Davide Nitti · Curriculum vitae

Machine learning researcher with a background in probabilistic models, reinforcement learning, computer vision, and logic programming.

01 · Overview

Profile

Machine Learning & Computer Vision

My main areas of expertise include machine learning, computer vision, Monte Carlo methods, Bayesian inference, reinforcement learning, Markov decision processes, relational learning, and logic programming.

I am particularly interested in reinforcement learning and deep learning, as well as their intersection.

02 · Career

Work experience

Sep 2017—Present

Senior Machine Learning Engineer

Prophesee · Paris, France

Prophesee produces neuromorphic, event-based cameras. I develop machine learning models for these cameras, including models for object detection and optical flow.

Feb—Jul 2010

Software Developer

Dreamslair Entertainment s.r.l. · Valenzano, Italy

Analyzed and developed both server-side and client-side browser games.

Aug 2007—Jul 2008

Research Project

University of Milano-Bicocca, Department of Informatics, Systems and Communication · Milan, Italy

Collaborated on the “Neuroweb” project, which focused on integrating and sharing information and knowledge in neurology and neuroscience.

Sep 2007—Jul 2008

Collaboration

@ITIM, Italian Association of Telemedicine and Medical Informatics · Desio, Italy

Provided organizational and teaching support for meetings and seminars:

  • “Grid technologies in biomedicine and healthcare” at the Mediterranean Meeting of Telemedicine.
  • Seminar on data analysis and statistical software in medicine, covering MLP and SOM neural networks.
  • Design and development of a web portal for managing health information, using PHP and SSL.

03 · Study

Education & research

Aug 2016—Feb 2017

Postdoctoral Researcher

KU Leuven · Leuven, Belgium

Contributed to the EU ReGROUND project, whose goal was to perform symbol grounding by linking human language, a robot’s internal beliefs, and perception in robotic tasks.

  • RelNet: a relational neural network combining relational learning with the capabilities of neural networks. (unpublished work)
  • Relational symbol grounding: learning the meaning of relations extracted from sentences.
  • Taught exercise sessions for “Machine Learning and Inductive Inference.”
Mar 2011—Aug 2016

PhD in Engineering Science (Computer Science)

KU Leuven · Leuven, Belgium

Thesis: Hybrid Probabilistic Logic Programming.

Main topics included probabilistic programming, logic programming, Bayesian inference, Monte Carlo methods, particle filtering, probabilistic planning, object tracking, and robotics.

Contributed to the EU FP7 First-MM project, focused on autonomous mobile manipulation robots for complex manipulation and transportation tasks.

Received an IWT scholarship from the government agency for Innovation by Science and Technology in 2012.

  • Taught exercise sessions and graded projects for “Machine Learning and Inductive Inference.”
  • Supervised master’s theses in relational learning, robotics, and learning by demonstration.
Oct—Dec 2010

Internship

Institute of Cognitive Sciences and Technologies, CNR · Rome, Italy

Internship in the EU FP7 Humanobs project, whose goal was to learn socio-communicative skills by observing and imitating people.

2005—2009

Master’s Degree in Computer Systems Engineering

Politecnico di Bari, Faculty of Engineering · Bari, Italy

Specialization in intelligent systems. Final grade: 110/110 cum laude.

Thesis: “Boolean Games and Description Logics for Multi-attribute Automatic Negotiation.”

Main topics included mathematics, computer science, electronics, control, and physics.

2002—2005

Bachelor’s Degree in Computer Systems Engineering

Politecnico di Bari, Faculty of Engineering · Bari, Italy

Final grade: 110/110 cum laude.

Thesis: “Stereo-Matching Techniques Optimization Using Evolutionary Algorithms.”

Main topics included mathematics, computer science, electronics, control, and physics.

1997—2002

Diploma di Perito Informatico

ITIS “Luigi dell’Erba” · Castellana Grotte, Italy

Upper secondary school diploma with an IT specialization. Final grade: 100/100.

Main topics included mathematics, physics, chemistry, computer science, and electronics.

04 · Toolkit

Skills

Languages & frameworks

Technical stack

  • Python
  • NumPy
  • scikit-learn
  • PyTorch
  • TensorFlow
  • C / C++
  • Julia
  • Knet
  • Prolog
  • YAP Prolog
  • ROS

05 · Recognition

Awards

2012—2015

PhD Scholarship

IWT scholarship for strategic basic research from the government agency for Innovation by Science and Technology.

ECML / PKDD 2015

Best Student Paper — Machine Learning Journal Award

D. Nitti, V. Belle, and L. De Raedt. “Planning in Discrete and Continuous Markov Decision Processes by Probabilistic Programming.”