Project acronym 321
Project from Cubic To Linear complexity in computational electromagnetics
Researcher (PI) Francesco Paolo ANDRIULLI
Host Institution (HI) POLITECNICO DI TORINO
Call Details Consolidator Grant (CoG), PE7, ERC-2016-COG
Summary Computational Electromagnetics (CEM) is the scientific field at the origin of all new modeling and simulation tools required by the constantly arising design challenges of emerging and future technologies in applied electromagnetics. As in many other technological fields, however, the trend in all emerging technologies in electromagnetic engineering is going towards miniaturized, higher density and multi-scale scenarios. Computationally speaking this translates in the steep increase of the number of degrees of freedom. Given that the design cost (the cost of a multi-right-hand side problem dominated by matrix inversion) can scale as badly as cubically with these degrees of freedom, this fact, as pointed out by many, will sensibly compromise the practical impact of CEM on future and emerging technologies.
For this reason, the CEM scientific community has been looking for years for a FFT-like paradigm shift: a dynamic fast direct solver providing a design cost that would scale only linearly with the degrees of freedom. Such a fast solver is considered today a Holy Grail of the discipline.
The Grand Challenge of 321 will be to tackle this Holy Grail in Computational Electromagnetics by investigating a dynamic Fast Direct Solver for Maxwell Problems that would run in a linear-instead-of-cubic complexity for an arbitrary number and configuration of degrees of freedom.
The failure of all previous attempts will be overcome by a game-changing transformation of the CEM classical problem that will leverage on a recent breakthrough of the PI. Starting from this, the project will investigate an entire new paradigm for impacting algorithms to achieve this grand challenge.
The impact of the FFT’s quadratic-to-linear paradigm shift shows how computational complexity reductions can be groundbreaking on applications. The cubic-to-linear paradigm shift, which the 321 project will aim for, will have such a rupturing impact on electromagnetic science and technology.
Summary
Computational Electromagnetics (CEM) is the scientific field at the origin of all new modeling and simulation tools required by the constantly arising design challenges of emerging and future technologies in applied electromagnetics. As in many other technological fields, however, the trend in all emerging technologies in electromagnetic engineering is going towards miniaturized, higher density and multi-scale scenarios. Computationally speaking this translates in the steep increase of the number of degrees of freedom. Given that the design cost (the cost of a multi-right-hand side problem dominated by matrix inversion) can scale as badly as cubically with these degrees of freedom, this fact, as pointed out by many, will sensibly compromise the practical impact of CEM on future and emerging technologies.
For this reason, the CEM scientific community has been looking for years for a FFT-like paradigm shift: a dynamic fast direct solver providing a design cost that would scale only linearly with the degrees of freedom. Such a fast solver is considered today a Holy Grail of the discipline.
The Grand Challenge of 321 will be to tackle this Holy Grail in Computational Electromagnetics by investigating a dynamic Fast Direct Solver for Maxwell Problems that would run in a linear-instead-of-cubic complexity for an arbitrary number and configuration of degrees of freedom.
The failure of all previous attempts will be overcome by a game-changing transformation of the CEM classical problem that will leverage on a recent breakthrough of the PI. Starting from this, the project will investigate an entire new paradigm for impacting algorithms to achieve this grand challenge.
The impact of the FFT’s quadratic-to-linear paradigm shift shows how computational complexity reductions can be groundbreaking on applications. The cubic-to-linear paradigm shift, which the 321 project will aim for, will have such a rupturing impact on electromagnetic science and technology.
Max ERC Funding
2 000 000 €
Duration
Start date: 2017-09-01, End date: 2022-08-31
Project acronym 3D-nanoMorph
Project Label-free 3D morphological nanoscopy for studying sub-cellular dynamics in live cancer cells with high spatio-temporal resolution
Researcher (PI) Krishna AGARWAL
Host Institution (HI) UNIVERSITETET I TROMSOE - NORGES ARKTISKE UNIVERSITET
Call Details Starting Grant (StG), PE7, ERC-2018-STG
Summary Label-free optical nanoscopy, free from photobleaching and photochemical toxicity of fluorescence labels and yielding 3D morphological resolution of <50 nm, is the future of live cell imaging. 3D-nanoMorph breaks the diffraction barrier and shifts the paradigm in label-free nanoscopy, providing isotropic 3D resolution of <50 nm. To achieve this, 3D-nanoMorph performs non-linear inverse scattering for the first time in nanoscopy and decodes scattering between sub-cellular structures (organelles).
