patterns, estimate trend lag, and evaluate whether early consumer interest can provide meaningful insights for forecasting, marketing strategy, and business decision making.
Finding signals where others see noise.
A monthly visual collection of fashion, travel, architecture, texture, and the images
Summer 2026
All the things I'm thinking about and writing through <3.
Questions, topic ideas, polls, comments, this is the part that talks back.
Contact me: Gmail - shahchelsy@gmail.com, LinkedIn - https://www.linkedin.com/in/chelsy-shah/, GitHub - https://github.com/shahchelsy
Hi, I'm Chelsy. Welcome to my little corner of the internet, where fashion, business, and curiosity come together to tell stories through data.
"Fashion changes, but style endures." — Coco Chanel
Fashion has always been more than clothing to me.
It has always been a language. Some people see an outfit. I see confidence, identity, culture, timing, and the choices people make before they ever say a word. Fashion has this quiet ability to change how someone carries themselves. It is never about fitting into a trend or becoming someone else. It is about feeling comfortable enough to become more of yourself. When you feel confident in what you wear, you move differently, speak differently, and often believe in yourself a little more.
As I became more interested in fashion, I also became fascinated by the business behind it. I found myself asking questions that went far beyond collections and runway shows. Why do some trends disappear within weeks while others influence an entire generation? Why does one campaign become part of popular culture while another is forgotten? What makes people suddenly want the same product at the same time?
Those questions slowly introduced me to another world. A world of consumer behavior, marketing, forecasting, finance, and data.
Behind every successful fashion house are thousands of decisions supported by numbers. There are analysts forecasting demand months in advance, marketers understanding exactly who they are speaking to, buyers predicting what customers will love next, and strategists deciding when a collection should launch and where it should be seen. Great fashion is creative, but great fashion businesses are incredibly analytical.
Karl Lagerfeld once said, "Fashion is a language that creates itself in clothes to interpret reality." I like to think this language can also be predicted through data and modified in a better way.
Every search trend, every social media conversation, every shift in consumer preference tells a story. Numbers are not just spreadsheets to me. They are evidence of changing behavior. They reveal how culture evolves, how markets react, and how brands can understand people before people fully understand themselves.
That curiosity is what led me to study Business Analytics with IT and Finance alongside my interest in fashion. I enjoy finding patterns, asking questions, and connecting creativity with commercial strategy. The intersection of these worlds is where I feel most inspired.
This website is my digital notebook, a place where I document observations, research ideas, opinions, visual inspiration, and projects that explore fashion through both a creative and analytical lens. Some pages may begin with a runway show, while others begin with a dataset. Both are equally exciting to me because they tell different parts of the same story.
As Miuccia Prada once said, "What you wear is how you present yourself to the world." I would add that understanding why people choose to present themselves that way is just as fascinating.
Beyond my coursework at Rutgers University, I enjoy exploring the business of fashion through research, data, and observation. My interests lie at the intersection of consumer behavior, trend forecasting, marketing strategy, and finance, where creativity is supported by evidence and every decision is backed by insight.
This portfolio is a reflection of that journey. It brings together the projects I've built, the research I'm pursuing, and the ideas that continue to shape my perspective. Whether I'm analyzing emerging trends, studying financial markets, or exploring how consumer behavior influences brands, I'm always looking for ways to connect creativity with commercial strategy.
My goal is to build a career where I can contribute to the future of the fashion industry by helping brands make smarter, more informed decisions through data, innovation, and strategic thinking.
Every project starts with a question. This is where I explore it, test it, and document what I learn along the way.
How AI-detected signals predict brand performance and investor response
This project investigates the relationship between fashion trend signals and their downstream impact on consumer demand and financial markets. The research combines Google Trends, publicly available stock market data, and time series modeling to examine how digital attention evolves before measurable business outcomes occur. Using Python for data collection, preprocessing, visualization, and predictive analysis, the study applies statistical and machine learning techniques to identify patterns, estimate trend lag, and evaluate whether early consumer interest can provide meaningful insights for forecasting, marketing strategy, and business decision making.
Understanding how regulation, investor psychology, and market behavior influence financial decision making.
This research examined how retail investors make financial decisions beyond traditional market fundamentals. Through survey analysis, regulatory research, and the study of SEBI's role in market development, I explored how investor psychology, financial literacy, and trust influence participation in India's capital markets. The project reinforced the importance of understanding human behavior alongside quantitative market data when evaluating investment decisions.
All the things I'm thinking about and writing through <3.
The places that shaped how I solve problems, work with people, and think about business.
Fashion · Travel · Moodboards · Architecture · Texture · Lifestyle · Inspiration
Questions, topic suggestions, polls, reader comments — this is the part that's built for conversation.
Contact me: Gmail - shahchelsy@gmail.com, LinkedIn - https://www.linkedin.com/in/chelsy-shah/, GitHub - https://github.com/shahchelsy