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About me

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My Skills

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Languages :

Machine Learning Pacakages :

Modelling Technology :

Software and Tools :

Soft Skills :

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My Work Experience

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Oracle Canada, Full Stack Software Developer Intern
Oct. 2022 – March 2023

• Full stack development of UI and soft ware development of core logic of GraalVM Download Service.
• Created full detailed project documentation.
• Performed code reviews, deployed to live environment, code testing and code optimization.

Dept. of Electrical and Computer Engineering, McGill University , Software developer, Teaching Assistant, and Grader
Sept. 2021 – June 2022

• Research Assistant in ECE Engineering Lab from May to June, 2022.
• Volunteered to develop Arduino code and responsible for the fullstack development of the website for recycling pioneers.
• Taught advanced software language engineering (ECSE 539).
• Graded exams and assignments for Software Validation (ECSE 429) and for Model-Based Programming (ECSE 223).

School of Continuing Studies, McGill University , Teaching Assistant and Course Assistant
Sept. 2021 – Dec. 2022

• Taught basic and advanced concepts of Java (CCCS 300) and Database Design (CCCS 330), to adult students.
• Took tutorials, office hours, answered students' questions, and additional meetings to help students learn programming concepts.
• Went above and beyond to help students learn Java and taught them extra Java concepts like hashmaps.

McGill School of Computer Science, McGill University , Teaching Assistant
Sept. 2021 – Dec 2021

• Taught foundations of programming using Python (COMP 202) to undergraduate students.
• Took tutorials, office hours, presentations, and exam review sessions.
• Invigilated and graded the exams and assignments.

VMM Education, Web Developer Intern
January 2020 – May 2020

• Worked with clients, to analyze their needs, then design, develop, and test the software in order to meet those needs.
• Full Stack development of multiple websites, one similar to Netflix.
• Point of contact with clients for requirement gathering, knowledge transfer, and implementation.

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My Projects

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Here are some of my projects that I worked on during my job and studies.

GraalVM Download Service (Internship Project):

• Contributed to UI and Core logic of Oracle's GraalVM download service project.
• Updated the design of multiple web pages, designed the 404-not-found page and introduced new table columns.
• Refactored code, added new features, updated dependencies and performed bug fixes like enabling the deletion of correct files.
• Added a new artifact status and a cronjob to trigger status change if the required files are uploaded to the correct cloud bucket.

Detection of Modeling Mistakes in Class Diagrams (Thesis Research):

• Developed a Mistake Detection System (MDS) using Java that automatically compares multiple class diagrams with a correct solution and provides a list of mistakes to the student.
• The system can detect 97 different types of mistakes in a student's solution.
• Prepared a substantial test suite containing 382 tests to test the detection logic of the MDS.

COVID in Canada:

• Data analysis of tweets using python to understand the topics related to COVID discussed in Twitter Canada.
• Characterization of topics by computing the 10 words with the highest TF-IDF scores.

Introduction to Data Science:

• Developed projects using python and bash scripts involving Data Collection, Data Annotation, Data Analysis, and Interpretation.
• Hosted an online bokeh dashboard on AWS EC2.

Image Classification with Deep Learning Methods:

• Investigated the performance of supervised machine learning classification models to predict the total price of an image containing three clothing articles in the Modified Fashion-MNIST dataset.
• Implemented Neural Network(NN), Convolution Neural Network (CNN) and deep CNN.
• Explored the performance of the classifiers trained with Residual Neural Network (ResNet), VGG-16 and AlexNet. The model trained with VGG-16 had an accuracy of 97.88%.

Text Classification with Machine Learning Methods:

• Used the comments from the Reddit website as the text to be analyzed and predicted its subbredit or category out of 8 given subbredit labels or classes.
• Implemented Bernoulli Naive Bayes, Gaussian Naive Bayes, Multinomial Naive Bayes, Decision Tree, Random Forest, Bagging Decision Tree, Linear Support Vector Machine (Linear SVM), Logistic Regression, K Nearest Neighbor and Multi-layer Perceptron Classifier (MLP Classifier) algorithms.
• The model trained with MLP Classifier had an accuracy of 92.06%.