3D-nanoMorph innovatively devises complementary roles of light measurement system and computational nanoscopy algorithm. A novel illumination system and a novel light collection system together enable measurement of only the most relevant intensity component and create a fresh perspective about label-free measurements. A new computational nanoscopy approach employs non-linear inverse scattering. Harnessing non-linear inverse scattering for resolution enhancement in nanoscopy opens new possibilities in label-free 3D nanoscopy.
I will apply 3D-nanoMorph to study organelle degradation (autophagy) in live cancer cells over extended duration with high spatial and temporal resolution, presently limited by the lack of high-resolution label-free 3D morphological nanoscopy. Successful 3D mapping of nanoscale biological process of autophagy will open new avenues for cancer treatment and showcase 3D-nanoMorph for wider applications.
My cross-disciplinary expertise of 14 years spanning inverse problems, electromagnetism, optical microscopy, integrated optics and live cell nanoscopy paves path for successful implementation of 3D-nanoMorph.
Summary
Label-free optical nanoscopy, free from photobleaching and photochemical toxicity of fluorescence labels and yielding 3D morphological resolution of <50 nm, is the future of live cell imaging. 3D-nanoMorph breaks the diffraction barrier and shifts the paradigm in label-free nanoscopy, providing isotropic 3D resolution of <50 nm. To achieve this, 3D-nanoMorph performs non-linear inverse scattering for the first time in nanoscopy and decodes scattering between sub-cellular structures (organelles).
3D-nanoMorph innovatively devises complementary roles of light measurement system and computational nanoscopy algorithm. A novel illumination system and a novel light collection system together enable measurement of only the most relevant intensity component and create a fresh perspective about label-free measurements. A new computational nanoscopy approach employs non-linear inverse scattering. Harnessing non-linear inverse scattering for resolution enhancement in nanoscopy opens new possibilities in label-free 3D nanoscopy.
I will apply 3D-nanoMorph to study organelle degradation (autophagy) in live cancer cells over extended duration with high spatial and temporal resolution, presently limited by the lack of high-resolution label-free 3D morphological nanoscopy. Successful 3D mapping of nanoscale biological process of autophagy will open new avenues for cancer treatment and showcase 3D-nanoMorph for wider applications.
My cross-disciplinary expertise of 14 years spanning inverse problems, electromagnetism, optical microscopy, integrated optics and live cell nanoscopy paves path for successful implementation of 3D-nanoMorph.
Max ERC Funding
1 499 999 €
Duration
Start date: 2019-07-01, End date: 2024-06-30
Project acronym AGNOSTIC
Project Actively Enhanced Cognition based Framework for Design of Complex Systems
Researcher (PI) Björn Ottersten
Host Institution (HI) UNIVERSITE DU LUXEMBOURG
Call Details Advanced Grant (AdG), PE7, ERC-2016-ADG
Summary Parameterized mathematical models have been central to the understanding and design of communication, networking, and radar systems. However, they often lack the ability to model intricate interactions innate in complex systems. On the other hand, data-driven approaches do not need explicit mathematical models for data generation and have a wider applicability at the cost of flexibility. These approaches need labelled data, representing all the facets of the system interaction with the environment. With the aforementioned systems becoming increasingly complex with intricate interactions and operating in dynamic environments, the number of system configurations can be rather large leading to paucity of labelled data. Thus there are emerging networks of systems of critical importance whose cognition is not effectively covered by traditional approaches. AGNOSTIC uses the process of exploration through system probing and exploitation of observed data in an iterative manner drawing upon traditional model-based approaches and data-driven discriminative learning to enhance functionality, performance, and robustness through the notion of active cognition. AGNOSTIC clearly departs from a passive assimilation of data and aims to formalize the exploitation/exploration framework in dynamic environments. The development of this framework in three applications areas is central to AGNOSTIC. The project aims to provide active cognition in radar to learn the environment and other active systems to ensure situational awareness and coexistence; to apply active probing in radio access networks to infer network behaviour towards spectrum sharing and self-configuration; and to learn and adapt to user demand for content distribution in caching networks, drastically improving network efficiency. Although these cognitive systems interact with the environment in very different ways, sufficient abstraction allows cross-fertilization of insights and approaches motivating their joint treatment.
