CLAI Laboratory

Computational Logic and Artificial Intelligence

The CLAI Laboratory was established by the Academic Senate on 17/12/2020 and is dedicated to theoretical and applied research in computational logic and artificial intelligence, with a particular focus on machine learning, deep learning, automated reasoning, formal methods for the analysis, verification, and testing of software, systems, and processes to ensure their correctness and safety, combinatorial optimization problems, interaction among non-cooperative agents in social and communication networks, automated and interactive theorem proving, games, reinforcement learning, and planning.

The laboratory primarily carries out research activities but also supports teaching by hosting specific exercises, undergraduate and master's thesis students, research fellows and PhD students, and internships.

The goal of the laboratory is to create links with local and national industrial partners to participate in projects of common interest and foster technology transfer.

The laboratory is located in the Department of Economic Studies, Viale Pindaro 42, Pescara. The scientific director of the CLAI Laboratory is Prof. Maria Chiara Meo.

Nationally and Internationally Relevant Activities

• Two CLAI Laboratory projects have been funded under the cascading calls of the FAIR (Future Artificial Intelligence Research) Extended Partnership, topic “1. Artificial Intelligence: Foundational Aspects” (PNRR), for a total of €440,000:
  1. EcoGames – Existence, Complexity and Efficiency of Stable Solutions in Green-Oriented Games
  2. SMARTK – Smart Knowledge: Enhancing Argumentation and Abstraction for Explanation and Analysis.
  The CLAI Laboratory is starting its collaboration with one of the largest Artificial Intelligence projects in Italy!
• Organization of the First Italian School on Geometric Deep Learning – July 25–28, 2022 – Pescara (IT)
  • The school has ended, but you can watch the recordings of Michael Bronstein, DeepMind Professor of AI at the University of Oxford.
  • The school was funded by the Association for the Advancement of Artificial Intelligence (AAAI) and by Indam.
• Participation in the National PhD in Artificial Intelligence PhD-AI.it
  • Affiliated with the AI & Health and Life Sciences section of the National PhD in AI starting from the 37th cycle.
• Node of the CINI National Laboratory of Artificial Intelligence
  • Prof. Francesca Scozzari has been appointed as the head of the Artificial Intelligence node at Università d’Annunzio. Congratulations!

Founding Members of the Laboratory

Artificial Intelligence Courses

Some Artificial Intelligence courses taught by CLAI members in the degree programs at Università d’Annunzio:

• Artificial Intelligence
  • Symbolic Artificial Intelligence module
  • Machine Learning module
• Mathematics for Deep Learning
• Reinforcement Learning in Artificial Intelligence

Computing Infrastructure Management

Members of the laboratory manage the following computing infrastructure:

• oVirt Platform with 3 Nodes
  • ovirt-vlab-01.unich.it
    • PowerEdge R7425 (rack-mounted)
    • 2 AMD EPYC 7301 CPUs (2 × 16 cores)
    • 512 GB RAM
    • 2 × 558 GB SAS disks in RAID 1
    • 1 nVidia Tesla T4 GPU
    • 4 × 10Gbps Ethernet ports
    • oVirt compute node
  • ovirt-vlab-02.unich.it
    • PowerEdge R7425 (rack-mounted)
    • 2 AMD EPYC 7301 CPUs (2 × 16 cores)
    • 512 GB RAM
    • 2 × 558 GB SAS disks in RAID 1
    • 4 × 10Gbps Ethernet ports
    • oVirt compute node 2
  • storage-vlab-01.unich.it
    • PowerEdge R7425 (rack-mounted)
    • 2 AMD EPYC 7301 CPUs (2 × 16 cores)
    • 256 GB RAM
    • 2 × 223 GB SATA SSDs in RAID 1
    • 24 × 658 GB SAS disks in RAID 10 (6 TB total)
    • 4 × 10Gbps Ethernet ports
    • CentOS 8 used exclusively as oVirt storage node
• CLAI Server
  • Dell EMC PowerEdge R740xd (rack-mounted)
  • 2 Xeon Gold 6238R CPUs (2 × 28 cores)
  • 512 GB RAM
  • 2 × 480 GB SAS SSDs in RAID 1
  • 5 × 2.4 TB SAS SSDs in RAID 5 (9.6 TB total)
  • 2 nVidia A40 GPUs
  • 2 × 10Gbps Ethernet ports
• Server zeus.unich.it
  • Dell PowerEdge T620 (tower)
  • 2 Xeon E5-2640 CPUs (2 × 8 cores)
  • 64 GB RAM
  • 2 × 279 GB SAS 10K disks in RAID 1 (279 GB total)
  • 3 × 3726 GB near-line SAS disks in RAID 5 (7.45 TB total)
  • CentOS 7 with some virtual machines (KVM)
• Server atena.unich.it
  • Dell PowerEdge R620 (rack-mounted)
  • 2 Xeon E5-2640 CPUs (2 × 8 cores)
  • 64 GB RAM
  • 2 × 279 GB SAS 10K disks in RAID 1 (279 GB total)
  • 4 × 838 GB SAS disks in RAID 5 (2.51 TB total)
  • CentOS 7 used exclusively as hypervisor (KVM)