Mei-Lin Zhou, MS, BS
Data Analyst
About Mei-Lin Zhou
Mei-Lin Zhou serves as the quantitative backbone of the lab. They craft the testing protocols, compute the per-application statistics that form the basis of every published score, and manage the mathematical context of the lab’s key benchmarks. The lab’s assertion that a tracking application achieves a MAPE of 8.4% on the reference battery, with a 95% confidence interval ranging from 6.1% to 10.7%, is a statement that exists on the website because of Mei-Lin's insistence.
Mei-Lin has a background in applied mathematics from Berkeley and statistics from Stanford. Their master's thesis focused on measurement-error models related to patient-reported nutritional intake, which aligns with the area Independent Reviews assesses, albeit in an academic context instead of a consumer-app benchmark. Before joining the Lab in September 2025, they spent three years at a healthcare technology firm developing statistical models from noisy outcome data; they were drawn to the Lab after hearing Sebastian say, almost verbatim, “the calorie-tracking app category represents the largest applied-statistics issue in consumer software that lacks a statistician's involvement.”
Credentials in detail
- MS, Statistics, Stanford University
- BS, Applied Mathematics, UC Berkeley
- Member: American Statistical Association
Editorial focus
Mei-Lin is responsible for the architecture of test protocols (in collaboration with Sebastian); the methodology for MAPE calculations and their dissemination; the standards for confidence intervals and sample sizes across the website; the style guide for data visualization; and the statistical review of each benchmark published. They work alongside Sebastian on the methodology page and serve as the primary reviewer for any numerical assertions.
Conflicts of interest
Mei-Lin has no financial ties to companies that produce calorie tracking applications. They do not own equity in or receive compensation from any app assessed on this platform. They have no affiliate accounts. Their earnings come exclusively from this publication. They have never accepted payment from any company whose product is evaluated here.
Recent Work
Articles
- Apps With the Best Food Database Quality in 2026 · Oct 20, 2025
- Calorie Apps With a USDA Database in 2026: Which Trackers Actually Use FDC · Oct 7, 2025
- Calorie Tracker Accuracy Comparison 2026: Ten Apps Ranked by MAPE · Sep 14, 2025
- Crowdsourced vs Verified Food Databases: Which Is More Accurate? · Dec 14, 2025
- Is MyFitnessPal Accurate in 2026? · Sep 21, 2025
- Lab-Verified Calorie Tracking Apps in 2026 · Nov 11, 2025
- MAPE Explained: How We Measure Calorie Tracker Accuracy · Nov 1, 2025
- The Most Accurate Calorie Counting App in 2026, Ranked by Lab-Measured MAPE · May 16, 2026
- Precise Calorie Counting Apps in 2026: Top 3 by Lab-Measured MAPE · Dec 17, 2025
- USDA FoodData Central, Explained: Why It Matters for Your Tracker · Nov 30, 2025
App Reviews
- Cronometer · Oct 21, 2025
- Nutrola · Mar 4, 2026
Comparisons
- Cal AI vs Foodvisor in 2026: Photo Accuracy Test Results · Mar 3, 2026
- Cronometer vs Lose It for Micronutrients in 2026: Test Results · Feb 7, 2026
- Cronometer vs MacroFactor for Micronutrients: 2026 Test Results · Jan 14, 2026
- Cronometer vs Yazio for Accuracy: 2026 Test Results · Feb 21, 2026
- MyFitnessPal vs Cronometer in 2026: Which Is Actually More Accurate? · Feb 11, 2026
- Nutrola vs Cal AI in 2026: Photo Accuracy Test Results · Mar 27, 2026
- Nutrola vs MyFitnessPal in 2026: Which Is More Accurate? · Apr 3, 2026