In order to achieve more competitive advantages and enhance their innovation capacity, SMEs and Industries can have access to the following internal laboratories and facilities:



SISSA MathLab is a laboratory for mathematical modeling and scientific computing devoted to the interactions between mathematics and its applications, powered by the interest in problems coming from the real world, from industrial applications and from complex systems. A proven value partner for companies interested in mathematics as a tool for innovation offering a research team that focus on new trend in computational mechanics and numerical analysis.

Referent: Prof. Gianluigi Rozza

  • A team of scientists pursuing frontier research, while expanding the opportunities for a dialogue across academic and disciplinary boundaries.
  • A partner for companies interested in mathematics as a tool for innovation.
  • A research team focusing on new trend in computational mechanics and numerical analysis.
  • An integrated group in SISSA Mathematics Area, within the SISSA Phd Program In Mathematical Analysis, Modelling and Application and the SISSA-ICTP Master in High Performance Computing, as well as the master degree programme in mathematics offered by SISSA with University of Trieste, and in the master degree programme in data science and scientific computing offered by University of Trieste, Udine and SISSA.
  • SISSA Mathlab is in Digital Twin Live Demo of SMACT competence center, as well as in the coordination of Spoke 9 of iNEST.

The brochure providing an overview of the SISSA mathLab activities is available at:


Theoretical and Scientific Data Science Group

The group focuses on machine learning methodologies to understand biology and disease; theories of learning artificial and biological neural networks; custom-made machine learning solutions from the cutting-edge in the field as well as development of beyond-the-state-of-the-art methods to deal with the hardest, most intractable problems; statistical tools to tackle any data-driven statistical problem, from inference to optimization, from model comparison to anomaly detection.

The Theoretical and Scientific Data Science group (TSDS) is part of the Physics Area at the International School for Advanced Studies (SISSA) in Trieste, Italy. Thanks to the hiring of new permanent staff and by acting as a focal point for the existing data science expertise within the School, the TSDS group has created a new, major research line within SISSA and added a brand new doctoral training programme. Their aim is to develop an internationally renowned pole of excellence in Data Science for the Natural Sciences, focusing on both theoretical aspects and application to scientific problems of data science, machine learning and AI. 

The group includes a cross-disciplinary mix of experts in machine learning, neural networks, deep learning, dimensional reduction, and Bayesian inference. Their mission is:

  • To deliver enduring excellence in fundamental and applied data intensive science research, fostering interdisciplinary collaborations with local, national and international research centres.
  • To deliver world-class, research-led, student-centred education in Data Science at postgraduate level.
  • To collaborate with local, regional and national industrial and business partners to deliver cutting-edge data science training and translation of research insights into commercial, business and societal applications.
  • To work with the wider community in Trieste and in the Friuli Venezia Giulia region to foster public engagement with Data Science and Artificial Intelligence research and its applications to society.

Referents: Prof. Alessandro Laio | Prof. Guido Sanguinetti | Prof. Roberto Trotta

The TSDS Group is formed by different Research Units:

Theory of Neural Networks - referent prof. Sebastian Goldt. The goal of his group is to develop theories of learning artificial and biological neural networks. Its current focus is understanding how the interplay of data structure, learning rule and architecture shapes the representations that neural networks learn from their inputs. Its approach combines analytical tools from statistical physics and high-dimensional statistics with simulations.

AstroML - referent. prof. Roberto Trotta. Their work is at the interface between cosmology, machine learning and statistics, focusing on developing and applying new Bayesian and machine learning methods to large and complex data sets from cosmology and astrophysics.

Machine Learning and Systems Biology - referent prof. Guido Sanguinetti. Their main interests are in statistical modelling of biomedical data, with particular reference to Bayesian methodologies to interrogate sparse, high-dimensional data sets emerging from next generation sequencing experiments. 


Laboratory of Prion Biology

The focus of the Prion Biology Laboratory is studying prion diseases, rare and fatal neurodegenerative maladies that affect humans and animals for which there is no diagnostic tool, nor a cure. The main research lines of the lab are: 

Theranostics: Several classes of amyloid-directed compounds have been shown to inhibit a-synuclein (a-syn) aggregation and been investigated as potential new drugs, despite this, not a single molecule has reached the market.

