Pixel-art portrait of Ivana Sánchez Olivares

Ivana Sánchez Olivares

Bioinformatics · Machine Learning · Statistical Modelling · Reproducible Pipelines

About Me

I am a bioinformatician motivated to make a real impact on human health through data-driven insights. I build statistical models, machine learning methods, and reproducible computational pipelines to advance biomedical research and healthcare. I also enjoy science communication, interviewing epigenetics researchers for the CEEHRC podcast and helping organize its seminar series.

  • Python
  • R
  • SQL
  • PySpark
  • Bash
  • Machine Learning
  • Deep Learning
  • Single-Cell Analysis
  • Genomics
  • Epigenetics
  • Transcriptomics
  • Snakemake
  • Nextflow
  • Docker
  • HPC

Publications

Career

  1. WorkJul 2026 – Present

    AI Trainer in Bioinformatics, Data Science and Healthcare

    Data Annotation · Freelance · Vancouver

    Design bioinformatics and ML tasks with gold-standard solutions, and evaluate LLM outputs against them to generate feedback for reinforcement learning.

  2. VolunteeringJun 2025 – Present

    Podcast Team Member & Seminars Committee Representative

    Canadian Epigenetics, Environment & Health Research Consortium (CEEHRC) · Vancouver

    Interview Canadian epigenetics researchers for the CEEHRC podcast and help organize the seminar series.

  3. WorkSep 2024 – Sep 2026

    Research Assistant

    Birol Lab · Genome Sciences Centre & BC Cancer Research Institute · Vancouver

    • Simulated single-cell methylation profiles with a generalized linear mixed model in Snakemake (98% CpG recovery, MAE 0.031).
    • Contributed to AIEdit, a deep-learning genome assembly polisher (human assembly QV 28.7 → 32.9).
  4. EducationSep 2024 – Aug 2026

    M.Sc. in Bioinformatics

    The University of British Columbia · Vancouver

    Supervised by Dr. Inanc Birol

    CONAHCYT Merit-Based Scholarship · GPA 96.2/100

  5. WorkMay 2023 – Jul 2024

    Data Scientist Associate

    BBVA · Mexico City

    Built a product engagement metric that increased product usage by 30%, and a classification model for credit eligibility.

  6. WorkOct 2022 – May 2023

    Data Scientist Analyst

    BBVA · Mexico City

    Ensembled time-series models (e.g., ARIMA, ETS-LSTM) to forecast 90-day client income, expenses, and balances, effectively predicting 80% of clients’ amounts.

  7. WorkFeb 2022 – Aug 2022

    Intern in Mathematical Modeling and Data Validation (part-time)

    Intelligence Trade, S.L. (Moondi Export) · Mexico City

    Identified macroeconomic and demographic factors to rank the top 20 target countries for Spanish wine exports.

  8. EducationAug 2018 – Jun 2022

    B.Sc. in Applied Mathematics

    Universidad Nacional Autónoma de México (UNAM) · Mexico City

    Gabino Barreda Medal (highest GPA in cohort) · GPA 10.00/10.00

Projects

Simulation of Haplotype-Resolved Single-Cell Methylation Profiles

Can we simulate single cells with known methylation on both haplotypes and both strands of a diploid genome, as a benchmark for alignment and methylation-calling tools, and measure how much of that signal survives bisulfite sequencing?

Methods
  • Statistical modelling (overdispersed GLMM)
  • In silico bisulfite conversion & read simulation
  • Clustering
Tools
  • Python
  • Bash
  • Snakemake
  • Conda
  • Bismark
  • ART
  • SAMtools
  • bedtools

UBC · M.Sc. Bioinformatics Thesis · Vancouver, Canada · 2024–2026

Normative Brain Development and Aging

Can a deep learning model chart the normal range of brain structure and connectivity across age and sex in MRI data (ABIDE), so that individuals who deviate from the norm can be identified?

Methods
  • Quantile regression neural network (MLP)
  • Pinball loss with non-crossing quantiles
Tools
  • Python
  • PyTorch

Personal project · 2026

Benchmarking LLM-Generated Bioinformatics Workflows

Do the bioinformatics workflows that LLMs and AI agents produce use appropriate, current, and reproducible tools?

Methods
  • LLM agents (Biomni, STELLA, Claude, Gemini)
  • Rubric-based evaluation
  • Reproducibility testing
Tools
  • R
  • Python

Bioconductor BioNA Hackathon · Seattle, USA · Aug 2026

Medulloblastoma Groups 3 and 4

How do Group 3 and Group 4 medulloblastoma tumours differ at the single-cell level, and does their immune cell composition suggest immunotherapy opportunities?

Methods
  • K-means, k-medoids & hierarchical clustering
  • Differential expression
  • Pathway enrichment analysis
  • Automated cell-type annotation
Tools
  • R
  • Seurat

UBC · Vancouver, Canada · 2025

Benchmarking Single-Cell Classifiers

How accurately can machine learning and deep learning models annotate cell types in mouse brain scRNA-seq data (Tabula Muris)?

Methods
  • Support Vector Machine
  • Logistic Regression (CellTypist)
  • Variational Autoencoder (scANVI)
  • Autoencoder + cell similarity search (Cell BLAST)
Tools
  • Python
  • Scanpy
  • scikit-learn
  • PyTorch

UBC · Vancouver, Canada · 2025

Recurrence-Free Survival in Bladder Cancer

Can a survival model improve the clinical stratification of recurrence-free survival in low-grade, stage Ta bladder cancer patients?

Methods
  • LASSO-penalized Cox regression
  • Kaplan–Meier analysis
Tools
  • R
  • glmnet
  • survival

UBC · Vancouver, Canada · 2025

Cold Stress and the Pufferfish Kidney

How does low-temperature stress change the kidney transcriptome of Takifugu rubripes (Japanese pufferfish)?

Methods
  • Differential expression
  • Pathway enrichment analysis
  • PCA
Tools
  • R
  • STAR aligner
  • DESeq2
  • topGO

UBC · Vancouver, Canada · 2024

Automated SNV Calling Pipeline

How can single nucleotide variant calling from raw whole-genome sequencing reads be made reproducible for population-scale genomic analysis?

Methods
  • Short-read alignment
  • PCR duplicate removal
  • Variant calling
Tools
  • Nextflow
  • Docker
  • BWA
  • SAMtools
  • BCFtools

UBC · Vancouver, Canada · 2024

Paxlovid Cost-Effectiveness Model

Is expanding Paxlovid use beyond guideline criteria cost-effective for reducing severe COVID-19 disease?

Methods
  • Markov model
  • Cox proportional hazards
  • Cohort simulation
  • Sensitivity analysis
Tools
  • R

UNAM · Mexico City, Mexico · 2022–2024