Curriculum vitae


I am a Machine Learning researcher with a strong background in math.

My main expertise includes:
Monte-Carlo methods, Bayesian inference, Reinforcement Learning, MDPs, Relational Learning, Logic programming, Deep Learning.

I am particularly interested in Reinforcement Learning, Deep Learning and their combination.

Work experience


Software developer

Dreamslair Entertainment s.r.l., Valenzano (Italy)

Analysis and development of browser-games (server-side and client-side)​​.


Research project

UNIVERSITA' DEGLI STUDI DI MILANO - BICOCCA , Department of Informatics, Systems and Communication, Milano (Italy)

collaboration in "Neuroweb" project​​ (Integration and sharing of information and knowledge in neurology and neurosciences)​



@ITIM (Italian Association of Telemedicine and Medical Informatics), Desio (Italy) Organizational and didactic collaboration in meetings and seminaries:
  • "Grid technologies in biomedicine and healthcare" at "Mediterranean Meeting of Telemedicine"
  • Seminar on Data Analysis and Statistic Software in Medicine. Main topics: neural network MLP and SOM
  • Design and Development of a web portal to manage health information. Main technologies: PHP and SSL.



Postdoctoral researcher

KU Leuven, Leuven (Belgium)

Involved in EU ReGROUND project, whose goal is to perform symbol grounding to link human language, internal robot belief and perception for robotic tasks.

Ongoing research:

  • RelNet: Relational Neural Network to perform relational learning with the power of neural networks
  • Relational symbol grounding: learn the meaning of relations extracted from sentences
Teaching (exercise sessions) “Machine Learning and Inductive Inference”


Doctor of Engineering Science (PhD) in Computer Science

KU Leuven, Leuven (Belgium)

PhD thesis: Hybrid Probabilistic Logic Programming

Main topics: Probabilistic programming, Logic programming, Bayesian inference, Monte-Carlo methods​, Particle filtering, probabilistic planning (MDPs), object tracking, Robotics.

Involved in EU FP7 First-MM project, whose goal is to develop autonomous mobile manipulation robots that can perform complex manipulation and transportation tasks.

Obtained IWT (government agency for Innovation by Science and Technology) scholarship from 2012.

Teaching and supervision
  • Teaching (exercise sessions) and projects correction for “Machine Learning and Inductive Inference”
  • Master student thesis supervision (main topics: relational learning, Robotics, learning by demonstration)


Institute of Cognitive Sciences and Technologies − CNR (Rome - Italy)

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


Master degree in Computer Systems Engineering, specialization in intelligent systems

Politecnico di Bari, Facoltà di Ingegneria (Polytechnic of Bari, Faculty of Engineering), Bari (Italy)

Final Mark: 110/110 cum laude​

Master thesis: "Boolean Games and Description Logics for Multi-attribute Automatic Negotiation"

Main topics: mathematics, computer science, electronics, control,​​ physics.​


Bachelor Degree in Computer Systems Engineering

Politecnico di Bari, Facoltà di Ingegneria (Polytechnic of Bari, Faculty of Engineering), Bari (Italy)

Final Mark: 110/110 cum laude​

Bachelor thesis​:​ "Stereo-Matching Techniques Optimization Using Evolutionary Algorithms".

Main topics: mathematics, computer science, electronics, control, physics​.​


Diploma di Perito informatico (second grade secondary school with IT specialization)

ITIS "Luigi dell'Erba" (Istituto Tecnico Industriale Statale), Castellana Grotte (Italy)

Final Mark: 100/100

Main topics: mathematics, physics, chemistry, computer science, electronics


Programming languages / frameworks
  • Python (including Numpy, Scikit-learn, Tensorflow, Theano, Autograd)
  • Julia (including Knet for automatic differentiation)
  • C / C++
  • Prolog (Yap-Prolog)
  • ROS (Robot Operating System)


PhD scholarship

IWT (government agency for Innovation by Science and Technology) scholarship for strategic base research (doctoraatsbeurs van strategisch basisonderzoek), 2012-2015

Best Paper awards
Best Student Paper - Machine Learning Journal Award:

D. Nitti, V. Belle, L. De Raedt. Planning in discrete and continuous Markov decision processes by probabilistic programming. European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD 2015).

Personal (unpublished) projects

  • Differentiable assembly machine (python, Tensorflow): a simplified differentiable CPU model that extends “Neural Turing Machines”.
  • Deep reinforcement learning agents (Q-learning, policy gradient and other methods) applied to Gym-OpenAI environments.
  • Adaptive importance sampling.
  • Deep learning (Tensorflow, Theano, Autograd): auto-encoders, variational auto-encoders, convolutional NN, recurrent NN.
Some projects are publicly available at

Publications list here