Transcriptomics: The underlying conversion mechanism of PrPC into PrPSc is poorly understood and it is further complicated by the existence of several different strains characterized by distinct tertiary and quaternary structures as well as different clinical patterns.

Prion-like Diseases: In recent years a growing number of scientific studies has demonstrated that there is a common role for prions in neurodegenerative pathology.

Structural Biology of Prion Protein: A prerequisite for understanding Prion Diseases is unraveling the molecular mechanism leading to the detrimental conversion process wherein the α-helical motifs of the cellular prion protein (PrPC) are replaced by β-sheets in the disease-causing form (PrPSc).

Prion Protein Function: The cellular prion protein (PrPC) has been extensively investigated since its conformational isoform, the prion, was identified as the causative agent of prion disorders.

Referent: Prof. Giuseppe Legname


Molecular and Statistical Biophysics Group 

The activities of the Molecular and Statistical Biophysics Group (SBP) are focused on the development and application of theoretical and computational approaches to characterize the properties of biomolecular systems. Specifically, most of the research activity is devoted to characterize the kinetics, thermodynamics and mechanics of proteins and nucleic acids and to seek quantitative comparison with experimental data. Our main goals are: (i) addressing relevant problems in biological physics posed by the unprecedented wealth of detailed experimental data that is nowadays available and (ii) allowing for the most stringent validation of the methods and models that we develop to extend the current reach of computational studies of biomolecules. For both these aspects, the expertise gathered within the SBP group is broad and ranges from detailed quantum-mechanical calculations and hybrid quantum-classical (QM/MM) simulations applied to enzymatic reactions and metal containing drugs, to classical atomistic molecular dynamics simulations and advanced sampling techniques of proteins, to coarse-grained modelling of protein assemblies and large macromolecular systems such as long DNA filaments. The activity in these areas is very tightly integrated and hence offers a comprehensive multiscale expertise that is uncommon in a single department in Europe, and is probably unique in Italy.

Focused on the development and application of theoretical and computational approaches to characterize the properties of biomolecular systems. Most of the research activity is devoted to characterize the kinetics, thermodynamics and mechanics of proteins and nucleic acids and to seek quantitative comparison with experimental data. Its main goals are:  
(i) addressing relevant problems in biological physics posed by the unprecedented wealth of detailed experimental data that is nowadays available and  
(ii) allowing for the most stringent validation of the methods and models that we develop to extend the current reach of computational studies of biomolecules.

Referents: Prof. Alessandro Laio | Prof. Guido Sanguinetti | Prof. Giovanni Bussi | Prof. Cristian Micheletti


Laboratory of Computational Genomics

The Computational Genomic Lab focuses in particular on the development and usage of bioinformatics pipelines, data integration and harmonization, tools, methods and databases for large-scale functional genomics data analysis.

The Computational Genomics Lab is composed of biologists and computer scientists who combine molecular biology and functional genomics with the development and analysis of bioinformatics pipelines.

The laboratory studies the organization of the genome, its transcriptional output, the activity and evolution of non-coding DNA and transposons (also called junk DNA). The focus relies on how these features shape the genomes of living organisms and are involved in the establishment of diseases and illnesses, with a strong focus on health, the nervous system and somatic variations.

The laboratory specifically develops bioinformatics pipelines able to analyze a large number of data produced by functional genomics platforms in particular sequencing machines of the latest generations.

Thanks to this expertise the laboratory can analyze the sequence of the genome of any individual and can also identify variations determined by junk DNA at different stages of life and their relation to the responses of our genes to environmental and life-style change.

Referent: Prof. Remo Sanges is the coordinator of the laboratory is a molecular and computational biologist with extensive experience in development and usage of bioinformatics pipelines, data integration and harmonization, tools, methods and databases for large-scale functional genomics data analysis and more than 15 years of teaching experience.

