For the PhD students of the cycle XXXVIII, the study plan includes:
1. INDIVIDUAL RESEARCH, guided by at least one Tutor, which culminates with the defense of an original PhD dissertation. The Academic Board appoints one Tutor for each student. In some cases, more Tutors may be appointed. Students will have daily contact with the research group to which they belong. They should expect a formal meeting with their Tutor(s) at least once a month.
All PhD students will present their research regularly throughout their three years of the programme in seminars, annual reviews, summer schools, and scientific meetings both in Italy and abroad. Students will get some funding to attend scientific schools, conferences and workshops.
2. SPECIALIZED COURSES, of 1, 2 or 3 credits, for a total of 15 credits to be acquired in the first two years (each credit corresponds to either 8 hours of lectures or 15 hour of practice). The student chooses the courses of interest to be attended on each one of the first two years; four of such courses, for at least a total of 8 credits, require a final exam to be given by the end of the second year of the PhD Programme. By the end of the first year, the student has to pass at least two exams. The specialized courses may also include international schools of interest for the individual research.
3. SEMINARS on various topics, to be attended during the three years of the PhD Programme, for at least 40 hours: a) 10 hours on topics
related to advanced information technology; b) 10 hours on scientific research writing; c) 20 hours on topics related to research programs,
knowledge sharing with industry, copyright and patents. Such seminars are part of the student education, as required by article 4, section 1
2)(f) ) of the 14th Dec 2021 Ministerial Decree n. 226 ("Regulations concerning ... criteria for the creation of PhD Programmes by registered institutions”).
For the Academic Years 2022/2024, the following SPECIALIZED COURSES of Computer Science are offered:
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GiS methods and technologies for satellite image analysis (16 hours)
(2 CFU, 16 hours, course period March 2023) Teacher: Prof. Hanna Yailymova (academic visiting)
(scheduled lessons on the chart below)
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Human-Centred Computing: Interaction and Cooperation in Ubiquitous Environments (24 hours)
(3 CFU, 24 hours, october 2022) Teacher prof. Tom Gross ((academic visiting)
(scheduled lessons on the chart below)
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Big Data, Data mining, machine learning (32 hours)
1. Machine Learning settings for big data analytics (3 cfu – 24 hours, March-June 2023) Teachers: Gionvito Pio, Paolo Mignone
2. Learning from streaming big data (1 cfu -8 hours, March-June 2023) Teacher: Michelangelo Ceci
(scheduled lessons on the chart below)
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Human-Centered AI (HCAI): an innovative vision for designing intelligent systems (24 hours)
(3 CFU, 24 hours, course period July 2023/September 2023), Teachers: Prof. Rosa Lanzilotti (1 CFU), Prof. Berardina De Carolis (1 CFU), Prof. Giuseppe Desolda (1 CFU)
- Software Solutions for Reproducible Experiments
(2 CFU, 16 hours), Teacher: Prof. Fabio Calefato
(scheduled lessons on the chart below)
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Emotion recognition using non-invasive biometrics (16 hours)
(16 hours, SSD: INF/01, 2 CFU, March 2023, Teacher: Nicole Novielli)
(scheduled lessons on the chart below)
- Deep Learning for Content Representation in Recommender Systems
(3 CFU, 24 hours), Teacher: Dr. Marco Polignano, Prof. Cataldo Musto
(scheduled lessons on the chart below)
- Natural Language Processing for Information Extraction (24 hours)
(3 CFU, 24 hours, course period Feb. 2024), Teachers: Prof. Siciliani, Prof. Basile
- Advanced AI for predictive tasks
(3 CFU, 24 hours, course period to be announced), Teachers: to be announced
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Methods for describing visualization techniques, complex visualization pipelines and chained visualizations (23 hours)
(2 CFU, 23 hours, course period November 2023) Teacher: Prof. Marco Winckler (academic visiting)
(scheduled lessons on the chart below)
For the Academic Years 2022/2024, the following SPECIALIZED COURSES of Mathematics are offered:
- Joint numerical and spectral radii for tuples of operators – a non-commutative probability approach
(2 CFU, 16 hours, course period Nov-Dec 2022), Teacher: Janusz Wysoczanski (academic visiting)
(scheduled lessons on the chart below)
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Fourier analysis and its applications
(2 CFU, 16 hours, course period first part: Dec 2022, course period second part: Jan 2022), Teachers: Marcelo Rempel Hebert (academic visiting), Marcello D'Abbicco, Alessandro Palmieri
(scheduled lessons on the chart below)
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Control of Degenerate and Singular Parabolic Equations (16 hours)
(2 CFU, 16 hours Period: June-July 2022) Teacher: Genni Fragnelli
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Prescribed curvature problems and Liouville equations (16 hours)
(2 CFU, SSD: MAT/05, course period: March-April 2023) Teacher: Gabriele Mancini
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Geometric structures on varieties - Dirac operators: euclidean and manifold cases (16 hours)
(2 CFU, period: March-April 2023) Teachers: Amedeo Altavilla, Sara Azzali
(scheduled lessons on the chart below)
- Large Deviation Theory and Applications (16 hours)
(2 CFU, 16 hours, SSD MAT/07, course period November 2022), Teacher: Marco Zamparo
(scheduled lessons on the chart below)
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An Introduction to the Virtual Element Method with focus on the Navier-Stokes Equation (16 hours)
(2 CFU, 16 hours, SSD MAT/08, course period:October-November 2023), Teacher: Giuseppe Vacca
(scheduled lessons on the chart below)
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Polynomial identities and interactions with quantum groups (24 hours)
(3 CFU, 24 hours, course period: March-April 2023), Teacher: Lucio Centrone
1. Theories in STEM Education (2 CFU, 16 ore), Teacher: A. Montone e M.G. Fiorentino
2. Research Methods in STEM Education. (2 CFU, 16 ore, MAT/04, docenti E. Faggiano e R. Capone)
- Random matrix theory (24 hours)(3 CFU, 24 hours, course period March-April 2023), Teacher: Fabio Deelan Cunden
(scheduled lessons on the chart below)
- Stability of wave equation in one and multidimensional cases with and without geometric control conditions (8 hours)
(1 CFU, 8 hours, course period March 2024), Teacher: Mohammad Akil (academic visiting)
(scheduled lessons on the chart below)