Dr. Michael Snyder
Co-Founder, January AI

Why glucose is key to good health

At January, our mission is to increase the world’s “healthspan”—the number of years we remain in good health, free of chronic disease. Research continues to show that managing blood sugar is core to the cause, driven by its ability to regulate weight, cholesterol, inflammation, and so much more.

Now, for the first time, the January app harnesses powerful AI technology to help you better manage your glucose and build the habits that lead to a longer, healthier life.

January’s impact

Our cutting-edge research combines metabolic science, behavioral psychology, and world-class AI. After clinically proving that CGMs lead to weight loss, we successfully proved that AI can enable sustained behavioral change. Our peer-reviewed research validates what we’ve seen firsthand - that our users experience higher glucose control, weight loss, and more.

The Results

Users without diabetes
Users with Type 2 diabetes
16.2
%

Reduction in caloric intake

-4.1 lbs

Mean weight reduction (12-wks)

58
%

Improved Time in Range (70-140 mg/dL)

11.6
%

Increased relative protein intake

22.8
%

Increased relative fiber intake

4.2
%

Reduced carbohydrate intake

7.3
%

Reduction in caloric intake

-9.4 lbs

Mean weight reduction (12-wks)

63
%

Improved Time in Range (70-140 mg/dL)

*Improvement in estimated A1c=0.28%
10.6
%

Increased protein intake relative to total calorie

23.9
%

Increased fiber intake relative to total calorie

4.4
%

Reduced carbohydrate intake

Our Research

We’ve authored multiple whitepapers with rigorously designed clinical studies in metabolic health. This research has enabled our proprietary AI system to accurately predict glucose responses and has validated the impact of the January product.

0

Impact of digital health interventions on glycemic control and weight management

© January
2025
Arvind Veluvali, Ashkan Dehghani Zahedani, Amir Hosseinian, Nima Aghaeepour, Tracey McLaughlin, Mark Woodward, Alex DiTullio, Noosheen Hashemi & Michael P. Snyder
read
1

Digital health application integrating wearable data and behavioral patterns improves metabolic health

© January
2023
Ashkan Dehghani Zahedani, Arvind Veluvali, Tracey McLaughlin, Nima Aghaeepour, Amir Hosseinian, Saransh Agarwal, Jingyi Ruan, Shital Tripathi, Mark Woodward, Noosheen Hashemi & Michael Snyder
read
2

Heart Rate and CGM Feature Representation Diabetes Detection From Heart Rate: Learning Joint Features of Heart Rate and Continuous Glucose Monitors Yields Better Representations

© January
2021
Hootan Rashtian, Solmaz Shariat Torbaghan, Salar Rahili, Michael Snyder, and Nima Aghaeepour
read
3

Machine-Learned Prediction of Glucose Response for 1000 Subjects

© January
2016
Salar Rahili, Parin Dalal, Mehrdad Yazdani, Solmaz Shariat Torbaghan, and Michael Snyder
read
3

Virtual Blood Glucose Monitoring and Prediction Using Machine Learning

© January
2023
Ashkan Dehghani Zahedani, Arvind Veluvali, Saransh Agarwal Jiayu Zhou, Jingyi Ruan, Michael Snyder, Mark Woodward, Nima Aghaeepour. January AI. Stanford University
read
4

Improvement in Glucose Regulation Using a Digital Tracker and Continuous Glucose Monitoring in Healthy Adults and Those with Type 2 Diabetes

© January
2018
Ashkan Dehghani Zahedani, Solmaz Shariat Torbaghan, Salar Rahili, Kirill Karlin, Darrin Scilley, Riya Thakkar, Maziyar Saberi, Noosheen Hashemi, Dalia Perelman, Nima Aghaeepour, Tracey McLaughlin, and Michael P. Snyder
read
5

Digital Health: Tracking Physiomes and Activity Using Wearable Biosensors Reveals Useful Health-Related Information

© January
2017
Xiao Li , Jessilyn Dunn , Denis Salins , Gao Zhou, Wenyu Zhou, Sophia Miryam Schüssler-Fiorenza Rose, Dalia Perelman, Elizabeth Colbert, Ryan Runge, Shannon Rego, Ria Sonecha, Somalee Datta, Tracey McLaughlin, Michael P. Snyder
read
6

Glucotypes reveal new patterns of glucose dysregulation

© January
2018
Heather Hall , Dalia Perelman , Alessandra Breschi , Patricia Limcaoco, Ryan Kellogg, Tracey McLaughlin, Michael Snyder
read
6