Summary
Parameterized mathematical models have been central to the understanding and design of communication, networking, and radar systems. However, they often lack the ability to model intricate interactions innate in complex systems. On the other hand, data-driven approaches do not need explicit mathematical models for data generation and have a wider applicability at the cost of flexibility. These approaches need labelled data, representing all the facets of the system interaction with the environment. With the aforementioned systems becoming increasingly complex with intricate interactions and operating in dynamic environments, the number of system configurations can be rather large leading to paucity of labelled data. Thus there are emerging networks of systems of critical importance whose cognition is not effectively covered by traditional approaches. AGNOSTIC uses the process of exploration through system probing and exploitation of observed data in an iterative manner drawing upon traditional model-based approaches and data-driven discriminative learning to enhance functionality, performance, and robustness through the notion of active cognition. AGNOSTIC clearly departs from a passive assimilation of data and aims to formalize the exploitation/exploration framework in dynamic environments. The development of this framework in three applications areas is central to AGNOSTIC. The project aims to provide active cognition in radar to learn the environment and other active systems to ensure situational awareness and coexistence; to apply active probing in radio access networks to infer network behaviour towards spectrum sharing and self-configuration; and to learn and adapt to user demand for content distribution in caching networks, drastically improving network efficiency. Although these cognitive systems interact with the environment in very different ways, sufficient abstraction allows cross-fertilization of insights and approaches motivating their joint treatment.
Max ERC Funding
2 499 595 €
Duration
Start date: 2017-10-01, End date: 2022-09-30
Project acronym ANOREP
Project Targeting the reproductive biology of the malaria mosquito Anopheles gambiae: from laboratory studies to field applications
Researcher (PI) Flaminia Catteruccia
Host Institution (HI) UNIVERSITA DEGLI STUDI DI PERUGIA
Call Details Starting Grant (StG), LS2, ERC-2010-StG_20091118
Summary Anopheles gambiae mosquitoes are the major vectors of malaria, a disease with devastating consequences for
human health. Novel methods for controlling the natural vector populations are urgently needed, given the
evolution of insecticide resistance in mosquitoes and the lack of novel insecticidals. Understanding the
processes at the bases of mosquito biology may help to roll back malaria. In this proposal, we will target
mosquito reproduction, a major determinant of the An. gambiae vectorial capacity. This will be achieved at
two levels: (i) fundamental research, to provide a deeper knowledge of the processes regulating reproduction
in this species, and (ii) applied research, to identify novel targets and to develop innovative approaches for
the control of natural populations. We will focus our analysis on three major players of mosquito
reproduction: male accessory glands (MAGs), sperm, and spermatheca, in both laboratory and field settings.
We will then translate this information into the identification of inhibitors of mosquito fertility. The
experimental activities will be divided across three objectives. In Objective 1, we will unravel the role of the
MAGs in shaping mosquito fertility and behaviour, by performing a combination of transcriptional and
functional studies that will reveal the multifaceted activities of these tissues. In Objective 2 we will instead
focus on the identification of the male and female factors responsible for sperm viability and function.
Results obtained in both objectives will be validated in field mosquitoes. In Objective 3, we will perform
screens aimed at the identification of inhibitors of mosquito reproductive success. This study will reveal as
yet unknown molecular mechanisms underlying reproductive success in mosquitoes, considerably increasing
our knowledge beyond the state-of-the-art and critically contributing with innovative tools and ideas to the
fight against malaria.
Summary
Anopheles gambiae mosquitoes are the major vectors of malaria, a disease with devastating consequences for
human health. Novel methods for controlling the natural vector populations are urgently needed, given the
evolution of insecticide resistance in mosquitoes and the lack of novel insecticidals. Understanding the
processes at the bases of mosquito biology may help to roll back malaria. In this proposal, we will target
mosquito reproduction, a major determinant of the An. gambiae vectorial capacity. This will be achieved at
two levels: (i) fundamental research, to provide a deeper knowledge of the processes regulating reproduction
in this species, and (ii) applied research, to identify novel targets and to develop innovative approaches for
the control of natural populations. We will focus our analysis on three major players of mosquito
reproduction: male accessory glands (MAGs), sperm, and spermatheca, in both laboratory and field settings.
