Adil Abdullahi
Summary
- Graduate of Bachelor of Applied Science and Engineering in Electrical/Computer Engineering program
- Experienced in C++, Python, PostgreSQL, R, PowerShell, AWS, ReactJS, Verilog, and Assembly
- Knowledgeable in using data analysis tools (t-SNE, Pheatmap, NMF, HCL etc.)
- Well versed in software development in a Linux environment, bash shell scripting, and command line
- Experienced in an Agile work environment that required excellent interpersonal and teamwork skills. As well as exceptional oral and written communication skills in English
- Well versed in using Git and SVN for version control in team coding
Overview
6
6
years of professional experience
Work History
Data Analyst Intern
Ceridian
09.2020 - 08.2021
- Created PowerShell scripts to automate running BJE background jobs
- Created SQL scripts to automate the changes in the BJE background jobs log
- Used Pester to make unit tests for the creation of namespaces and verticals
- Created FitNesse tests to automate manual UI tests on Chrome and Firefox
Bioinformatics Analyst
SickKids Hospital
02.2017 - 08.2017
- Developed software in the Linux environment (i.e wrote R scripts and Bash scripts) to streamline analyzation and organization of brain tumour methylation data (both 450k and EPIC)
- Created scripts to produce t-SNE, Pheatmap, NMF, and HCL plots
- The plots were used to help determine what family a new brain tumour belonged to
- Responsible for consolidating and curating brain tumour data sets
- Created a brain tumour bank containing the samples and their prediction types from the various tools
- Filtered out samples that were unreliable to create a robust data set
- The data set was later used to create a tool through the use of a machine learning algorithm (Random Forest) that predicts the brain tumour a patient has
- The resulting data, along with the histological diagnosis were then used to determine how a child should be treated
Bioinformatics Analyst
SickKids Hospital
05.2016 - 08.2016
- Visualised and compared pediatric brain tumour predictions between different classifiers and the histological diagnosis, then presented my findings at the annual SickKids summer symposium
- Wrote R scripts and Bash shell scripts to streamline data analyzation through MethPed (a DNA methylation classifier that predicts tumour subtypes)
- Used R Shiny to make an interactive data application to view our data in multiple forms
Bioinformatics Analyst
SickKids Hospital
07.2015 - 08.2015
- Company Overview: Bioinformatics Assistant at Huang Lab for Pediatric Brain Tumours
- Bioinformatics Assistant at Huang Lab for Pediatric Brain Tumours
Education
Bachelor of Applied Science and Engineering - Computer Engineering, Minor in Artificial Intelligence Engineering
University of Toronto
06.2022
Skills
- C, Python, PostgreSQL, R, Bash, PowerShell, FitNesse, AWS, ReactJS, Verilog, and Assembly
- PyTorch, OpenCV, NumPy
- Pheatmap, t-SNE, NMF and HCL
- Git and SVN for version control
- MATLAB, Microsoft Word, Microsoft Excel, and Microsoft PowerPoint
Projects
Mapping Software – C++
● Reads in database of all intersections and streets in a city (Toronto, New York, London, etc.)
● Draws the resulting map and lets the user interact with it (pan, zoom, search for location, etc.)
● Finds travel routes between two intersections and displays directions to user
● Finds the fastest path and order of deliveries for a courier to complete their daily deliveries
Database Design – PostgreSQL
● Designed a back-end database for a dive-booking app where qualified divers enter booking info
● The database design enforced the required constraints without allowing any redundancies or NULL/DEFAULT values
License Plate Recognition and Detection Application – Python
● Using deep learning, trained a CNN on a database of 500+ images of license plates
● Able to detect a license plate in an image and identify the different alphanumeric characters
● Image data processing was conducted using OpenCV
● Data preprocessing consists of edge detection, rectangle detection and image thresholding
● Resulted in successfully extracting 92% of images and predicting 94% of test data
Final Year Design Project – Python
● Optimized a Sentiment Classifier Model that was provided to us, using the BERT model
● Minimized inference time from 10s to 0.0063s, minimized training time from 120min to 8minand maximized accuracy from 85% to 88.4%
● Implemented Smart Checkpointing, Early Stopping and a Training Report Generator
● Model is able to detect sentiments from a given piece of text
Elevate Hackathon (Helping Hand) – AWS
● Worked in a team of 8 to create an Arduino prototype that could open doors through voice commands on Alexa, and authenticate users with facial recognition
● Utilized various AWS services (Alexa, Lambda, Rekognition, IoT), Twilio APIs, and Arduino
Timeline
Data Analyst Intern
Ceridian
09.2020 - 08.2021
Bioinformatics Analyst
SickKids Hospital
02.2017 - 08.2017
Bioinformatics Analyst
SickKids Hospital
05.2016 - 08.2016
Bioinformatics Analyst
SickKids Hospital
07.2015 - 08.2015
Bachelor of Applied Science and Engineering - Computer Engineering, Minor in Artificial Intelligence Engineering
University of Toronto
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