print("Mauro's Portfolio")


Hi, I'm Mauro, nice to meet you!
I'm a Machine Learning research engineer in love with AI and its limitless applications.

I am currently looking for a PhD position in Machine Learning. My main research interests are Reinforcement Learning and Bayesian statistics. I would be happy to get in touch if you have any suggestions, opportunities, or just want to have a chat.

Get in touch

Mauro's Portfolio


Hi, I'm Mauro, nice to meet you!
I'm a Machine Learning research engineer in love with AI and its limitless applications.

I am currently looking for a PhD position in Machine Learning. My main research interests are Reinforcement Learning and Bayesian statistics. I'd be happy to get in touch if you have any suggestions, opportunities, or just want to have a chat.

Get in touch

Research: Paper Notes



I read many papers for work and personal interest. I usually read about Bayesian statistics, (Inverse) Reinforcement Learning, Autonomous Driving, Physics simulation, Computer Graphics and I've been exploring Biologically-inspired AI lately. Sometimes I post here the summary of the papers I read.

Go to paper notes

My Data Science and Machine Learning Projects



This is a partial list of my Machine Learning and Data Science projects, completed during academic courses and free-time. Main findings and challenges are highlighted, in form of R Notebooks or IPython Notebooks. My professional projects are not included.


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Deep Reinforcement Learning for Games

Develop a Bot using Deep Q-Learning that automatically learns how to play the game Snake


  • PYTHON
  • TENSORFLOW
  • PYGAME
  • KERAS
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Artificial Intelligence meets Art: Neural Transfer Style

Implement a Deep learning technique to transfer the style of a painting to a chosen image


  • PYTHON
  • TENSORFLOW
  • DEEP LEARNING
  • KERAS
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Flight Delay Prediction

Modeling and predicting the delay of 7 million US domestic flights using Big Data Tools.


  • SPARK
  • SCALA
  • R
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Highway patrol

Develop a Java application using Flink, implementing functionalities of Speed Radar, Average Speed Control and Accident Reporter on data streams.


  • JAVA
  • FLINK
  • DATA STREAM
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TPC-C Benchmark

Develop a Java program using HBase to create, load tables, and implementing four different queries to simulate the activity of any company that must manage, sell, and distribute products or services.


  • JAVA
  • HBASE
  • HADOOP
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Raw data processing for diseases prediction

Processing raw data to feed a machine learning model using IBM SPSS Modeler.


  • PYTHON
  • RAW DATA
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My Computer Graphics and Physics Simulation Projects



This is an incomplete list of my Computer Graphics projects, where I implement different approaches based on Monte Carlo statistics and Machine learning to my toy ray tracer. I am particularly interested in Physically Based Rendering and noise reduction.


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Monte Carlo Path Tracer

Implementation of different standard Monte Carlo approaches in path tracing, and comparison with Next event estimation


  • C++
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Q-Learning for Monte Carlo importance sampling

Implementation of a Machine learning based approach applied to the light transport equation for importance sampling


  • C++
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About me


  • Master thesis researching Q-Learning and Deep Reinforcement Learning for Importance Sampling in Physically-based rendering.

    02/2019 - 10/2019

    TU Delft (Delft, The Netherlands)

    Technical University of Eindhoven (Eindhoven, The Netherlands)

    Master thesis researching Q-Learning and Deep Reinforcement Learning for Importance Sampling in Physically-based rendering.
    Supervisor: Prof. Elmar Eisemann - TU Delft
    Supervisor: Prof. Decebal Mocanu - TU Eindhoven

  • EIT Digital Double Degree - MSc in Data Science, Distinction

    09/2017 - 10/2019

    Entry University: Universidad Politecnica de Madrid (Madrid, Spain)

    Exit University: Technical University of Eindhoven (Eindhoven, The Netherlands)

    A two-year Master double degree programme, coordinated by the European Institute of Innovation and Technology (EIT). Major in Data Science, and Minor in Innovation and Entrepreneurship.
    Topics covered:
    • Machine Learning algorithms and Deep Learning (Computer Vision, NLP)
    • Big Data Ecosystem: creation of Big Data application with Spark (Scala), Flink, HBase
    • Advanced statistics with R
    • Innovation and Enterpreneurship, focused on start-ups development.

  • Premaster in Data Science and Business Information Technology

    09/2016–07/2017

    University of Twente

    Enschede, The Netherlands

    Bridge program on Computer Science and Business IT. Among the courses I took, I followed joint courses with Delft University and Standford University.

