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BIOINFORMATICS SYSTEMS X DATA ENGINEERING

Kaizen Nathani

Bioinformatics Scientist | Data Engineer | Clinical Informatics

I build automated bioinformatics pipelines and AI-ready data systems for translational research and clinical decision-making.

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What I build

Systems that sit where clinical workflows, biomedical data, and production engineering meet.

Clinical Bioinformatics Systems

CLIA/CAP-compliant clinical bioinformatics systems for somatic variant analysis, NGS quality control, and automated reporting.

NGSCLIA/CAPVariants Analysis

AI Agents for Healthcare Data

LLM-assisted extraction and review systems that turn clinical text into structured, auditable outputs.

LLMsFHIR

Data Engineering for Precision Oncology

Cloud/HPC-aware pipelines that make biomedical data reliable, traceable, and analysis-ready.

AWSDockerNextflowCI/CD

Featured work

Selected clinical AI, NGS QC, and translational cancer informatics projects.

View all projects
EHR Agent
LLM-powered clinical notes to structured outputs.
AI / LLM

Problem: Clinical notes contain high-value details that are difficult to reuse for research databases or review workflows.

Built: Built an MVP for extracting structured clinical information from notes or mock records with JSON validation and human-review-friendly output.

Impact: Demonstrates a practical clinical informatics path from narrative text to auditable structured data.

Clinical textREDCapFHIRLLM
GitHub
Ion Torrent Amplicon Capture Sequencing QC Dashboard
Run-level and sample-level sequencing QC for clinical NGS.
QC / Visualization

Problem: Homopolymer-region artifacts and flow-rate or fluidics issues can complicate variant review.

Built: Designed a dashboard framework for automated amplicon coverage monitoring, sequencing artifacts tracking, and clinical sequencing QC investigation.

Impact: Supports faster investigation of false-positive results and run-level sequencing behavior by pathologists on a no-code interface.

GenexuscoveragehomopolymersQC