We will then translate this information into the identification of inhibitors of mosquito fertility. The
experimental activities will be divided across three objectives. In Objective 1, we will unravel the role of the
MAGs in shaping mosquito fertility and behaviour, by performing a combination of transcriptional and
functional studies that will reveal the multifaceted activities of these tissues. In Objective 2 we will instead
focus on the identification of the male and female factors responsible for sperm viability and function.
Results obtained in both objectives will be validated in field mosquitoes. In Objective 3, we will perform
screens aimed at the identification of inhibitors of mosquito reproductive success. This study will reveal as
yet unknown molecular mechanisms underlying reproductive success in mosquitoes, considerably increasing
our knowledge beyond the state-of-the-art and critically contributing with innovative tools and ideas to the
fight against malaria.
Max ERC Funding
1 500 000 €
Duration
Start date: 2011-01-01, End date: 2015-12-31
Project acronym ARS
Project Autonomous Robotic Surgery
Researcher (PI) Paolo FIORINI
Host Institution (HI) UNIVERSITA DEGLI STUDI DI VERONA
Call Details Advanced Grant (AdG), PE7, ERC-2016-ADG
Summary The goal of the ARS project is the derivation of a unified framework for the autonomous execution of robotic tasks in challenging environments in which accurate performance and safety are of paramount importance. We have chosen surgery as the research scenario because of its importance, its intrinsic challenges, and the presence of three factors that make this project feasible and timely. In fact, we have recently concluded the I-SUR project demonstrating the feasibility of autonomous surgical actions, we have access to the first big data made available to researchers of clinical robotic surgeries, and we will be able to demonstrate the project results on the high performance surgical robot “da Vinci Research Kit”. The impact of autonomous robots on the workforce is a current subject of discussion, but surgical autonomy will be welcome by the medical personnel, e.g. to carry out simple intervention steps, react faster to unexpected events, or monitor the insurgence of fatigue. The framework for autonomous robotic surgery will include five main research objectives. The first will address the analysis of robotic surgery data set to extract action and knowledge models of the intervention. The second objective will focus on planning, which will consist of instantiating the intervention models to a patient specific anatomy. The third objective will address the design of the hybrid controllers for the discrete and continuous parts of the intervention. The fourth research objective will focus on real time reasoning to assess the intervention state and the overall surgical situation. Finally, the last research objective will address the verification, validation and benchmark of the autonomous surgical robotic capabilities. The research results to be achieved by ARS will contribute to paving the way towards enhancing autonomy and operational capabilities of service robots, with the ambitious goal of bridging the gap between robotic and human task execution capability.
Summary
The goal of the ARS project is the derivation of a unified framework for the autonomous execution of robotic tasks in challenging environments in which accurate performance and safety are of paramount importance. We have chosen surgery as the research scenario because of its importance, its intrinsic challenges, and the presence of three factors that make this project feasible and timely. In fact, we have recently concluded the I-SUR project demonstrating the feasibility of autonomous surgical actions, we have access to the first big data made available to researchers of clinical robotic surgeries, and we will be able to demonstrate the project results on the high performance surgical robot “da Vinci Research Kit”. The impact of autonomous robots on the workforce is a current subject of discussion, but surgical autonomy will be welcome by the medical personnel, e.g. to carry out simple intervention steps, react faster to unexpected events, or monitor the insurgence of fatigue. The framework for autonomous robotic surgery will include five main research objectives. The first will address the analysis of robotic surgery data set to extract action and knowledge models of the intervention. The second objective will focus on planning, which will consist of instantiating the intervention models to a patient specific anatomy. The third objective will address the design of the hybrid controllers for the discrete and continuous parts of the intervention. The fourth research objective will focus on real time reasoning to assess the intervention state and the overall surgical situation. Finally, the last research objective will address the verification, validation and benchmark of the autonomous surgical robotic capabilities. The research results to be achieved by ARS will contribute to paving the way towards enhancing autonomy and operational capabilities of service robots, with the ambitious goal of bridging the gap between robotic and human task execution capability.
