Coffee Data Science
Advanced Espresso Now Available on Kickstarter
A new book on maximizing espresso efficiency
After the success of my first book, Engineering Better Espresso: Data Driven Coffee, I have been continuing with coffee experiments and have learned a great deal. The resulting two years have felt like I’ve been learning how to advance the knowledge of espresso beyond the current for my new book called Advanced Espresso: Elements of Coffee.
Coffee has held my attention for a few years now. What started as a small investigation to better understand some espresso equipment has snowballed into a broad array of deep-dives into everything coffee related. I have used data to answer more questions than I started with, but my rate of question generation has continued to increase relative to having answers.
Initially, I wanted to put together a book with a premise of a diving deep into the coffee bean. However, as I started putting together the material, I noticed a lot of gaps still existed. I’m not convinced those gaps will ever disappear, and the part of coffee that makes it so interesting to drink and study is its mystery.
My aim is to explain the mystery of coffee through the lens of four elements: earth, wind, water, and fire. All of these are tied together using data. I grouped the different components of espresso by these elemental categories in an attempt to group variables that are highly inter-connected.
The conclusion of this work is to encourage people to study coffee and the evolution of coffee extraction. We have found good methods for coffee extraction through a lot of trial and error by many people across many years. All of this is a great starting point for the next revolution in coffee, applied data.
The Book
Just like the first book, I have a draft ready. I will use an editor and graphic designer to turn my rough draft into a polished experienced. Then I’ll have the book printed and shipped. My aim is to use the same people as before that I used to produce Engineering Better Espresso as seen here.
This book will take from my prior learnings, articles, and videos. If you enjoyed them, you would also enjoy this book.
Here are some examples:
Understanding Grind RPM using Pattern Recognition
I used pattern recognition to understand the differences in particle shapes from the Molar Z and the Niche. I have also applied this technique to other grinders.
The Coffee Bean is Not Homogenous: Sifted Salami Espresso
To better understand the bean, I made an experiment to separately test how the different particle sizes extracted over time. While this is seemingly intuitive, finding out that the inside-fines (the softer part of the bean) extracted much faster than everything else.
Effective Top Paper Filter Designs
Through a series of tests, I found a top paper filter cut like a star reduces the effects of side channeling and is far superior than using a full circle paper on top of the puck.
Thermal Pre-Infusion for More Even Heat Distribution and Water Flow
In another series of experiments to separate water flow and heat flow, I found thermal pre-infusion was the key to unlock high extraction espresso in a shorter ratio and at a lower water temperature.
Prior Work
Engineering Better Espresso was well received by many.
The book was also stocked by Chromatic Coffee (my favorite coffee shop) and Sweet Maria’s (my source for most of my green coffee).
My Background
I come from a family of engineers. I grew up playing with Legos building cities and all sorts of toys. In school, I studied electrical engineering and mathematics, completing a bachelors with a double major and a masters in 4 years at Detroit Mercy. I then went to the University of Notre Dame where I earned a Ph.D. in computer science and engineering with a dissertation on 3D face scanning and recognition.
My first job was doing 3D face recognition research and development at Digital Signal Corporation followed by Apple. I have been at Apple for 9 years starting on the first generation Watch, doing wrist detection and background heart-rate. I then worked on Face ID in various aspects across multiple devices and years, Roomscan API, Apple Depth, and Vision Pro. I also developed a passion for accessibility and helped drive computer vision features for blind people into the phone such as People Detection, Outside Door Detection, and Point to Speak.
My day job is a mix of computer vision, machine learning, image processing, and data science. I have been through the trials and tribulations of designing, collecting, cleaning, and analyzing small and large datasets for multiple programs. In the past few years, I have used that knowledge to extract the most out of coffee into my espresso.
If you are interested in my new book, check is out here: Advanced Espresso: Elements of Coffee.
