Technical Skills · Overview

Technical Skills

A guide to every technique, platform, model system, and protocol I've built or shipped: high-content imaging, proteomics and genomics, Python and lab automation, in-vivo neuroscience, primary cell culture, and the differentiation and assay protocols that ground the rest. Pick a category below.

Core skills

Microscopy, ‑omics, code & full stack

The four pages most reviewers want first: imaging modalities I run, ‑omics workflows I drive, the computational stack I built, and the consolidated skills page that pulls everything together.

01 · Imaging Microscopy & Imaging Confocal, super-resolution, high-content (Opera Phenix), live-cell time-lapse, transmission electron microscopy. Custom acquisition pipelines and ImageJ / Fiji / Imaris workflows. Confocal Opera Phenix TEM Live-cell 02 · ‑omics Proteomics & Genomics Mass spectrometry-based proteomics, multiplexed immunoassays, bulk and single-cell RNA-seq, downstream differential-expression and pathway-enrichment analysis. LC-MS Luminex / MSD scRNA-seq 03 · Code · Automation Coding & Automation Python pipelines, BRAVO / Tecan / Hamilton liquid handling, plate miniaturization, ML for morphology classification, AutoMorphoTrack open-source package. Python BRAVO 96/384 ML 04 · Full sheet Full Technical Skills The consolidated, single-page reference: every assay, platform, model system, statistical method, and software tool I'm fluent with — for ATS and reviewer scans. Assays Platforms Models Stats

In Vivo & Primary

Animal & primary-cell work

What I've done in living systems and freshly-isolated primary cultures — the wet-lab credibility that grounds the iPSC, imaging, and automation work upstream.

In vivo In Vivo Studies Photothrombotic stroke model in adult mouse, perfusion fixation, toluidine blue histology, and transmission electron microscopy of brain tissue. Mouse Stroke model TEM Primary Primary Neuronal Culture Rodent cortical and hippocampal primary neuron isolation, plating, and maintenance for imaging and physiology experiments. Cortical Hippocampal Primary Primary Cardiomyocyte Culture Isolation and culture of primary cardiomyocytes for contractility, calcium imaging, and electrophysiology readouts. Contractility Ca²⁺ imaging

Protocols

Step-by-step differentiation & assay protocols

The reproducible, peer-tested protocols I rely on for iPSC differentiation lineages, molecular assays, and imaging. Each page is annotated with reagents, timing, and QC checkpoints.

Differentiation Neuron / Cardiac Differentiation Dopaminergic, cortical, NGN2-induced, and cardiomyocyte iPSC differentiation timelines with reagents, density windows, and maturation checkpoints. DA NGN2 Cardiac Differentiation Endoderm & Ectodermal Protocols Endodermal and ectodermal lineage induction from iPSC, with media schedules, factor titrations, and lineage-marker QC. Endoderm Ectoderm Differentiation Pancreatic β-Cell Differentiation Multi-stage differentiation from iPSC to functional β-cells, with stage-specific markers and glucose-stimulated insulin-secretion QC. β-cell GSIS Assays Assay & Molecular Protocols Molecular and cell-based assay protocols: PCR, Western, ELISA, immunostaining, viability, killing assays, and proximity-ligation workflows. qPCR WB PLA Imaging Microscopy & Imaging Protocols Sample prep and acquisition protocols for confocal, live-cell time-lapse, high-content, super-resolution, and electron microscopy. Confocal HCS EM

Output

Publications

Peer-reviewed work tying these skills to biological results. Includes the AutoMorphoTrack methods paper (eLife review), the in-vivo neuroscience papers, and ongoing preprints.

Bibliography Publications & Preprints Full publication list with PMIDs, DOIs, and bioRxiv preprint links — filterable by topic. Peer-reviewed bioRxiv Google Scholar

How the skills stack

Model

iPSC differentiation + primary cell isolation provide the biological substrate.

Perturb

CRISPR screens, compound libraries, and biologics applied with BRAVO / Tecan / Hamilton automation.

Measure

Imaging, proteomics, and ‑omics generate phenotypic and molecular readouts.

Analyze

Python pipelines (AutoMorphoTrack, AMTcomparison) and statistical models in scikit-learn, pyDESeq2, SciPy.

Decide

Evidence convergence + agentic systems (Code & AI) prioritize next experiment.