Gian Piero Bandieramonte

November First is a payment platform for transferring funds internationally in different currencies. The platform has been in place in the company's IT base since the moment I began this project. The goal was twofold: to upgrade the platform to exploit a more comprehensive array of functionalities from the newer version of the FIX protocol and to revamp the platform as it presented deep performance and scalability issues.

I recreated the payment platform in a way that it could perform quote and trade requests, as well as process the respective responses in a faster and more stable fashion. The code was also rendered more maintainable and scalable so that further enhancements could be done more efficiently. A wider array of functionalities were added to the trading platform, including dealing with requests for quotes (RFQ) and market data simultaneously, enabling the trading of SPOT, TOD, and TOM orders, and handling express payments.

The offering of these new functionalities solicited by customers and the fueling of the number of transactions they perform on the platform led to a significant increase in the number of new account openings and, consequently, in the company's revenue by at least 12%.

Worked for Brainlab, a company that had an algorithm that performed image registration between X-rays and digitally generated X-rays (DRR). Such an algorithm did not have a unit testing framework to find potential errors in its precision. Providing this framework was complex because the algorithm relied on 3D imaging APIs such as DirectX. This fact implied that any conformance test checking the correctness of the algorithm would have to rely on methods without using 3D imaging APIs. I, therefore, designed an image registration method emulating some parts of the DirectX functioning. Here geometry was exploited by also using supporting C++ headers. This code performed image registration on specific border cases. The resulting images were then compared pixel by pixel against the results of the original algorithm.

With this method, we found significant discrepancies in the pixel patterns between the algorithm's results and my unit testing method's results. Handling such discrepancies increased by roughly 8% of the algorithm's precision, which led to better radiotherapy irradiation beam precision when targeting tumors in patients with cancer and to better cancer treatment solutions offered by Brainlab.

I am currently developing an eCommerce web app for a global organization to facilitate the online sale of books in various formats, including physical and digital deliveries of books. The app comprises three projects:

• A React storefront that powers the front end with the interface where users can browse and place orders.
• A React dashboard where managers can oversee the inventory, fulfill orders, manage users, and more.
• A Python API that stores and provides inventory and user data and powers the required back-end functionality.

Both the storefront and the dashboard communicate with the API to receive and store inventory and user data.

This project is based on Saleor's successful open source platform (https://saleor.io/).

Project details under NDA.

Created a web app as a full stack developer that enabled the online trading of stocks within a brokerage organization that otherwise could only take trading orders from its clients via phone. This was critical for boosting the organization's rate of orders placed by its clients, ultimately increasing its revenues considerably.

The project was developed using ASP.NET and C# to power its back end, using SQL to manage the data, and finally, a combination of CSS, HTML, and JavaScript to power its front end. Both MS Visual Studio and Adobe Dreamweaver were utilized as IDEs.

Co-founded an investment management firm where I served as its chief analyst and developed an algorithm to cherry-pick undervalued fixed-income securities.

To accomplish this, financial data from hundreds of companies were downloaded through the Bloomberg platform using its proprietary API, which was fed into the Excel models I created. An algorithm ran using such data powered by Excel VBA to aid in analyzing huge amounts of data. An array of charts was also created to assist in the process of selecting the undervalued financial securities.

In addition to picking undervalued fixed-income securities, they also had to be tailored to the financial needs and goals of our clients for whom we designed the investment portfolios. The aforementioned algorithm, at the same time, was responsible for this sort of tailoring.

The project's goal was to implement a program that finds the optimal path to solve any shuffled instance of Rubik's cube using an acceptable amount of time and memory resources. By optimal path, I mean the shortest possible path from the initial shuffled instance to the ordered instance. There can be multiple paths leading to the same ordered instance of Rubik's cube.

TASKS
Rubik's Cube has an astronomical number of ways it can be permuted, and the code had to be efficient with time and memory usage. I used C++ due to its high level of performance and control with which the programmer can manage the memory. The path-finding algorithm known as A*, i.e., A Star, was one of the main actors of this solution and worked especially well with this kind of problem.

After code optimizations, tests, and refactoring, a robustly designed program was devised that could solve any shuffled instance of Rubik's cube using an acceptable amount of time and memory.

The client requested multiple loan calculators that would compute metrics, such as the repayment plan, interest cost, and amortization schedule of conventional amortized loans.

As a full-stack developer, I created these calculators and presented them in a user-friendly UI within the web app.

A neural network system was developed using MATLAB with the purpose of imitating a successful stock investor.

The system would be fed with the trading patterns of such investor and back-tested to ensure consistency. It was also tested against real-time forward-looking data.

A book was then published following its success. A link to the book is shown in the project URL.

My main contribution to the Life-Assist company so far is a complete redesign of its web app's homepage. Their marketing team documented all the design requirements for a successful redesign. Completing this project required implementing CSS animations, dynamic menus, carousel sliders, JavaScript and TypeScript functions, and more. A responsive design and compatibility with major browsers were critical requirements. Back-end work was also essential because the homepage is closely connected to many modules within the API. Therefore, I ended up working with .NET, C#, and SQL Server to implement new modules and controllers while extending the API's core functionality. New SQL tables and stored procedures were also created. The result was a fully modernized, enhanced, and more stable homepage where the IT coordinator responsible for this project exposed his total satisfaction with the new homepage.