Michele Lombardi Home Page
post doctoral fellow
DISI, Università di Bologna
Tel. +39 051 20 93270
I am a fixed-term Assistant Professor at the DISI department of the University of Bologna, working on Combinatoral Optimization and Decision Support Systems. In particular, my research activity is focused on hybrid optimization methods, based on heterogeneous techniques such as Constraint Programming, (Mixed) Integer Linear (and Non-Linear) Programming, and Machine Learning. My main application fields are Resource allocation and Scheduling problems, Cyclic Scheduling (e.g for control system design), and Scheduling problems in the presence of Uncertainty.
More recently, I have started to work with prof. Michela Milano on a methodology to solve optimization problems over complex system by embedding Machine Learning models withing optimization models: we called it "Empirical Model Learning". If you are interested, you can find more information here, or you can check some code for embedding Neural Networks in CP.
I have to say that I like this "Empirical Model Learning" idea very much, and not just because it's something I am working on. I actually like the idea that by hybridizing CP (or another optimization technique) and learning we can tackle problems that would be impossible to address by using either of the techniques alone.
Some shared resources (some refer to past activities...):
- Together with Standa Zivny, I was Doctoral Programme chair at CP 2012. If you are interested have a look at the Doctoral Programme web site.
- Together with Paolo Liberatore and Floriano Scioscia, I chaired the Doctoral Consortium of the AIxIA Symposium 2012. For more information you can check the DC web site.
- The full text of my PhD thesis is available for download (see the link on the left).
- I gave lectures at the 2012 ACP Summer School in Wroclaw, Poland. You can access here lesson 1, lesson 2 and lesson 3.
I have recently started to share code via git repositories and Virtual Machines. Currently, I have:
- A repository about a work on devising a Lagrangian Propagator for Neural Networks in CP
- More VMs are coming...