Ketaki Ghatole

Ketaki
Ghatole

Building at the intersection of AI & Biology

I have a background in computational biology from Carnegie Mellon and experience across the biotech industry and research labs. My work spans bioinformatics, AI, and product development. I’ve built tools that help scientific teams streamline and automate complex workflows. I also write about advances in AI for biotech, with a focus on practical applications for scientific teams.

Right now, I’m building a platform to help biotech teams preserve context and reasoning across fragmented information, and make better decisions using the knowledge they already have

I'm talking to biotech teams who struggle to make sense of their own data over time. If that resonates, I'd love to connect

Connect on LinkedIn Blog →
Ketaki Ghatole
01 Thesis
Building a reasoning layer for biotech data
Biotech teams lose the why behind their decisions, data gets recorded but the reasoning doesn't.
When a project pivots, or a meeting ends without good notes, that context disappears and the next person starts from scratch.
A knowledge layer can capture institutional reasoning and bring it back up when teams need it, so people can make better decisions using context they already have.
I'm currently prototyping and talking to teams across biotech to understand this problem better.
02 Work
2024–2025
Bioinformatics Product Manager
Creyon Bio
Launched an AI-driven target discovery tool that cut scientific evaluation by ~3h per target. Delivered end-to-end assay data workflows that reduced analysis time 50%+. Drove company-wide responsible GenAI adoption.
2023–2024
Bioinformatics Data Analyst
Creyon Bio
Improved a LightGBM treatment-tolerability model (PR-AUC +4%). Deployed high-throughput NGS pipelines via Snakemake. Built real-time dashboards that accelerated experimental feedback and analysis turnaround.
2023
Computational Biologist
Jefferson Health
Analyzed differential gene expression to uncover biological pathways. Created Python visualizations to communicate findings clearly to wet-lab collaborators.
2022
Computational Science Intern
Moderna
Built an eCLIP data pipeline including preprocessing, peak calling, and motif extraction to support RNA-binding protein research.
2020–2021
Junior Analyst
Axiom Healthcare Strategies
Competitive intelligence in oncology, clinical trial analysis, conference proceedings, and strategic forecasting.
03 Education
2021–2023
M.S. Computational Biology
Carnegie Mellon University, Pittsburgh, PA
James R Swartz Entrepreneurial Fellow 2022
2016–2020
B.E. Biotechnology
M.S. Ramaiah Institute of Technology, Bengaluru, India
Co-founder, Numera Math & Logic Club
04 Projects
GitHub →
AI · Knowledge Graph

Bioweave

Interactive knowledge graph connecting genes, proteins, and publications, making fragmented biological context searchable and visible in one place.

View on GitHub →
Product · Full-stack

Clinical Trial Finder

Full-stack lung cancer trial matching app that makes trial discovery easier to search and understand around patient-specific needs.

View on GitHub →
Data Infrastructure

Bio Data Organizer

Schema-driven tool that automatically structures scattered experimental data into clean, analysis-ready formats.

View on GitHub →
Machine Learning

Multi-omic Lung Cancer

Lung cancer subtype classification using TCGA data. A PyTorch autoencoder whose multi-omic ensemble outperformed mono-omic baselines.

View on GitHub →
Machine Learning

Malaria Detector

ResNet50 transfer-learning classifier distinguishing infected from healthy blood-smear cells to address inconsistent manual screening.

View on GitHub →
Bioinformatics

Variant Calling Pipeline

Reproducible workflow for calling SNPs and indels from raw paired-end reads with filtered variant output for IGV visualization.

View on GitHub →
Bioinformatics

RBP Peak Finder

CNN identifying where RNA-binding proteins interact with viral RNA using eCLIP data, distinguishing binding peaks from background.

View on GitHub →
06 Writing
Read all →
Biology × AI
Practical workflows and tools lab teams can actually use
→
Thinking in Products
Building in technical and scientific markets
→
Back to Basics
Concepts that are easy to name but hard to explain well
→
07 Outside work

Currently learning latte art, training for a 10K, working toward my first pull-up, and experimenting with design on the side.

First rosetta
First rosetta
Hiking in Zion
Hiking in Zion
Sunset yoga in San Diego
Sunset yoga in San Diego
Let's talk

If you're building something or
working in Biotech or AI

I'd love to connect.

Email me → Connect on LinkedIn