  • Bachelor of Science in Mechanical Engineering

    09/2011 – 02/2015

    Polytechnic University of Milan

    Milan, Italy

    Thesis Project: "Mechanical design and virtual prototyping for thermal turbomachinery"
    • Cost accounting and decision making, economic criteria for the dimensioning of industrial plants and facilities, layout planning
    • C++ and Matlab programming
    • Operations Research and linear planning for optimization
    • Design methods and CAD Softwares (Autodesk Inventor, SolidWorks, SolidEdge, PTC Creo)

  • Machine Learning Research Engineer

    03/2019 - Present

    TNO - Netherlands Organisation for Applied Scientific Research

    Helmond, The Netherlands

    Focus on researching and applying Machine Learning techniques for autonomous driving:
    • Deep Learning for trajectory prediction and decision making
    • (Inverse and Deep) Reinforcement Learning for planning and decision making
    • Bayesian statistics for uncertainty modelling, Explainable AI and Interpretable AI

  • Machine Learning Intern

    03/2018 - 08/2018

    Zinkcloud

    Madrid, Spain

    Developed Deep Learning algorithms for Image detection in aerospace applications (Python, Tensorflow, Keras).

  • Internship as Product manager assistant and Aerospace Engineer

    02/2015 - 04/2015

    Jenoptik GmbH

    Hamburg, Germany

    • Mechanical design and optimization for aerospace systems (drones, Airbus components)
    • Product Management: market analysis for military and civil helicopters, market research and analysis for unmanned aerial veichle

  • Trainee as Mechanical design Engineer

    09/2014 - 01/2015 (3 Months)

    Stilmas

    Milan, Italy

    Computational Fluid Dynamics and turbomachinery optimization

About me


  • Master thesis: Deep Reinforcement Learning for importance sampling in Physically-based rendering.
    02/2019 - 10/2019

    TU Delft (Delft, The Netherlands)

    Technical University of Eindhoven (Eindhoven, The Netherlands)

    Master thesis researching Q-Learning and Deep Reinforcement Learning for Importance Sampling in Physically-based rendering.
    Supervisor: Prof. Elmar Eisemann - TU Delft
    Supervisor: Prof. Decebal Mocanu - TU Eindhoven

  • EIT Digital Double Degree - MSc in Data Science
    09/2017 - 10/2019

    Entry University: Universidad Politecnica de Madrid (Madrid, Spain)

    Exit University: Technical University of Eindhoven (Eindhoven, The Netherlands)

    A two-year Master double degree programme, coordinated by the European Institute of Innovation and Technology (EIT). Major in Data Science, and Minor in Innovation and Entrepreneurship.
    Topics covered:
    • Machine Learning algorithms and Deep Learning (Computer Vision, NLP)
    • Big Data Ecosystem: creation of Big Data application with Spark (Scala), Flink, HBase
    • Advanced statistics with R
    • Innovation and Enterpreneurship, focused on start-ups development.

  • Premaster in Data Science and Business Information Technology
    09/2016–07/2017

    University of Twente

    Enschede, The Netherlands

    Bridge program on Computer Science and Business IT. Among the courses I took, I followed joint courses with Delft University and Standford University.

  • Bachelor of Science in Mechanical Engineering
    09/2011 – 02/2015

    Polytechnic University of Milan

    Milan, Italy

    Thesis Project: "Mechanical design and virtual prototyping for thermal turbomachinery"
    • Cost accounting and decision making, economic criteria for the dimensioning of industrial plants and facilities, layout planning
    • C++ and Matlab programming
    • Operations Research and linear planning for optimization
    • Design methods and CAD Softwares (Autodesk Inventor, SolidWorks, SolidEdge, PTC Creo)

  • Machine Learning Research Engineer
    03/2019 - Present

    TNO - Netherlands Organisation for Applied Scientific Research

    Helmond, The Netherlands

    Focus on researching and applying Machine Learning techniques for autonomous driving:
    • Deep Learning for trajectory prediction and decision making
    • (Inverse and Deep) Reinforcement Learning for planning and decision making
    • Bayesian statistics for uncertainty modelling, Explainable AI and Interpretable AI

  • Machine Learning Intern
    03/2018 - 08/2018

    Zinkcloud

    Madrid, Spain

    Developed Deep Learning algorithms for Image detection in aerospace applications (Python, Tensorflow, Keras).

  • Internship as Aerospace Engineer and Product Management assistant
    02/2015 - 04/2015

    Jenoptik GmbH

    Hamburg, Germany

    • Mechanical design and optimization for aerospace systems (drones, Airbus components)
    • Product Management: market analysis for military and civil helicopters, market research and analysis for unmanned aerial veichle

  • Trainee as Mechanical Design Engineer
    09/2014 - 01/2015

    Stilmas

    Milan, Italy

    Computational Fluid Dynamics and turbomachinery optimization

Contact Me


maurocomi92@gmail.com
Currently in Eindhoven (the Netherlands)
www.000webhost.com