Teaching

My teaching is student-oriented: I believe that interactive learning is the best and most effective way of assimilating new knowledge and how to put it in practice. This is the underlying ethos of all my teaching, from undergraduate to advanced postgraduate level. All my courses now involve some form of “active learning” and interactive teaching, and they are increasingly blended with online material, quizzes and forums.

Apart from postgraduate courses in machine learning and Bayesian inference at SISSA, I also co-teach a course on “Journalism and AI” on the SISSA Master in Science Communication. 

Teaching Awards

• Imperial College London President’s Award for Excellence in Teaching 2016:
  “Dr Trotta’s innovative and enthusiastic way of teaching as well as readiness to improve and adapt his teaching methods to suit the students make him stand out, and his exceptional ability to communicate his expertise in cosmology in an engaging and accessible manner has been an inspiration to many”
• Imperial College London Faculty of Natural Sciences Prize for Excellence in Teaching 2016:
  “Roberto receives this prize for providing an inspirational introduction to cosmology and astroparticle physics to third year physics students and for the innovative use of modern technology to encourage student interaction in lectures.”
• International Astrostatistics Association Elected Fellow (June 2016):
  “For his contributions to the International Astrostatistics Association as a member of its founding Council; for his efforts to bring astronomy and understanding of data to the general public; and for his efforts in advancing the statistical education among astronomers” 

PhD Programme in Theoretical and Scientific Data Science

Starting in the academic year 2021-22, I am the course director of a a new PhD programme in Data Science at SISSA.

For 2022-23, I am teaching the following postgraduate modules at SISSA:

• Lecturer: Bayesian Inference II (24 hours + labs): Foundations of Bayesianism; Priors selection; Advanced sampling methods; Bayesian model comparison; Simulation-based inference
• Module leader: Ethics in Machine Learning and AI
• Monographic course: Topics in advanced Bayesian methods
• Masters in Science Communication: Giornalismo ed AI (con Elisabetta Tola)

Student feedback

Really good, please can you make other lecture courses more in this structure, was super helpful and I felt I learnt a lot better.

Best use of the active learning I’ve seen yet from any lecturer!

Dr Trotta is a great lecturer, he and explains stuff very well. You can tell he cares about teaching the module and enjoys it. This made me enjoy the lectures too. I really liked the active learning, the mentimeter questions made me actually think about what was being said in the lectures and understand it better as a whole.

Clearly a man who cares about teaching effectively. At first was sceptical of the extra learning platforms but they are very good for a course like this. Great stuff.

Fantastic use of different media to keep students engaged and practising the content throughout the course, bravo!

You put your heart and soul into this course and your hard work paid off, it was wonderful.

Dr Trotta is clearly extremely passionate about making sure everyone gets the best they can out of the course, which is absolutely wonderful to see from a student’s point of view.

I felt it was fun as well as gaining depth as much as possible in this broad subject.

My favourite lecturer this year!

Faculty of Natural Sciences Excellence in Teaching prize award ceremony 2016

Your professionalism and enthusiasm allowed me to better appreciate modern day developments in the exciting field of cosmology and astrophysics.

Dr Trotta is super enthusiastic and clearly put a lot of effort into this course.

Great enthusiasm! It really does make a difference. Speaking to my friends, it seems that the cosmology component of the course will be pushing quite a few of us to do further work in the field 🙂

Appreciated the dedication to understanding the student viewpoint and general enthusiasm for the course.

Thoroughly enjoyable course – great lecturing!

Loved the mentimeter sessions. Best course of the degree!

Enjoyed the course. I think having weekly quizzes was great, first to make material more familiar and build intuition and second it made me keep up with the course as it went along. I found many mentimeter questions very difficult, but found it useful to be exposed to questions during the lecture.

A big plus for mentimeter and the possibility to ask questions during lectures. One of the few lecturers that were better to come to the classes than watch at home.

This project has been my most enjoyable experience here at Imperial! (3rd BSc Physics project student)

Student Academic Choice Award 2019 nomination:

Without Roberto, Horizons wouldn’t be the fantastic program that it is today. He is very enthusiastic, helpful and considerate all while being a strong leader. He is committed to incorporating the student voice into his decision making, is a key ally to Imperial College Union and an advocate for the best student experience. I have an immense respect for Roberto and his dedication to Horizons and am thankful for the work he has put in to deliver the best possible experience for students.

Past postgraduate courses

Teaching Astrostatistics at an ESAC advanced school – who says statistics can’t be fun?

• Heidelberg GradDays 2021, April 2021
• Astronomy in the Era of Big Data, Saas-Fee, Switzerland, March 2021
• ICIC Data Analysis Postgraduate School, Imperial College London 2018
• Analytics, Inference and Computation in Cosmology: Advanced methods, Cargese, France, 2018
• Astronomical Data Analysis (ADA) IX School, Valencia, Spain, 2018
• School of Statistics for Astrophysics Stat4Astro 2017, France, Oct 2017 
• Graduate School “The Dark and the Visible Universe”, July 2017, Texel, The Netherlands
• First Italian Astrostatistics School, June 12-16th 2017, Milan, Italy
• ESAC Statistics Workshop, October 25th-26th 2016, European Space Astronomy Centre, Villanueva de la Canada, Spain.
• ADA8 Summer School on Astronomical Data Analysis, Chania, Greece, May 21st-23rd.
• 44th Saas Fe Advanced Course, Engelberg, Switzerland, 3-7th March 2014. Video of the lectures available here.
• XII School of Cosmology, Cargèse, 15th-20th Sept 2014.
• ICIC Data Analysis Summer School, Imperial College London, Sept 2014.
• International elite PhD Course, Niels Bohr Institute, Copenhagen, 6-10th Oct 2014.
• XXVI Winter School “Bayesian inference in Astronomy and Astrophysics”, Tenerife, 3-14th Nov 2014.
• School on Bayesian Analysis in Physics and Astronomy, Stellenbosch, South Africa, Nov 2013,Course website
• ICIC Data Analysis Workshop, Imperial College London advanced postgraduate course, Sept 2013 Course website
• Statistical Inference, 3-weeks long postgraduate course at the African Institute for Mathematical Sciences, Cape Town, March 2012 (with Bruce Basset). Course webpage.
• Advanced method in statistical data analysis, elite PhD course in Copenhagen, Nov 14-18th 2011. Slides, problems and handout available here.
• Introduction to cosmology, postgraduate lecture for the High Energy Physics students, Imperial, Nov 2010.
• Advanced statistical methods, postgraduate lectures for PhD students, Imperial Astrophysics, Sept 2010.
• Statistical methods for cosmology, 1st Jayme Tiomno School of Cosmology, Rio de Janeiro, July 2010.
• Probability theory, statistics and data analysis. Postgraduate lectures series, Imperial/UCL, Jan 2009.
• The cosmic microwave background and its statistical interpretation. A series of 3 invited lectures given at Physics Department of Wuerzburg University (Germany) in Dec 2008.
• Introduction to modern cosmology. (Lecture 1) (Lecture 2) Postgraduate lectures series, Imperial/UCL, Oct 2008.
• Advanced Statistical tools for cosmology. (Lecture 1) (Lecture 2) Invited lectures given at the Taller des altas energias, Madrid, UAM, Sept 2008 and in Valencia in May 2009.