The laboratory has developed different bioinformatics pipelines to analyze sequencing data, annotate genomic regions, finding gene clusters, mining and annotating de-novo generated transcriptomes. These tools are widely used by the community and regularly cited.

The latest developments regard the identification and prioritization of mutations/variations potentially associated to specific diseases and phenotypes. The computation genomic lab's pipeline, differently from other standard ones, is capable to identify also mutation generated by the activity of junk DNA (transposable elements) and uses ad-hoc developed prioritization modules capable to increase the rate of annotation and identification of potentially causative variants. This expertise allows to profile DNA being capable to analyze also all those regions of the human genome which have not been considered so far (non-coding and transposons) and that can contain important information also potentially related to the variability of the response of a patient to a given drug.


Laboratory of Neuronal Dynamics

SISSA Laboratory of Neuronal Dynamics focuses on quantifying information processing and the response properties of cortical neurons, investigating the impact of synaptic "noise" and ion channels "noise", developing mathematical models of neurons and neuronal networks and investigating heterogeneities in human and rodent cortical microcircuits. Its main point of interest is electrophysiology of nerve cells, microcircuits and networks, which compose the mammalian cortex. The research focuses also on information representation and processing in nerve cells, and we work towards dissecting the biophysical primitives underlying computation. Ultimately, SISSA Laboratory of Neuronal Dynamics aims at understanding, repairing, replacing, and enhancing of the electrical properties of neural systems.

Referent: Prof. Michele Giugliano 


Neurobiology Group

A combination of molecular, cellular, integrative, and computational methods to investigate the nervous system: the Neurobiology Sector offers a complete research approach to understand the brain mechanisms and functions. Neurobiologists seek to explain the mechanisms that account for behaviour and for cognitive higher functions in terms of sensory signals, integration and motor output.  The SISSA Neurobiology sector faces this challenge with an interdisciplinary approach, combining different research lines and closely working with physicists, mathematicians, nanotechnolgists and biologists.

From single molecules to synaptic plasticity, from sensory systems to advanced imaging techniques: all these fascinating research areas can be investigated in our labs in an original and fruitful way.

Such laboratories offer advanced tools for physiological research, DNA sequence analyzer, and molecular biology instrumentation. This Area also uses advanced computers and software for molecular modeling, and for the study of hybrid bio-electronic devices. Advanced types of software for the study of biology-inspired machine vision are in use. The microscope facilities of the Neurobiology Area are: an electron microscope, two confocal microscopes and numerous fluorescence microscopes. Its studies concerns also nanomaterials (carbon nanotubes and graphene based nanomaterials) applied to neurons.

Research Fields:

  • Olfactory Systems and Ion Channels
  • Applied Neurophysiology and Neuropharmacology
  • Bionanotechnology
  • New Materials and Neurons
  • Phototransduction
  • Structure and Function of Ionic Channels
  • Dynamics of neuronal excitability
  • Information processing and neural computation

Referent: Prof. Paul Alexander Heppenstall


Laboratory of Cerebral Cortex Development 

Centre of excellence interested in molecular mechanisms specifying embryonic cortico-cerebral precursors and regulating their proliferation-differentiation profile. Their work is mainly focussed on a small set of evolutionarily conserved transcription factor genes involved in these processes. They are dissecting their impact on the behaviour of cortico-cerebral neural stem cells and committed progenitors, in normal development and select neurodevelopmental disorders. Moreover they are working at ncRNA-based methodologies, aimed at stimulating transcription of endogenous genes for therapy of haploinsufficiencies. 

The achievement of these goals relies on the integrated employment of a large body of classical and state-of-art technologies. Strong emphasis is placed on creative and critical contibution by young, intellectually independent PhD students, in charge of these projects.

Referent: Prof. Antonello Mallamaci


Laboratory of Evolutionary Neurobiology (Falcone Lab) 

Dr. Carmen Falcone's laboratory is focussed on researching the functions of astrocytes across evolution and the development of the cerebral cortex in mammals. By integrating neurogenomics, bioinformatics and electrophysiology, Dr. Falcone and her team investigate why the primate brain has much more refined functions than other animals, with prticular attention to the role of the interlaminar astrocytes in creating the neural connectivity of the primate cerebral cortex. The research project is one of the few that has been selected by Human Technopole’s initiative Early Career Fellowship Program.

