Computer Science Engineer

Pietro Di Marco

Æ +1-312-***-**** Q ***************@***.***

https://www.linkedin.com/in/pietrodimarco/

Graduate Computer Science engineer completing the final year of a master’s degree. Possess a wide range of Computer Science knowledge applied in many different projects during the academic years. Passionate about Machine Learning and Artificial Intelligence.

Education

Double Degree Program. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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UIC Chicago, U.S.

Master of Science in computer science, GPA: 3.3/4 2016–May 2018

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Politecnico Di Milano Milano, Italy

Master of Science in computer science, GPA: 3.3/4 2016–July 2018

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Politecnico Di Milano Milano, Italy

Bachelor of Science in computer science, Score: 95/110 2013–2016 Skills

+ Programming: Proficient in: Java, C, Python, HTML, MySQL Also basic ability with: Assembly, VHDL, JavaScript, PHP.

+ Language Skills: Italian (Native Language), English (Good). Research Experience

+ Research Assistant: (UIC, December-May 2018)

- Conducted experiments to enhance the Security of a Web Application.

- Worked with Professor Aravinda Sistla at the department of Computer Science. Notable Projects

+ Does #FakeNews make you popular?: (UIC, August-November 2017)

- Demonstrated that between similar tweets, the hashtag "#FakeNews" is correlated with more viral tweets.

- Worked with a dataset of 13 gigabytes file stored in MongoDB.

- Virality defined as the Wiener Index of the cascade the tweet is part of.

- The "similarity" between tweets is assessed using propensity score matching.

- The presence of the "#Fake-News" in a tweet resulted in a greater virality compared to tweets that had the same propensity, but did not have any of the fake news related hashtag.

+ RoomMap App (UIC, August-November 2017)

- Developed University Indoor Navigator for Android.

- Worked with Beacons and Indoor Atlas.

- Many features: navigate to a certain room, restroom and display their availability.

+ Default Prediction On Loan Dataset: (Politecnico Di Milano, August-November 2016)

- Developed a data mining model that could predict the risk of default for credit card users. The goal was to maximize the F1 measure given a 6MB dataset.

- Tried a series of different models: Decision Trees and Random Forests, Neural Networks, Logistic Regression, AdaBoost and XGBoost.

- XGBoost was the most performing, with F1 measure close to 55% in crossvalidation compared to a 40% baseline.

+ Council Of Four: (Politecnico Di Milano, January-July 2015-2016))

- Developed a multithreaded and distributed game.

- Java for the core, JavaFX for the graphical interface.

- Created a working tested application and applied well known software design patterns such as: MVC, Factory, Adapter, Decorator, Observer.

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