Hi, my name is Abbas Meghani
I am a Software Engineer with experience in data-intensive backends and Machine Learning research.

About Me


Or jump to any of the following sections

About me

Profile Image

I am a Software Engineer with experience working in an intensive startup environment alongside an AGILE team. I have almost three years of experience in object-oriented programming, particularly in the development of high-volume, low-latency products. My professional track record highlights my proficiency in tackling intricate data-intensive applications, with a keen focus on optimizing efficiency.

Outside of my professional commitments, I enjoy going on long hikes in nature, reading books and working on research projects.

View Resume

Education

MSc: Data Science

at HEC Montréal, University of Montréal

Website

GPA: 3.6/ 4.3

Notable Achievements: Received a scholarship for Fin-ML Research and was hired three times for distinct programming projects, two of which were used to facilitate course capstone projects.

Coursework: Decision Analysis, Machine Learning, Machine Learning II: Deep Learning, Adv. Statistics, Forecasting Methods, Algorithms, Complex Networks Analysis, Optimization, Statistical Modelling

BEng: Computer Engineering

at Rizvi College Of Engineering (RCOE), University of Mumbai

Website

GPA: 8.4/ 10

Notable Achievement: One of only two teams in my cohort to receive research funding.

Coursework: Data Structures, Object Oriented Programming, Data Management Systems, Distributed Systems, Operating Systems, Adv. Applied Mathematics I/ II/ III/ IV, Digital Logic Design, Microprocessor, Circuits, Web Technologies


Experience

Feb 2022 - Present

Data Scientist: Backend

at Shift-Technology, a Fintech Unicorn Startup

Tech Stack: C#, T-SQL, Python
Monitoring: Grafana
CI/ CD: TeamCity, Octopus

Note: This position did not encompass analytics, which is typically a core aspect of Data Science; instead, it focused solely on backend tasks.

Website

  • Used design patterns in C# to make a generic and reusable data transformation tool for the Fraud Detection product, resulting in better scalability and enhancing efficiency for more than 10 clients.

  • Enhanced company-wide impact by improving data transformation efficiency by 5% through the utilization of better data structures and adjustments to mapping algorithms.

  • Coded hash-based deduplication filters and processes to help efficiently ingest and process tables with up to 9 billion highly duplicated rows of data within server memory constraints.

June 2021 - Feb 2022

Software Engineer: Backend

at MKSoftware, a company that makes ERP solutions
Main Product: DocuFire

Tech Stack: C#, React.js, Typescript, T-SQL
CI/ CD: Windows Installer, Installshield

Website

  • Achieved a 15% increase in efficiency by implementing asynchronous parallel processing of pages in the pdf document generation module of the core ERP Solution allowing for processing of documents at scale.

  • Led the transformation of a legacy project's data access layer into a REST API, preserving all existing methods. Strengthened the system with improved unit tests, ensuring enhanced functionality.

  • Designed and developed the MVC backend for an interactive ASP.Net Core Web Application, seamlessly integrating it with the REST API mentioned above.

May 2021 - Oct 2023 (Part Time)

Research Assistant

at HEC Montréal, University of Montréal; developing web application to facilitate course capstone projects

Tech Stack: C#, MySQL, Python

Website

  • Created and hosted a scalable C#/ASP.Net Core website with MySQL for the 'Sports Analytics' course. The system fulfilled functional requirements such as user registration, team and game sign-ups, and included an on-server Machine Learning simulation.

  • Developed Python visualizations for data from a sports simulation ML model, subsequently adapting them for use on the server of the website.

Aug 2021 - Oct 2021 (Part Time)

Research Consultant

at Sentometrics, writing a Machine Learning research paper

Tech Stack: R, Python

Website Publication

  • Used topic modeling (R) to analyze and gain insights about financial research over time.

  • Scraped data, preprocessed text, and annotated the text corpus.

  • Created and transformed several covariates for 33 Financial Journals.

  • Implemented, optimized, and compared multiple Structural Topic Models for relevant insights.

Sept 2020 - Apr 2021 (Part Time)

Research Assistant

at ERPSim Lab, HEC Montréal

Tech Stack: Python, SAS

Website

  • Documenting and verifying validity (Python) of simulated data for use in Cortex - a platform for learning and practicing data science concepts.

  • Programming in SAS and writing guides for students and teachers about using SAS-EM effectively to analyze the simulated datasets.


Projects

Apr 2021 (Python)

Complex Networks

  • Created a complex road network of bike sharing service usage by overlaying it with a road network of the city.

  • Converted data into daily and weekly demand time series and incorporated conversion of time series data into complex networks using distance metrics and also a visibility graph.

  • Analyzed networks using global/local network descriptors, & community detection algorithms.

Report

Oct 2020 (Python)

Convex Hull Algorithms

  • The project features a GUI for visualizing convex hull algorithms using Python & Tkinter.

  • Users can explore algorithms like Brute Force, Jarvis' March, Graham Scan, and Divide & Conquer by generating random points.

  • A specialized LeftHull algorithm is included for polygon convex hulls.

  • These algorithms are implemented from the psuedocode in their original research papers, wherever available.

See Code

Nov 2019 (Python)

Convolutional Neural Networks

We classify images of recyclable trash into different categories by using the following:

  • Support Vector Machines (SVM): One vs Many

  • Convolutional Neural Networks (CNN):

    • Architectures: VGG10, VGG13, VGG16, ResNet34

    • Hyperparameters: Pooling, Batch Normalization, Depth, Data Augmentation

Poster

Research

Jun 2023 (R, Python)

Thirty years of academic finance

in The Journal Of Economic Surveys

Employed an unsupervised Machine Learning Bayesian Model, the Structural Topic Model, to analyze financial journals.

Paper

May 2018 (Java)

Wearable Navigation and Assistive System for Visually Impaired

in the 2nd International Conference on Trends in Electronics and Informatics, published by IEEE

Developed an Arduino project integrating ultrasonic sound sensors and a gyroscope onto a glove, accompanied by custom code aimed at enhancing navigation for individuals with visual impairments.

Paper

Dec 2017 (Java, Android Studio)

Intelligent disaster warning and response system with dynamic route selection for evacuation

in the 2017 International Conference on Intelligent Sustainable Systems, published by IEEE

Created an Android application designed to issue natural disaster warnings and guide users to the closest warehouse, factoring in considerations such as distance, capacity, and other relevant metrics.

Paper

Oct 2017 (PHP, HTML, CSS)

Multi-platform college management framework

in the 2017 2nd International Conference on Communication and Electronics Systems, published by IEEE

This project entails the development of a web application aimed at modernizing and optimizing record management processes in colleges and universities. By digitizing these tasks, it effectively lessens the administrative burden. The application encompasses features such as an online paper-checking module, attendance tracking, and a digital notice board, all of which contribute to enhanced efficiency in academic operations.

Paper

Contact Me

Ontario, Canada

Number: +1 (438) 866-6499

Email: abbmeghani@gmail.com

Email Me