23 November 2022 - 23 November 2022

As a servo control engineer, who entered robotics control field afterwards, I found that there is a discrepancy between servo control and robot control. This talk is about this discrepancy between them, and also about how the servo control methodologies can be applied to the robot control. Model-based control using Disturbance Observer (DOB) has been a very powerful tool in the servo control, and this talk introduces how this DOB techniques can be applied to robot control. Force control including Series Elastic Actuators as well as force sensor feedback is one of the main application of this approach.
East Campus USI-SUPSI - Room A1.02 15h00

23 November 2022 - 23 November 2022

“All models are wrong, but some are useful”, I clearly remember the moment when I first heard this well-known aphorism by George Box stepping into the Faculty of Statistical Sciences at the Sapienza University of Rome in 1993. It became a sort of mantra, and my challenge became to prove it wrong: some models “must be” correct and give – as a map – a reliable idea of the territory although they cannot represent every single detail. During this talk I will show my successes and inevitably my failures in many statistical collaborations and projects that I have accumulated since then: in particular, I will present an overview of some of my activities around statistical methods and applications in randomized clinical trials, observational studies and my view that no perfect analysis and/or modelling approach can rescue a badly designed study. I will also discuss about the current infodemic of systematic (and unfortunately not so systematic) reviews and meta-analyses and how the Bayesian approach to this type of apparently simple and low-dimensional datasets can avoid misleading medical conclusions. Lastly, emphasis will be given to the multidisciplinarity of Health Technology Assessment and how the evidence-generation loop to inform medical intervention’ evaluations is a natural fit to the Bayesian paradigm that today’s posterior is tomorrow’s prior.
Room C2.09, 2nd floor Sector C, East Campus USI-SUPSI

17 November 2022

The EU MCSA VIRTUOUS project aims to create a virtual tongue through an integrated computational framework able to screen food for natural ligands targeting taste receptors. VIRTUOUS integrates drug discovery techniques, big-data and machine learning algorithms to predict the organoleptic profile of Mediterranean ingredients based on their chemical composition. Recent developments in the VIRTUOUS project will be presented in the workshop, ranging from new algorithms for advanced modelling simulation, machine learning tools to identify the most relevant descriptors affecting compounds’ taste, and standardized procedures for sensory analysis of virgin olive oils. New results on application of artificial intelligence for quality assessment of extra-virgin olive oil from fluorescence spectrum will be shown. Finally, a first DEMO of the Virtuous platform will be presented
East Campus USI-SUPSI - Room C1.02

13 October 2022 - 13 October 2022

Atmospheric Science commonly deals with complex spatiotemporal fields. Methods based on deep learning (DL), such as convolutional neural networks, have turned out to be powerful tools for analyzing such data. However, predictive DL models are typically trained to optimize loss functions such as the root-mean-square error, which leads to blurry predictions and does not give a quantitative estimate of the uncertainty of the prediction, whose importance is particularly emphasized in the weather and climate fields. Alternatively, probabilistic losses such as cross entropy can produce pointwise uncertainties, but still fail to represent the spatial correlations in the uncertainty. Generative models are able to produce diverse, realistic samples. This makes them – and especially their conditional variants – well suited for representing uncertainty through sample diversity. In the recent years, generative adversarial networks (GANs), have found applications in weather and climate data processing. They can be used for common problems in this field, such as generating physical fields from the corresponding in-situ and remote sensing observations, increasing the resolution of observed data, or predicting the time evolution of data fields. In this presentation, I will give an overview on the applications of generative models in the atmospheric science, with an emphasis on my own work in processing cloud and precipitation observations with them. I will also discuss more generally which problems in climate science could (or already do) benefit from generative models. Furthermore, I will discuss the current challenges and open questions for training generative models for weather and climate applications, and in validating and interpreting their results.
Room B1.14 - East Campus - Lugano

7 October 2022 - 7 October 2022

PH curves are parametric polynomial curves for which the norm of the first derivative is still a polynomial. Introduced by Farouki and Sakkalis in 1990, they found several applications in manufacturing, numerical control machines and robotics. Here we consider their exponential counterparts, based on exponential polynomials, in order to expand the design options for this class of curves. The construction of EPH curves revolves on quaternions with exponential polynomial coefficients, while their evaluation presents some numerical issues which are addressed by the new algorithm proposed.
East Campus USI-SUPSI, Lugano

16 September 2022 - 16 September 2022

We revisit the laser model with cavity loss modulation, from which evidence of chaos and generalized multistability was discovered in 1982 [1]. Multistability refers to the coexistence of two or more attractors in nonlinear dynamical systems. Despite its relative simplicity, the adopted model shows us how the multistability depends on the dissipation of the system. The model is then tested under the action of a secondary sinusoidal perturbation, which can remove bistability when a suitable relative phase is chosen [2]. Such a control strategy is universally known as “phase control” and it was first implemented in the same physical system but at different resonance frequencies [3]. The potential of this control technique has been validated on other paradigmatic chaotic systems such as the Duffing oscillator. In this particular case, it has been verified that the control is more sensitive when applied to the cubic term of the nonlinearity [4]. We recently demonstrated that phase control, which is classified as a nonfeedback method, can be converted to a closed loop control (feedback method) when a suitable adaptive filter is used on the chaotic signal to be processed [5].
East Campus USI-SUPSI - 11:30-12:30

