what i'm currently researching, and where it stands.
i'm not a researcher by training — this is me learning in public, digging into a real dataset from my own product, and being honest about how far along it actually is.
current research
01a longitudinal study of milk-procurement behaviour in a dairy cooperative, built on my own SaaS platform for dairy farmers.
in progress · exploratory analysisgoal: deeply understand farmer behaviour before modelling anything — then build a farmer-churn prediction system on top of it.
~2.2M daily records
6,693 farmers
8 societies
~1.6 years of data
kerala, india
- full data pipeline: firestore → clean, de-identified analysis panel.
- entity resolution — recovered true farmer identities (4,428 → 6,693) via phone-based ids where depot-shared membership numbers collided. a novel data-cleaning contribution, not something i expected going in.
- characterised data quality and distributions; established that SNF and rate are derived values, not measured ones.
- found a seasonal (monsoon) supply rhythm. the bigger realization: the real challenge is retention, not production.
- segmented farmers into 5 behavioural types; measured ~27% churn, detectable from first-90-day signals — low regularity, morning-only habit, low volume. notably, not milk quality.
papers i'm reading
09the reading list behind the modelling work above.
self-supervised & time-series representation learning
BERT (Devlin et al.)
✅ completed
PatchTST
⏳ queued
TS2Vec
⏳ queued
TST (Zerveas et al.)
⏳ queued
CoST
⏳ queued
MOMENT
⏳ queued
time-series foundation models
Chronos
⏳ queued
TimesFM
⏳ queued
Moirai
⏳ queued
last updated: august 8, 2026