Shraddha Piparia, Ph.D.

Applied Scientist & Computational Biologist

Modeling disease heterogeneity with machine learning.

I build machine learning models across diverse biomedical data types including genomics, single-cell and multi-omic data, miRNA, proteomics, and clinical data to study disease risk, treatment response, and patient variability.

My work focuses on patient stratification, biomarker discovery, drug response modeling, and representation learning for high-dimensional biological data.

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Experience

Postdoctoral Scientist, University of California San Diego, USA (Nov 2021 – Present)

Computational genomics and pharmacogenomics research focused on disease heterogeneity, patient stratification, and treatment response modeling in asthma and immune-mediated disease.

Developed LD-aware VAE and transformer models for genotype representation learning, identifying genetic axes linked to asthma heterogeneity, patient stratification, and treatment response.
Built single-cell RNA-seq and RNA+ATAC integration workflows to characterize immune cell states and infer regulatory drivers of disease-associated transitions.
Identified neurocognitive subtype–specific Long COVID protein signatures using Olink NPX data and scalable UK Biobank pipelines across ~50K participants.
Modeled asthma heterogeneity and inhaled corticosteroid response using multi-modal genomic, proteomic, and clinical data.
Designed scalable, reproducible workflows in Python, R, PLINK, PySpark, and HPC environments for large-scale genomics analysis.

Application Developer, Oracle India Private Limited®, Telangana, India (Jun 2013 – Jul 2016)

Software engineer working on Oracle Cloud Enterprise applications (Oracle Project Portfolio Management).

Designed and implemented production features for Oracle Project Portfolio Management within Oracle Cloud enterprise applications.
Developed Build Verification Tests (BVTs) and automated testing workflows to improve release reliability and software quality.
Built an NLP and machine learning–based sentiment analysis system using Oracle Social Network data to improve search relevance and predict project risk and outcomes.
Developed backend services and data-processing workflows for enterprise-scale applications using Java, SQL, and Oracle technologies.

Education

Ph.D., Computer Science, University of North Texas, USA

Focus: Machine learning and probabilistic modeling for complex, structured, and event-driven data.