Falcone Lab's current study focuses on interlaminar astrocytes (ILAs), a subset of GFAP+ astrocytes that can be identified in the cerebral cortex by having a soma present in layer I very close to the pia, and long interlaminar processes running into deeper cortical layers. These long processes have been considered to be a predominant feature in the postnatal primate cortex and have been described in many primates and in the lateral cortex of few other mammals (Chiroptera and Scandentia). The Lab is studying ILA evolution, development and functions in the mammalian cerebral cortex, with special emphasis to primates.

Among different types of cortical astrocytes, the interlaminar astrocytes (ILAs) are a subset of Glial fibrillary acidic protein (GFAP)+ astrocytes with singular morphological traits: they can be identified in the cerebral cortex by having a cell body in the most marginal layer of the cerebral cortex (layer I), very close to the pia, and long, interlaminar processes running into deeper cortical layers, reaching layer V in human. All mammals have certain types of ILAs, but what makes them distinctive in primates is a combination of primate-specific features in terms of density, morphology and molecular markers. Primates with exceptional cognitive functions, specifically great apes and human, exhibit ILAs with the highest complexity. These data, together with their peculiar interlaminar morphology support the hypothesis that they contribute to the exceptionality of the primate brain and cognitive abilities through specific, yet-to-be-investigated functions. The goal of the research is to investigate the ILA functions in the primate brain at a molecular, cellular, circuit and behavioral level, with postmortem human brains and chimera mouse models.

In a comparative study of ILAs, Falcone's team have characterised ILAs presence across mammals and have measured their density and morphological properties across evolution. It has been found that ILAs are present in all mammals: rudimentary (with processes not exitying layer I), or typical (with processes crossing layer I-II boundary), but they are more numerous and more morphologically complex in primates. As their processes contact blood vessels and neurites, this work also suggests a potential role for ILAs in blood brain barrier and in the communication among different brain cell types, meninges and cerebrospinal fluids.

The central nervous system shows an incredible diversity across evolution at anatomical, cellular, molecular, and functional levels. Over the years, neuronal cell number and heterogeneity have been rigorously investigated in comparative neuroscience studies. However, astrocytes play pivotal roles in the central nervous system, such as regulating water and ion homeostasis, exchanging nutrients across the blood-brain barrier, and regulating synapse development and function.


Laboratory of Neurogenetics 

The laboratory of Neurogenetics is using Drosophila melanogaster as a model organism to investigate the genetics and the molecular mechanisms underlying differentiation, circuit formation and neuron-glia interaction during brain development and in nervous system diseases. Among other molecular mechanisms, the Neurogenetics lab also focuses on the involvement of epitranscriptomic modifications in these processes.

Referent: Prof. Alessia Soldano


Neural Computation Laboratory  

This Lab is interested in the computational principles that underlie the ability of the animal brain to perform efficient inference and prediction under tight resource constraints:
• study behavior and cognition in animals and humans, and information processing in neuronal circuits; 
• develop and employ techniques that draw from a broad range of approaches, including statistical learning, information theory, artificial neural networks, and Bayesian statisticss.

Referent: Prof. Eugenio Piasini


Cognitive Neuroscience Laboratories

Such laboratories include test cabins for psycholinguistic experiments with adults and children using sophisticated artificial speech; a virtual theatre for presenting visual scenes to test reasoning processes in children; high-density evoked potential recording to carry out neuroimaging on children and adults; a neuropsychology laboratory equipped for transcranical magnetic stimulation. Other methodological highpoints include the tactile perception laboratory, which examines the neuronal basis of sensation using a 100-microelectrode matrix implanted in cerebral cortex; this group also monitors neuronal activity underlying perceptual decisions in behaving animals.