Max ERC Funding
2 750 000 €
Duration
Start date: 2017-10-01, End date: 2022-09-30
Project acronym BACKUP
Project Unveiling the relationship between brain connectivity and function by integrated photonics
Researcher (PI) Lorenzo PAVESI
Host Institution (HI) UNIVERSITA DEGLI STUDI DI TRENTO
Call Details Advanced Grant (AdG), PE7, ERC-2017-ADG
Summary I will address the fundamental question of which is the role of neuron activity and plasticity in information elaboration and storage in the brain. I, together with an interdisciplinary team, will develop a hybrid neuro-morphic computing platform. Integrated photonic circuits will be interfaced to both electronic circuits and neuronal circuits (in vitro experiments) to emulate brain functions and develop schemes able to supplement (backup) neuronal functions. The photonic network is based on massive reconfigurable matrices of nonlinear nodes formed by microring resonators, which enter in regime of self-pulsing and chaos by positive optical feedback. These networks resemble human brain. I will push this analogy further by interfacing the photonic network with neurons making hybrid network. By using optogenetics, I will control the synaptic strengthen-ing and the neuron activity. Deep learning algorithms will model the biological network functionality, initial-ly within a separate artificial network and, then, in an integrated hybrid artificial-biological network.
My project aims at:
1. Developing a photonic integrated reservoir-computing network (RCN);
2. Developing dynamic memories in photonic integrated circuits using RCN;
3. Developing hybrid interfaces between a neuronal network and a photonic integrated circuit;
4. Developing a hybrid electronic, photonic and biological network that computes jointly;
5. Addressing neuronal network activity by photonic RCN to simulate in vitro memory storage and retrieval;
6. Elaborating the signal from RCN and neuronal circuits in order to cope with plastic changes in pathologi-cal brain conditions such as amnesia and epilepsy.
The long-term vision is that hybrid neuromorphic photonic networks will (a) clarify the way brain thinks, (b) compute beyond von Neumann, and (c) control and supplement specific neuronal functions.
Summary
I will address the fundamental question of which is the role of neuron activity and plasticity in information elaboration and storage in the brain. I, together with an interdisciplinary team, will develop a hybrid neuro-morphic computing platform. Integrated photonic circuits will be interfaced to both electronic circuits and neuronal circuits (in vitro experiments) to emulate brain functions and develop schemes able to supplement (backup) neuronal functions. The photonic network is based on massive reconfigurable matrices of nonlinear nodes formed by microring resonators, which enter in regime of self-pulsing and chaos by positive optical feedback. These networks resemble human brain. I will push this analogy further by interfacing the photonic network with neurons making hybrid network. By using optogenetics, I will control the synaptic strengthen-ing and the neuron activity. Deep learning algorithms will model the biological network functionality, initial-ly within a separate artificial network and, then, in an integrated hybrid artificial-biological network.
My project aims at:
1. Developing a photonic integrated reservoir-computing network (RCN);
2. Developing dynamic memories in photonic integrated circuits using RCN;
3. Developing hybrid interfaces between a neuronal network and a photonic integrated circuit;
4. Developing a hybrid electronic, photonic and biological network that computes jointly;
5. Addressing neuronal network activity by photonic RCN to simulate in vitro memory storage and retrieval;
6. Elaborating the signal from RCN and neuronal circuits in order to cope with plastic changes in pathologi-cal brain conditions such as amnesia and epilepsy.
The long-term vision is that hybrid neuromorphic photonic networks will (a) clarify the way brain thinks, (b) compute beyond von Neumann, and (c) control and supplement specific neuronal functions.
Max ERC Funding
2 499 825 €
Duration
Start date: 2018-11-01, End date: 2023-10-31
Project acronym BrightEyes
Project Multi-Parameter Live-Cell Observation of Biomolecular Processes with Single-Photon Detector Array
Researcher (PI) Giuseppe Vicidomini
Host Institution (HI) FONDAZIONE ISTITUTO ITALIANO DI TECNOLOGIA
Call Details Consolidator Grant (CoG), PE7, ERC-2018-COG
Summary Fluorescence single-molecule (SM) detection techniques have the potential to provide insights into the complex functions, structures and interactions of individual, specifically labelled biomolecules. However, current SM techniques work properly only when the biomolecule is observed in controlled environments, e.g., immobilized on a glass surface. Observation of biomolecular processes in living (multi)cellular environments – which is fundamental for sound biological conclusion – always comes with a price, such as invasiveness, limitations in the accessible information and constraints in the spatial and temporal scales.