Machine-Learned Prediction of Glucose Response

© January
2023
Salar Rahili, Parin Dalal, Mehrdad Yazdani, Solmaz Shariat Torbaghan, and Michael Snyder
read
7

A longitudinal big data approach for precision health

© January
2019
Sophia Miryam Schüssler-Fiorenza Rose, Kévin Contrepois, Kegan J. Moneghetti, Wenyu Zhou, Tejaswini Mishra, Samson Mataraso, Orit Dagan-Rosenfeld, Ariel B. Ganz, Jessilyn Dunn, Daniel Hornburg, Shannon Rego, Dalia Perelman, Sara Ahadi, M. Reza Sailani, Yanjiao Zhou, Shana R. Leopold, Jieming Chen, Melanie Ashland, Jeffrey W. Christle, Monika Avina, Patricia Limcaoco, Camilo Ruiz, Marilyn Tan, Atul J. Butte, George M. Weinstock, George M. Slavich, Erica Sodergren, Tracey L. McLaughlin, Francois Haddad & Michael P. Snyder
read
8

Personal aging markers and ageotypes revealed by deep longitudinal profiling

© January
2020
Sara Ahadi, Wenyu Zhou, Sophia Miryam Schüssler-Fiorenza Rose, M. Reza Sailani, Kévin Contrepois, Monika Avina, Melanie Ashland, Anne Brunet & Michael Snyder
read
9

Deep longitudinal multiomics profiling reveals two biological seasonal patterns in California

© January
2020
M. Reza Sailani, Ahmed A. Metwally, Wenyu Zhou, Sophia Miryam Schüssler-Fiorenza Rose, Sara Ahadi, Kevin Contrepois, Tejaswini Mishra, Martin Jinye Zhang, Łukasz Kidziński, Theodore J. Chu & Michael P. Snyder
read
10

Pre-symptomatic detection of COVID-19 from smartwatch data

© January
2020
Tejaswini Mishra, Meng Wang, Ahmed A. Metwally, Gireesh K. Bogu, Andrew W. Brooks, Amir Bahmani, Arash Alavi, Alessandra Celli, Emily Higgs, Orit Dagan-Rosenfeld, Bethany Fay, Susan Kirkpatrick, Ryan Kellogg, Michelle Gibson, Tao Wang, Erika M. Hunting, Petra Mamic, Ariel B. Ganz, Benjamin Rolnik, Xiao Li & Michael P. Snyder
read

Our Advisors

Meet the experts behind our groundbreaking research.

Scientific Advisory Board

Dean at the Tufts Friedman School of Nutrition Science and Policy, and Professor of Medicine at Tufts Medical School
Read more
Dariush Mozaffarian, MD, PhD
Scientific Advisor
Professor of Medicine, Stanford School of Medicine, Endocrinology, Gerontology, & Metabolism
Read more
Tracey McLaughlin, MD, MS
Scientific Advisor
Assistant Professor, Stanford School of Medicine. Artificial Intelligence, Machine Learning, and Multiomics Integration for Clinical Immunology
Read more
Nima Aghaeepour, PhD
Scientific Advisor
Associate Professor of Microbiology & Immunology, Stanford, NIH Director’s Pioneer Award Winner
Read more
Justin Sonnenburg, PhD
Scientific Advisor
Research Dietitian, Stanford University
Read more
Dalia Perelman
Scientific Advisor
Associate Professor University of Michigan Medical School Department of Microbiology & Immunology
Read more
Eric Martens, PhD
Scientific Advisor
Founder at Nautilus Biotechnology and Associate Professor at Stanford University
Read more
Parag Mallick, PhD
Scientific Advisor
Professor Emeritus, Friedman School of Nutrition Science and Policy at Tufts University and Chair, American Nutrition Association Board of Directors
Read more
Jeffrey Blumberg, PhD
Scientific Advisor

AI Advisory Board

Professor UC Berkeley, Founder/President/Chief Scientist covariant.ai (formerly Embodied Intelligence), Founder Gradescope
Read more
Pieter Abeel, PhD
AI Advisor
Associate Professor of Computer Science, Stanford University, Chief Scientist at Pinterest, and investigator at Chan Zuckerberg Biohub
Read more
Jure Leskovec, PhD
AI Advisor
Assistant Professor, Department of Electrical Engineering and Computer Sciences, UC Berkeley.
Read more
Sergey Levine, PhD
AI Advisor
Assistant Professor at Carnegie Mellon University
Read more
Zico Kolter, PhD
AI Advisor

Try January for free, today!

Download the January app today and see how you can manage your glucose, calories, and macros by simply taking a picture of your food.

Get started
DOWNLOAD FOR FREE