Facilities for research with human participants at SISSA span virtually all state-of-the-art techniques in the field. We have a number of behavioural testing booths, including some specifically designed for ms-accurate display of visual stimuli. We host three different eye tracking systems, including one with high precision in space and time (EyeLink 1000+); two Biosemi EEG systems, allowing up to 128-channel recording; a neuronavigation-guided TMS system, allowing single and double pulse stimulation; a Biopac system for Electromyography. We have an olfactometermovement tracking systems, and a mirror stereoscope. Our department has access to 3T fMRI at the Santa Maria della Misericordia Hospital in Udine, entirely maintained by School funds. 

Animal research also takes advantage of unique facilities and equipment. The Tactile Perception and Learning Lab houses state-of-the-art facilities for behavioral neurophysiology. These include 3 complete Tucker-Davis Technologies recording systems for multi-electrode array recordings from animals carrying out sensory-perceptual tasks. A set of 6 booths, endowed with acoustical, visual, vibrational and electromagnetic shielding, each hosts a fully mechanized setup.  The setups are computer-controlled through custom LabVIEW software together with both visible and infrared high-speed video recordings and tracking algorithms. An optogenetics line of research with novel physiological/optic integration has been recently initiated, opening the way to merging classical electrode-based techniques with optical excitation and inhibition in behaving rats. The Visual Neuroscience Lab features multiple scalable rack-mounted setups available for parallel training of batches of behaving animals in visual-based tasks. Each rack contains a Multi Channel Systems neural digital wireless recording system for free-moving subjects, as well as a wired Tucker-Davis traditional system. Novel arenas equipped with virtual reality displays allow studies in both real and virtual 3D custom-designed environments. Large computer controlled displays are available as active stimuli for acute surgery experiments. Advanced online video tracking methods have been internally developed and are available for both 2D and 3D tracking of the animal subject position and head movement. Animals of the Tactile Perception and Learning Laboratory and the Visual Neuroscience Laboratory are quartered in enriched, climate-controlled environments.

The Mechatronics Lab is a shared workshop facility equipped with a high resolution 3D-System plastic photolithographic printer, a laser cutter machine, a 4-axis CNC milling machine, a lathe, a column driller and other mechanical tools. Laboratory technicians are expert in electronics, mechanics, CAD, drawing, software, mathematics, engineering and animal handling. To broaden the training of young investigators, Mechatronics offers technical courses during the academic year. The Laboratory can also facilitate contacts between industry and research to nurture the transfer of technologies developed in Neuroscience.

Finally, SISSA hosts facilities outside the Cognitive Neuroscience program for histologymolecular biology, and microscopy.

Referent: Prof. Mathew E. Diamond


High Performing Computing Laboratory

SISSA (with ICTP) host one of the largest HPC facilities in Italy, a cluster with more than 4000 cores based on the newest technology. This allows scientists, SMEs and Industries to gain direct experience in a production environment and to explore characteristics and configurations of an HPC cluster. The HPC system also provides a number of nodes with accelerators explicitly dedicated to advanced research and industry projects. The in-house facilities are complemented by state-of-the-art facilities available world wide to computational research groups involved with the Master in Hight Performing Computing (MHPC). Experimental HPC facilities are also available trough european research program which involves local scientific research institution and companies.

Since 2014, when the first edition of MHPC started, SISSA and ICTP host a large HPC facility recently extended thanks to a generous funding from the FVG Regional Government. The supercomputer Ulysses is available to MHPC students as an experimental facility.

Advanced techniques and methods of high performance scientific computingreduced models (reduced bases); isogeometric analysisfinite element methodsfinite spectral volumesfinite differencesparameterization and decomposition of calculation domains.

The research concerning scientific computing, thanks to the decomposition of the calculation procedures (offline and online) allows to export the scientific calculation and the simulation in contexts and contexts in which this strand is not yet developed and widespread (eg small and medium enterprises , hospitals), reality often far from access to super-computers or clusters. The export of scientific calculus in new contexts (coupling high performance and reduced models) also allows to integrate mathematical and numerical models with experimental and statistical data, improving the reliability of the models and of the simulated results.

Referents: Prof. Gianluigi Rozza