The overall objective of the BrightEyes project is to break the above limitations by creating a novel SM approach compatible with the state-of-the-art biomolecule-labelling protocols, able to track a biomolecule deep inside (multi)cellular environments – with temporal resolution in the microsecond scale, and with hundreds of micrometres tracking range – and simultaneously observe its structural changes, its nano- and micro-environments.
Specifically, by exploring a novel single-photon detectors array, the BrightEyes project will implement an optical system, able to continuously (i) track in real-time the biomolecule of interest from which to decode its dynamics and interactions; (ii) measure the nano-environment fluorescence spectroscopy properties, such as lifetime, photon-pair correlation and intensity, from which to extract the biochemical properties of the nano-environment, the structural properties of the biomolecule – via SM-FRET and anti-bunching – and the interactions of the biomolecule with other biomolecular species – via STED-FCS; (iii) visualize the sub-cellular structures within the micro-environment with sub-diffraction spatial resolution – via STED and image scanning microscopy.
This unique paradigm will enable unprecedented studies of biomolecular behaviours, interactions and self-organization at near-physiological conditions.
Summary
Fluorescence single-molecule (SM) detection techniques have the potential to provide insights into the complex functions, structures and interactions of individual, specifically labelled biomolecules. However, current SM techniques work properly only when the biomolecule is observed in controlled environments, e.g., immobilized on a glass surface. Observation of biomolecular processes in living (multi)cellular environments – which is fundamental for sound biological conclusion – always comes with a price, such as invasiveness, limitations in the accessible information and constraints in the spatial and temporal scales.
The overall objective of the BrightEyes project is to break the above limitations by creating a novel SM approach compatible with the state-of-the-art biomolecule-labelling protocols, able to track a biomolecule deep inside (multi)cellular environments – with temporal resolution in the microsecond scale, and with hundreds of micrometres tracking range – and simultaneously observe its structural changes, its nano- and micro-environments.
Specifically, by exploring a novel single-photon detectors array, the BrightEyes project will implement an optical system, able to continuously (i) track in real-time the biomolecule of interest from which to decode its dynamics and interactions; (ii) measure the nano-environment fluorescence spectroscopy properties, such as lifetime, photon-pair correlation and intensity, from which to extract the biochemical properties of the nano-environment, the structural properties of the biomolecule – via SM-FRET and anti-bunching – and the interactions of the biomolecule with other biomolecular species – via STED-FCS; (iii) visualize the sub-cellular structures within the micro-environment with sub-diffraction spatial resolution – via STED and image scanning microscopy.
This unique paradigm will enable unprecedented studies of biomolecular behaviours, interactions and self-organization at near-physiological conditions.
Max ERC Funding
1 861 250 €
Duration
Start date: 2019-09-01, End date: 2024-08-31
Project acronym CAPABLE
Project Composite integrated photonic platform by femtosecond laser micromachining
Researcher (PI) Roberto OSELLAME
Host Institution (HI) CONSIGLIO NAZIONALE DELLE RICERCHE
Call Details Advanced Grant (AdG), PE7, ERC-2016-ADG
Summary The quantum technology revolution promises a transformational impact on the society and economics worldwide. It will enable breakthrough advancements in such diverse fields as secure communications, computing, metrology, and imaging. Quantum photonics, which recently received an incredible boost by the use of integrated optical circuits, is an excellent technological platform to enable such revolution, as it already plays a relevant role in many of the above applications. However, some major technical roadblocks needs to be overcome. Currently, the various components required for a complete quantum photonic system are produced on very different materials by dedicated fabrication technologies, as no single material is able to fulfil all the requirements for single-photon generation, manipulation, storage and detection. This project proposes a new hybrid approach for integrated quantum photonic systems based on femtosecond laser microfabrication (FLM), enabling the innovative miniaturization of various components on different materials, but with a single tool and with very favourable integration capabilities.