Methods to Improve the Performance of Logistic Regression:

• Investigate the performance of two-class logistic regression classifiers on two benchmark datasets “hepatitis” and “bankruptcy”.
• Techniques like normalizing the data, base expansion, transformation of variables and feature selection using filter method and wrapper method were implemented.
• The model had an accuracy of 82.26% for "hepatitis" dataset and 77.28% accuracy for "bankruptcy dataset".

Advanced Software Language Engineering:

• Model-Oriented Programming and Code Generation with Umple, EMF, ECore, and OCL.
• Model Transformation to User Requirements Notation using ATL Transformation Language.
• Implemented Sirius, a graphical domain-specific language. Generated Java code using Acceleo.

Model-Driven Software Development:

• Explored the Model-Driven Engineering (MDE) concepts of Abstraction, Modularity, Separation of Concerns and Reuse.
• Created a reusable Logging concern that can be applied to any design model whenever logging functionality is needed.
• Developed a variation interface (feature model + impact models) for Grocery store concern.

Ph.D. submission module for G.N.D University, Amritsar:

• Allows student to submit Ph.d submission details online.
• Add a system of feedback used by examiners and administration officials to interact and exchange thoughts regarding the evaluation of submitted Ph.D. thesis.

Online Streaming Plateform:

• This project is inspired by Netflix. Users can select from different packages and stream TV shows and movies. They can also add comments to the content provided.
• This project uses NLP to identify a positive or negative review using SentimentIntensity Analyzer of VADER (Valence Aware Dictionary and sEntiment Reasoner).
• GitHub Repo : Online Streaming Plateform

Helping-Medicine:

• Software keeps track of medicine stock, their expiration date, purchase and sale history.
• Automatically notifies the owner about the medicine stock details, such as required stock, expired stock and expiry dates of all stored medicines.
• GitHub Repo : Helping-Medicine

Hotel-Management System:

• This project enables the hotel to manage the booking of all rooms and related facilities with a great efficiency.
• Enables room booking, cancellation and room management.
• GitHub Repo : Hotel-Management System

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My Publications

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SAM 2022

• Prabhsimran Singh, Younes Boubekeur, Gunter Mussbacher A research paper on Detecting Mistakes in a Domain Model, 14th SAM Conference 2022, Nov. 2022.

MODELS 2022

• Younes Boubekeur, Prabhsimran Singh, Gunter Mussbacher A DSL and Model Transformations to Specify Learning Corpora for Modeling Assistants, MODELS 22, Nov. 2022.

REFSQ 2021

• Prabhsimran Singh, Gunter Mussbacher A poster presentation on Domain Modelling Mistake Detection System , REFSQ 21, Essen, Germany as Virtual Event, April 2021.

ICMDE2021

• Kamaljit Kaur, Prabhsimran Singh, Parminder Kaur A Review of Artificial Intelligence Techniques for Requirement Engineering , ICMDE 2021 at SRM University, Sonipat, India, Jan 2021.

Computer Society of India 53rd Annual Convention

• Harpreet Singh, Prabhsimran Singh, Parminder Kaur A Research Paper on Solving the Website Structure Optimization problem using Genetic Algorithm, in Computer Society of India 53rd Annual Convention, Bhubaneswar, India, January 2020.
  

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Extra Curricular Activities

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At McGill University

• Part of 'Recycling Pioneers' team whose goal is to improve waste habits at McGill University through education and technology.
• Student Volunteer in MODELS 2020 conference.
• Volunteering as a "Buddy"(First contact) in McGill's "Buddy Program".
• Volunteering to be a "Mentor" in McGill's "New Student Mentorship Program".

At Guru Nanak Dev University

• Member of the Technical Team and Placement Team in CESS(Computer Engineering Student Society).
• Coordinated placement/hiring drives. Actively help and guide students regarding placement activities and getting into masterʼs studies abroad through in-person and virtual sessions.
• Coordinated a gaming event in Polaris Tech-Fest at GNDU in Oct 2018.
• Part of a tree plantation drive held locally in my home city, Amritsar, India.

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