2 September 2022 - 2 September 2022

For centuries mathematics has been an activity carried out by humans for humans. In recent years, a new perspective has arisen, in which mathematics is an activity that humans and machines perform for humans and machines. In the seminar, we exploit this duality within Computer Aided Geometric Design (CAGD) and deep learning frameworks. We consider the problem of constructing spline models starting from data observations and their necessary parameterization. This latter step, namely computing the parametric values associated with each observation, highly affects the shape and accuracy of the final spline model. In particular, we propose a data-driven parameterization based on convolutional neural networks which take in input the relative distances of a variable number of data points and return a suitable parameterization of randomly measured points. We show, with numerical examples, that the proposed scheme leads to improve the spline model accuracy, it is flexible with respect to the input data dimension and can generalize with respect to different kinds of data.
East Campus USI-SUPSI Room D1.13 14:30-16:00

29 August 2022 - 29 August 2022

IDSIA is pleased to organise a mini-workshop on the very relevant topic of explainable AI and scientific understanding which will see the participation of Dr Florian J Bone and Dr Emanuele Ratti.
Room D1.06, Sector D, first floor, Campus Est, USI-SUPSI, Lugano-Viganello

13 June 2022 - 17 June 2022

The innovative training network (ITN) on "learninG, pRocessing, And oPtimising shapES" (GRAPES), funded by the EU's Horizon 2020 research and innovation programme, with 17 partners from all over Europe, will come to Lugano for its second doctoral school, hosted by the Faculty of Informatics and organized by Prof. Hormann. Keynote speakers from all over the world will come to USI's Campus Est to participate in the second GRAPES doctoral school. The thematic focus of the event is on Computer-Aided Design in its broadest sense, covering the historical development of the field, latest research results, applications, and the relevance for industry.
East Campus - Room D1.14

1 June 2022 - 4 June 2022

In memory of the Federal Councillor Stefano Franscini, a native ofTicino, the Congressi Stefano Franscini (CSF), hosted at Monte Verità in Ascona, provide a meeting platform for scientific exchange. Prof. Hormann is organizing an international CSF workshop on the interdisciplinary topic of generalized barycentric coordinates. From June 1 to June 4, researchers from all over the world will flock to the Monte Verità to discuss the latest discoveries in the theoryof generalized barycentric coordinates and their applications in computer graphics and computational mechanics.
Congressi Stefano Franscini, Monte Verità, Ascona

18 May 2022

On Wednesday 18 May, the prize-giving ceremony of the Wiki-Science Competition 2021 will take place in the Auditorium of the West Campus of Università della Svizzera italiana (USI). A report by the Dalle Molle Institute for Artificial Intelligence USI-SUPSI won the "Image sets" section.
Auditorium West Campus - USI

9 May 2022 - 18 May 2022

AIDD is a European Project which aims at training and preparing a new generation of scientists who have skills both in machine learning and in chemistry and can advance medicinal chemistry. In this context IDSIA USI-SUPSI is proud to host and co-organise the first Summer School on advanced Machine Learning for Drug Discovery.
East Campus USI-SUPSI, Lugano-Viganello

5 May 2022 - 6 May 2022

From May 4th to 6th, the Dalle Molle Institute for Artificial Intelligence (IDSIA), will host at the East Campus of Lugano-Viganello the annual meeting of the European COST action INNOGLY, a European research action aimed at creating research networks to develop knowledge on the function of glycans in different biological contexts.
East Campus, Lugano - Viganello

29 April 2022

In the past few years, Reinforcement Learning (RL) has achieved significant breakthroughs and its intersection with practical applications has become more and more relevant.
East Campus USI-SUPSI, Lugano

30 March 2022

Understanding mental illnesses requires looking at a variety of different factors contributing to the development, persistence, and treatment of mental illness. That is, scientists must take into account the role of, e.g., behavioral, psychological, neurophysiological, genetic, pharmacological and environmental influences on psychopathology. To integrate real-world data regarding such varied factors, complex computational models have been raising high hopes. In this talk, I shall examine the vices and virtues of recent multiplex approaches for grasping psychopathology.
Room D1.06, Sector D, first floor, Campus Est, USI-SUPSI, Lugano-Viganello

3 March 2022

AI is growing to play an increasingly important role in the decision environments of human agents. One of the key challenges here is AI influence - an aspect that seems largely unaddressed in current debates around AI Ethics. In this talk, I aim to shed some light on the notion of AI influence and the problems that surround it. In the first part of this talk, I will outline what exactly I mean by AI influence. For this, I will introduce what I call the objectivity-fallacy, and will differentiate between cases of intended and unintended AI influence. The second part of this talk will then focus on the ethical implications of unintended AI influence. I hope to emphasise an important change in the power dynamics in human-AI interaction, and will outline how unintended AI influence changes the roles and thereto related responsibilities in human-AI interaction.
Room B1.12, Sector B, first floor, Campus Est, USI-SUPSI, Lugano-Viganello