This project will mainly focus on two major breakthroughs: the first one will be increasing the complexity achievable in the photonic platform and demonstrating unprecedented quantum computation capability; the second one will be the integration in the platform of multiple single-photon quantum memories and their interconnection.
Achievement of these goals will only be possible by taking full advantage of the unique features of FLM, from the possibility to machine very different materials, to the 3D capabilities in waveguide writing and selective material removal.
The successful demonstration and functional validation of this hybrid, integrated photonic platform will represent a significant leap for photonic microsystems in quantum computing and quantum communications.
Summary
The quantum technology revolution promises a transformational impact on the society and economics worldwide. It will enable breakthrough advancements in such diverse fields as secure communications, computing, metrology, and imaging. Quantum photonics, which recently received an incredible boost by the use of integrated optical circuits, is an excellent technological platform to enable such revolution, as it already plays a relevant role in many of the above applications. However, some major technical roadblocks needs to be overcome. Currently, the various components required for a complete quantum photonic system are produced on very different materials by dedicated fabrication technologies, as no single material is able to fulfil all the requirements for single-photon generation, manipulation, storage and detection. This project proposes a new hybrid approach for integrated quantum photonic systems based on femtosecond laser microfabrication (FLM), enabling the innovative miniaturization of various components on different materials, but with a single tool and with very favourable integration capabilities.
This project will mainly focus on two major breakthroughs: the first one will be increasing the complexity achievable in the photonic platform and demonstrating unprecedented quantum computation capability; the second one will be the integration in the platform of multiple single-photon quantum memories and their interconnection.
Achievement of these goals will only be possible by taking full advantage of the unique features of FLM, from the possibility to machine very different materials, to the 3D capabilities in waveguide writing and selective material removal.
The successful demonstration and functional validation of this hybrid, integrated photonic platform will represent a significant leap for photonic microsystems in quantum computing and quantum communications.
Max ERC Funding
2 381 875 €
Duration
Start date: 2017-10-01, End date: 2022-09-30
Project acronym CellKarma
Project Dissecting the regulatory logic of cell fate reprogramming through integrative and single cell genomics
Researcher (PI) Davide CACCHIARELLI
Host Institution (HI) FONDAZIONE TELETHON
Call Details Starting Grant (StG), LS2, ERC-2017-STG
Summary The concept that any cell type, upon delivery of the right “cocktail” of transcription factors, can acquire an identity that otherwise it would never achieve, revolutionized the way we approach the study of developmental biology. In light of this, the discovery of induced pluripotent stem cells (IPSCs) and cell fate conversion approaches stimulated new research directions into human regenerative biology. However, the chance to successfully develop patient-tailored therapies is still very limited because reprogramming technologies are applied without a comprehensive understanding of the molecular processes involved.
Here, I propose a multifaceted approach that combines a wide range of cutting-edge integrative genomic strategies to significantly advance our understanding of the regulatory logic driving cell fate decisions during human reprogramming to pluripotency.
To this end, I will utilize single cell transcriptomics to isolate reprogramming intermediates, reconstruct their lineage relationships and define transcriptional regulators responsible for the observed transitions (AIM 1). Then, I will dissect the rules by which transcription factors modulate the activity of promoters and enhancer regions during reprogramming transitions, by applying synthetic biology and genome editing approaches (AIM 2). Then, I will adopt an alternative approach to identify reprogramming modulators by the analysis of reprogramming-induced mutagenesis events (AIM 3). Finally, I will explore my findings in multiple primary reprogramming approaches to pluripotency, with the ultimate goal of improving the quality of IPSC derivation (Aim 4).
In summary, this project will expose novel determinants and yet unidentified molecular barriers of reprogramming to pluripotency and will be essential to unlock the full potential of reprogramming technologies for shaping cellular identity in vitro and to address pressing challenges of regenerative medicine.
Summary
The concept that any cell type, upon delivery of the right “cocktail” of transcription factors, can acquire an identity that otherwise it would never achieve, revolutionized the way we approach the study of developmental biology. In light of this, the discovery of induced pluripotent stem cells (IPSCs) and cell fate conversion approaches stimulated new research directions into human regenerative biology. However, the chance to successfully develop patient-tailored therapies is still very limited because reprogramming technologies are applied without a comprehensive understanding of the molecular processes involved.
