Prof. Daniel Gianola - Programs of seminars and courses
Prof. Daniel Gianola (University of Wisconsin-Madison, USA; see his CV) will be Visiting Professor at DAFNAE for 3 months thanks to fundings provided by Fondazione Cassa di Risparmio di Padova e Rovigo (http://www.fondazionecariparo.net).
During his staying in DAFNAE, Prof. Gianola will give a series of seminars (in collaboration with Scuola Galileiana) and course focused on biostatistical methods applied to genetics.
Seminars (announcements available below for download)
- Wednesday 7th June 2017 - 5.30pm - Aula Magna at Collegio Morgagni (via San Massimo 33, Padova) - 'Application of kernel methods and neural networks in quantitative genetics'
- Wednesday 21st June 2017 - 5.30pm - Aula Magna at Collegio Morgagni (via San Massimo 33, Padova) - 'Enhancing and evaluating prediction machines using resampling: applications to animal and plant breeding'
Courses and labs (timetable in progress; syllabi are available below for download)
- From 26th to 30th June 2017- Room 14 at Pentagono building - 'An introduction to Bayesian methods for scientists' | Lectures from 10:00 to 12:30 | Lunch from 12:30 to 14:00 | Lectured/labs from 14:00 to 15:30.
- From 3rd to 7th July 2017 - Room 14 at Pentagono building - 'Prediction of complex traits' | Lectures from 9:30 to 13:00 | Lunch from 13:00 to 14:30 | Labs from 14:30 to 16:30.
- Labs with Prof. Gustavo de los Campos (see syllabus attached)
Registration
The courses of Prof. D. Gianola have reached the maximum number of attendants.
Information - Contacts
For further information and details, please contact Prof. Alessio Cecchinato (alessio.cecchinato@unipd.it | Mobile +39 3346958501).
Supported by: | In collaboration with: |
Attachments
- "Application of kernel methods and neural networks in quantitative genetics" | Download Announcement (.PDF)
- "Enhancing and evaluating prediction machines using resampling: applications to animal and plant breeding" | Download Announcement (.PDF)
- "An introduction to Bayesian methods for scientists" - Dal 26 al 30 Giugno 2017 | Download Syllabus (.PDF) | Download Announcement (.PDF)
- "Prediction of complex traits" | Download Syllabus (.PDF) | Download Announcement (.PDF)
- Labs | Download Syllabus (.PDF)