Usha Kiranmayee

Results-driven quantitative geneticist and plant breeder with 15+ years of research experience spanning ICRISAT, academic institutions, and private seed industry. Deep expertise in genomic selection (GS), genomic estimated breeding values (GEBVs), GWAS, QTL mapping, and genetic gain optimization. Proficient in building and deploying machine learning and mixed linear model frameworks (rrBLUP, GBLUP, LASSO, Random Forest) for multi-omics data integration.

Published researcher with a strong track record of driving genetic gain through data-driven breeding strategies in sorghum, maize, rice, and cotton. Passionate about bridging AI/ML with quantitative genetics to accelerate crop improvement.

Data Analyst / Research Scientist at Conduent Business Solutions (2025-10 – Present)

• Apply advanced statistical and machine learning models to large-scale business datasets, generating actionable insights for operational decision-making.
• Develop automated data pipelines and dashboards (Python, SQL, Tableau) to support real-time reporting and KPI tracking across business units.
• Leverage expertise in linear mixed models and predictive analytics to optimize data-driven solutions in a fast-paced enterprise environment.

Senior Scientist – Genomics & Breeding at Nuziveedu Seeds Ltd. (2021-01 – 2022-10)

• Designed and deployed genomic prediction models (GBLUP, rrBLUP, LASSO) using 80K SNP arrays to estimate GEBVs for hybrid performance in maize, rice, and cotton, achieving significant improvement in selection accuracy for complex traits.
• Spearheaded genomic selection pipeline integration into commercial breeding, enabling accelerated varietal development cycles through data-driven early-generation selection.
• Optimized genetic gain by coupling genomic prediction with selection index theory, prioritizing high-value trait combinations across drought tolerance, disease resistance, and yield.
• Conducted GWAS to identify marker-trait associations for fiber quality, blast resistance, and bollworm tolerance, leveraging SNP array data for trait dissection.
• Led multi-environment trial (MET) analysis, applying mixed linear models (lme4, ASReml) to estimate BLUPs and GxE interactions across breeding stages.

Visiting Scientist – Genomic Breeding at ICRISAT (2019-09 – 2020-12)

• Developed native trait marker strategies for blast disease and heat tolerance in finger millet, integrating genomic and phenotypic data for selection efficiency.
• Coordinated multi-location trials for heat tolerance, implementing selection index approaches and statistical frameworks to identify elite lines with improved resilience.
• Spearheaded cross-crop data workflow unification and trait prioritization frameworks, laying the foundation for genomic prediction across breeding programs.

Visiting Scientist – PI, Gene Pyramiding (DST-SERB Postdoctoral Fellow) at ICRISAT (2017-04 – 2019-04)

• Served as Principal Investigator on a SERB-funded project on gene pyramiding for shoot fly resistance and drought tolerance in sorghum — first-ever PI grant awarded at ICRISAT.
• Applied KASP genotyping assays to validate marker-QTL associations and assess genotype-phenotype relationships, advancing pyramided lines into elite breeding pools.
• Integrated LeasyScan-based high-throughput phenotyping with genomic data to model drought response, demonstrating early competency in phenomics-genomics data fusion.
• Designed end-to-end experimental workflows including biometric analysis, team leadership, and scientific communication for multi-trait improvement programs.

Research Scholar – Ph.D. at ICRISAT / Osmania University (2011-04 – 2016-12)

• Conducted fine mapping of shoot fly resistance and stay-green QTLs on sorghum chromosome SBI-10 — Ph.D. dissertation — generating high-resolution marker maps used in downstream MAB programs.
• Applied GBS (Genotyping-by-Sequencing) for high-density SNP discovery: full NGS pipeline from raw FASTQ (FastQC, BWA, SAMtools, GATK) through variant calling and population structure analysis.
• Executed large-scale genotypic and phenotypic data integration, gaining deep expertise in biometric methods (BLUP, heritability, variance component estimation).
• Standardized high-throughput DNA/RNA extraction and multiplex PCR protocols, improving throughput and reproducibility for molecular breeding programs.

Research Technician – Molecular Breeding at ICRISAT (2008-01 – 2011-03)

• Supported molecular breeding programs for Striga resistance, shoot fly, grain mold, and post-flowering drought tolerance in sorghum.
• Designed field trial layouts and managed Breeding Management Software (BMS) data entry and analysis pipelines.
• Performed genotypic data extraction, transformation, and visualization using R and MS Excel for cross-program reporting.

Ph.D. in Genetics & Plant Breeding – Osmania University & ICRISAT (2011-04 – 2016-12)

M.Sc. in Agricultural Biotechnology – Andhra University (2007)

B.Sc. in Biotechnology, Zoology & Chemistry – P.R. Govt. College, Kakinada (2005)