Matthew Mamelak

About Me

Hi everyone! My name is Matthew Mamelak. I hold an undergraduate degree in Computer Engineering from Queen's University and am currently pursuing a Master's degree in Mathematical Finance at the University of Toronto. My interest in technology and computers began at a young age and continued through high school, where I was enrolled in a four-year engineering specialization stream. This experience solidified my passion for computer technology and my aspiration to pursue a career in software development and finance.

Throughout my undergraduate studies, I gained proficiency in Python, Java, and C/C++, focusing on problem-solving and data analysis. My coursework taught me to break problems down into components and develop creative solutions, fostering critical thinking and effective organization. I have learned to present data clearly, communicate ideas effectively, and collaborate within team-based projects.

The rigorous nature of the Queen’s computer engineering program improved my time management skills, which were further strengthened by my professional experiences. Over two summer internships and two years of part-time work at TD Bank as a Business Automation Analyst, I applied my programming skills to discover innovative solutions to real-world problems. These experiences also enhanced my ability to prioritize tasks and manage multiple projects simultaneously.

Alongside my academic and professional pursuits, I am studying for my CFA Level 1. I also served as a Project Manager for Queen's University Business Engineering (QUBE), where I taught team members how to create discounted cash flow (DCF) models, aiding them in understanding financial modeling, cash flow projection, and risk assessment for better valuation comprehension. Additionally, I was a member of the Queen's Algorithmic Trading team, where I developed a buy-side pairs trading algorithm. This achievement won 1st place in a four-month trading period competition, achieving a 13% return and earning a $500 cash prize.

Beyond my comittment to the tech and finance world, I am passionate about sports. I have played competitive hockey and tennis my entire life and continue to play intramural hockey and other sports like baseball and volleyball.

Here is a team photo of my summer hockey team.

Projects

Black-Scholes Option Pricing Calculator

- Developed an interactive web application using Streamlit to calculate European option prices for both non-dividend and dividend-paying stocks.
- Implemented the Black-Scholes model, allowing users to input parameters like stock price, volatility, and time to maturity, and visualize how option prices decay over time.
- Integrated educational content within the app to help users understand the underlying financial model, with interactive sliders for real-time exploration of formula components.
- Used Python libraries such as NumPy, SciPy, and Matplotlib to perform calculations and generate dynamic plots for time decay visualization.

Early Warning of Ovarian Cancer Project

- Developed a predictive model using the PLCO dataset from the National Cancer Institute, achieving 94.58% accuracy and 91.96% recall for early detection of ovarian cancer, especially in asymptomatic individuals.
- Created a user-friendly web and mobile application that assesses ovarian cancer risk through a Random Forest machine learning model, with a strong emphasis on user privacy by not retaining personal data.
- Consulted with a gynecologist and applied innovative techniques like SMOTE and biomarker dataset integration to refine the model, enhancing precision and recall to support public health and clinical applications.

Predicting Airbnb Rates Influenced by Local Events

- Analyzed how local events in New York City impact Airbnb pricing strategies.
- Approach included data cleaning, regression methods, and machine learning algorithms to achieve high predictive accuracy.
- Identified peak demand times, examined price elasticity during significant tourist events, and analyzed booking duration distribution.

Study Stream - QHacks 2024

- Uses AI to condense long articles, papers, and documents into brief summaries and bullet points.
- Generates quizzes for self-assessment and offers links to additional resources connected to the content processed.
- Integrates OpenAI's API for natural language processing (NLP) and pdf.js for extracting text from PDFs.
- Built with a React front end and operates on a Node.js back end, providing a strong and scalable system architecture.

BERT Transformer-based ML Model for Analyzing the Influence of Twitter Sentiments on TPa

- Developed a BERT transformer-based machine learning model to assess the impact of Twitter sentiments on a stroke treatment.
- Used the model to evaluate the role of public perceptions in the application of Tissue Plasminogen Activators (TPa) for stroke treatments.

OpenSeat - QHacks 2023

- A real-time library occupancy tracker using affordable NFC tags.
- Easily locates available seats, saving students valuable study time during busy hours.
- Students tap NFC tags with smartphones to mark seats as OCCUPIED or AVAILABLE.
- Developed front-end using HTML and CSS, and back-end functionality using PHP, SQL, and an Apache server connected to the Internet via ngrok.

Activity Classifier

- Collaborated with a team of students to develop an activity classifier that detects if the person is walking or jumping in real-time and on a given set of data.
- To accomplish this, we created a logisitic regression classifier and pre-trained it with our own raw data.
- We then performed webscraping using Selenium and Beautiful Soup to extract the live results from a specific URL.
- Built a GUI in python using PyQt to display the result.

Rocket Engine Test Stand Design

- Collaborated with a team of students to develop a rocket engine test stand for the Queen's Rocket Engineering Team.
- Coded a force sensor using Arduino and demonstrated adaptability by modelling the sensor's performance using SolidWorks.
- Assumed a leadership role as team co-lead by assigning tasks to other members, organizing meetings with the client, and proofreading documents for accuracy and completeness.

Emergency Fall Detection Device

- Worked with a group of five students to program an emergency fall detection device used to alert an emergency contact if it detects a sudden change in acceleration.
- Successfully incorporated sensors, a data processing unit, and a telecommunication device.
- Oversaw the programming of the accelerometer, Bluetooth module, buttons, LCD screen, and buzzer using Arduino software.

C++ Casino Game

- Worked with a group of students to develop a functioning, casino Game (using wxWidgets for our GUI).
- The game can run on Mac or Windows computers. The GUI includes different routes for each of the three games.
- The three games we have created are Blackjack, Roulette, and Odds Are. All variables were saved saved locally to avoid hosting a database.

ÀLA.HAUSSE

- This mobile application allows individuals to buy, sell, trade and lend their personal clothing assets.
- Currently working with a team to develop a multifunctional AI-Powered fashion sustainability ecosystem.
- Use Mixpanel software to monitor and optimize data generated through the ÀLA.HAUSSE mobile application.

Resume

Contact

• LinkedIn
• Instagram
• GitHub

Elements

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print 'It took ' + i + ' iterations to sort the deck.';