Here, I propose a multifaceted approach that combines a wide range of cutting-edge integrative genomic strategies to significantly advance our understanding of the regulatory logic driving cell fate decisions during human reprogramming to pluripotency.
To this end, I will utilize single cell transcriptomics to isolate reprogramming intermediates, reconstruct their lineage relationships and define transcriptional regulators responsible for the observed transitions (AIM 1). Then, I will dissect the rules by which transcription factors modulate the activity of promoters and enhancer regions during reprogramming transitions, by applying synthetic biology and genome editing approaches (AIM 2). Then, I will adopt an alternative approach to identify reprogramming modulators by the analysis of reprogramming-induced mutagenesis events (AIM 3). Finally, I will explore my findings in multiple primary reprogramming approaches to pluripotency, with the ultimate goal of improving the quality of IPSC derivation (Aim 4).
In summary, this project will expose novel determinants and yet unidentified molecular barriers of reprogramming to pluripotency and will be essential to unlock the full potential of reprogramming technologies for shaping cellular identity in vitro and to address pressing challenges of regenerative medicine.
Max ERC Funding
1 497 250 €
Duration
Start date: 2018-03-01, End date: 2023-02-28
Project acronym CLEAR
Project Modulating cellular clearance to cure human disease
Researcher (PI) Andrea Ballabio
Host Institution (HI) FONDAZIONE TELETHON
Call Details Advanced Grant (AdG), LS2, ERC-2009-AdG
Summary Cellular clearance is a fundamental process required by all cells in all species. Important physiological processes, such as aging, and pathological mechanisms, such as neurodegeneration, are strictly dependent on cellular clearance. In eukaryotes, most of the cellular clearing processes occur in a specialized organelle, the lysosome. This project is based on a recent discovery, made in our laboratory, of a gene network, which we have named CLEAR, that controls lysosomal biogenesis and function and regulates cellular clearance. The specific goals of the project are: 1) the comprehensive characterization of the mechanisms underlying the CLEAR network, 2) the thorough understanding of CLEAR physiological function at the cellular and organism levels, 3) the development of strategies and tools to modulate cellular clearance, and 4) the implementation of proof-of-principle therapeutic studies based on the activation of the CLEAR network in murine models of human lysosomal storage disorders and of neurodegenerative diseases, such as Alzheimers s and Huntington s diseases. A combination of genomics, bioinformatics, systems biology, chemical genomics, cell biology, and mouse genetics approaches will be used to achieve these goals. Our goal is to develop tools to modulate cellular clearance and to use such tools to develop therapies to cure human disease. The potential medical relevance of this project is very high, particularly in the field of neurodegenerative disease. Therapies that prevent, ameliorate or delay neurodegeneration in these diseases would have a huge impact on human health.
Summary
Cellular clearance is a fundamental process required by all cells in all species. Important physiological processes, such as aging, and pathological mechanisms, such as neurodegeneration, are strictly dependent on cellular clearance. In eukaryotes, most of the cellular clearing processes occur in a specialized organelle, the lysosome. This project is based on a recent discovery, made in our laboratory, of a gene network, which we have named CLEAR, that controls lysosomal biogenesis and function and regulates cellular clearance. The specific goals of the project are: 1) the comprehensive characterization of the mechanisms underlying the CLEAR network, 2) the thorough understanding of CLEAR physiological function at the cellular and organism levels, 3) the development of strategies and tools to modulate cellular clearance, and 4) the implementation of proof-of-principle therapeutic studies based on the activation of the CLEAR network in murine models of human lysosomal storage disorders and of neurodegenerative diseases, such as Alzheimers s and Huntington s diseases. A combination of genomics, bioinformatics, systems biology, chemical genomics, cell biology, and mouse genetics approaches will be used to achieve these goals. Our goal is to develop tools to modulate cellular clearance and to use such tools to develop therapies to cure human disease. The potential medical relevance of this project is very high, particularly in the field of neurodegenerative disease. Therapies that prevent, ameliorate or delay neurodegeneration in these diseases would have a huge impact on human health.
Max ERC Funding
2 100 000 €
Duration
Start date: 2010-03-01, End date: 2015-02-28
