Eric Arezza
About Career Education Skills Projects Interests

About

Me at the Eiffel Tower

I extract information and reveal insights from all kinds of data! My main interests include data science, statistical analysis, machine learning, visualizations, and taking advantage of computational tools and techniques.

Currently residing in Belfast, Northern Ireland (UK), I work remotely as a Bioinformatics Analyst performing bioinformatics data processing and analysis at the Ottawa Hospital Research Institute. More specifically, I am supporting the Dilworth Lab and Megeney Lab in studying the epigenetics of stem cells.

Professional Career

cells fluorescent microscopy

Bioinformatics Analyst

OHRI logo

March 2022 - Present
The Ottawa Hospital Research Institute, Ottawa, ON

Performing collection, processing, and analysis of -omics data for stem cell epigenetics research. Handling experiment -omics data from assay techniques including CUT&Tag, ChIP-seq, ATAC-seq, RNA-seq, Hi-C/Micro-C, and more in bulk & single-cell samples.

fiber optics

Teaching & Research Assistant

January 2020 - May 2022
Carleton University, Ottawa, ON

Examined and developed machine learning methods for predicting protein-protein interactions with the cuBIC lab, supervised by Dr. James Green.
Proctored student learning workshops and evaluated assignments.

Me working with lasers on the lab bench

Research Student

Gastops Ltd.

September 2017 - November 2018
Gastops Ltd, Gloucester, ON

Investigated hardware improvements for product (ChipCHECK) that performs diagnostics of damage and wear in machinery using LIBS (Laser-Induced Breakdown Spectroscopy) technology.
Experimented with various LIBS parameters/configurations and conducted high-power laser experiments for data collection.

fiber optics

Optical Network Tester

Nokia

January 2017 - August 2017
Nokia, Kanata, ON

Automated feature testing of optical network devices (1830 PSD) and compatibility using Python and API in compliance with device specifications.

Academic Education

Me at bachelor graduation

Master of Applied Science in Biomedical Engineering
with Specialization in Data Science

January 2020 - May 2022
Carleton University, Ottawa, ON

Graduated - see my thesis here!

Me at bachelor graduation

Bachelor of Information Technology
with Advanced Diploma in Photonics and Laser Technology

September 2014 - May 2019
Carleton University & Algonquin College, Ottawa, ON

Graduated with High Distinction, COOP, and Awarded the University Medal in Information Technology

Skill Set & Experience

computer

Computers & Software

Check out my GitHub!

Programming (Windows & Linux OS):

  • Python
  • R
  • Bash/shell
  • SQL
  • Experience with others as well as HTML and CSS
  • Scripting for exploration, automation, GUIs, data management, code reuse, etc...

Bioinformatics Tools:

  • FASTQC & MultiQC for reads and alignment stats and quality checking
  • Samtools & Picard for filtering and formatting
  • Cutadapt & trimmomatic for trimming reads
  • Bowtie2 & Hisat2, BWA for assembly alignment
  • HOMER & MEME-SUITE for motif discovery
  • MACS & SEACR for peak calling
  • DiffBind, DESeq2 & edgeR & limma/voom for differential analyses
  • Scanpy & Seurat for single-cell analyses
  • Juicebox & Juicertools for Hi-C data
  • UCSC Genome Browser & IGV for visualizing -omics files

Data Science and ML Tools:

  • Pandas, NumPy, dplyr, tidyr for data wrangling and manipulation
  • Matplotlib, Seaborn, ggplot2, Tableau, PowerBI for EDA and visualizations
  • Scikit-learn, Tensorflow/Keras for ML model selection, testing, evaluation, and deployment

Other Tools:

  • Git/GitHub for software development version control
  • Slurm for HPC environment, parallelization, and resource management
  • Conda/Mamba and virtualenv for package management
  • Nextflow for workflow management
  • Apptainer/Singularity and Docker for containerization
  • Jupyter Notebooks for interactive coding, documentation, and collaboration
  • Visual Studio Code, Spyder, RStudio, and other IDEs for software development environments
computer

Research

Literacy:

  • Identifying and citing recent and relevant sources of literature
  • Documenting methods, recording data, and writing reports with high attention to detail
  • Presentating findings with PowerPoint using simple and digestible visuals
  • Organizing and managing data and files using file structures for easy recall

Experimental Design

  • Using hypothesis testing and statistical significance evaluations to determine likelihood of differences
  • Determining sources of error and considering confounding variables
  • Weighing selection of type I or type II error trade-off

Publication Contributions:

orcid logo

computer

Machine Learning & Data Analysis

  • Data collection, inspection, and cleaning
  • Generating visualizations
  • Feature design and engineering
  • Model creation and parameter testing
  • Evaluation of prediciton performance
  • Communicating results and delivering actionable insights
computer

Bioinformatics

Bulk High-Throughput (Next-Generation) Sequencing:

  • Quality control
  • Trimming
  • Genome alignment
  • Normalizing coverage
  • Peak calling
  • Generating count matrices
  • Differential analysis of binding sites and gene expression
  • Annotating regions (gene mapping, GO, KEGG)

Single-Cell Analysis:

  • QC and filtering
  • UMAP & tSNE plots
  • Cell clustering
  • Differential gene expression analysis
  • Identifying & annotating clusters
  • Pseudotime & trajectory analysis

Personal Projects

House rental

Canadian Rentals Analysis

Purpose:

Analyze real ad listings in Canadian cities and obtain market insights.

Methods:

Kijiji is chosen as a popular website for ad postings.
Python is used for data scraping and wrangling:

  • Collection/extraction with Requests and parsed with Beautiful Soup
  • Processing/transformation/cleaning with Pandas and NumPy
  • Visualization presented with Power BI...to be polished and published...

Preliminary Results:

Raw example of initial timepoint below...data collection is ongoing and dashboard reports to be developed...(DEPRECATED)

SecurityCamera

Computer Vision Security Camera

Purpose:

Monitor and report room intrusions when I'm absent.

Methods:

Raspberry Pi with external webcam for lightweight, standalone, and continuous operation.
Python is used for machine learning models implementation:

  • Object detection with OpenCV and TensorFlow Lite
  • Model used is the EfficientDet-Lite0 pre-trained on the COCO dataset

Result:

Successfully detects when a person is in the room through real-time video and takes time-stamped snapshots of intrusion events.
Example from early testing:

RPiPersonDetected

Interests

Candidly me

Learning new skills such as:

  • Making this webpage
  • 3D modeling and printing
  • DIY fixes
  • Playing piano

I also enjoy:

  • Playing guitar
  • Exercising and working out
  • Long bike rides
  • Trivia
  • Drawing, painting, and crafts
  • Baking and - of course - eating new recipes