From Egypt to an IEEE acceptance on climate-resilient rice

Soil salinization is one of the biggest threats to rice, the staple food for more than half the world. Tarek built OryzaGen, a reproducible pipeline that combines high-throughput transcriptomic profiling, public 3K Rice genomic phenotypes, published GWAS loci and population-blocked machine learning classifiers. The pipeline isolated 28 high-confidence candidate genes within 100 kb of established salinity GWAS peaks, including LOC4329464, LOC4329812 and LOC4352160, giving breeders a transparent shortlist for marker-assisted selection and targeted crop engineering in climate-vulnerable regions.

FIELDGenomics & Machine Learning

RESULTFirst-author paper accepted at an IEEE conference

VENUEIEEE, 2026

Tarek Osama, YRI FellowIEEE

BEFORE THE FELLOWSHIP

A student at Sharkya STEM School in Egypt with big ideas in biology but no way to turn them into real research.

AFTER

First author of a multi-omics machine learning paper on rice salinity tolerance, accepted at an IEEE conference.

“YRI taught me how to think like a scientist, blending biology with AI, and pushed me to unlock my full potential.”

TAREK OSAMA

THE LEDGER

01First-author paper accepted at an IEEE conference

02Built OryzaGen, an integrative transcriptomic, genomic and machine learning pipeline for rice salinity tolerance

03Identified 28 high-confidence candidate genes within 100 kb of published salinity GWAS peaks

04Benchmarked CatBoost, LightGBM, XGBoost, Random Forest and logistic regression under population-blocked cross-validation to rule out ancestry leakage

05Screened 57,381 expression probes and matched 478 of 479 public 3K Rice salinity phenotypes

NEXT CASE STUDYSadaf Shireen, Admitted to Brown, Johns Hopkins and UT Austin

Every case study starts with one application.

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