Project acronym BBRhythms
Project Brain and body rhythms: on the relationship between movement and percept
Researcher (PI) Barbara Haendel
Host Institution (HI) JULIUS-MAXIMILIANS-UNIVERSITAT WURZBURG
Call Details Starting Grant (StG), SH4, ERC-2015-STG
Summary Exciting findings from animal electrophysiological research in the last years suggest that an increased rate of body movements results in an enhanced response of neurons within the visual system despite the absence of visual changes. It is unclear why such modulation occurs in areas which process visual input. In humans, little is known about the influence of body movements on sensory brain areas mainly due to the technical challenges of measuring brain responses during pronounced muscle activity. However, psychophysical studies in humans show that also percept and perceptual demands are connected to the rate of movements. These two lines of evidence suggest a general link between rhythmic body movements and perceptual processes.
The main aim of the proposed research is to decode the relationship between body movements and percept and to identify the underlying mechanism. To this end human non-invasive recordings from electro- and magnetoencephalography (EEG, MEG) as well as invasive human and animal multi-electrode recordings collected during movement execution will be analyzed. Directly relating perceptual processes and their underlying neuronal oscillations to rhythmic body movements offers an approach circumventing some of the methodological problems.
This research could uncover a new mechanism of how our system modulates perceptual processes through body movements. The proof of such a mechanism would constitute a ground-breaking step in understanding perception during natural behavior. We need to keep in mind that in the awake state our body is constantly in motion. However, up to now, the vast majority of studies which investigate sensory brain responses are conducted under strict movement suppression. Besides facilitating exciting new insights, this research can strengthen the assumption that the knowledge we have gathered about artificial situations generalizes to our natural behavior.
Summary
Exciting findings from animal electrophysiological research in the last years suggest that an increased rate of body movements results in an enhanced response of neurons within the visual system despite the absence of visual changes. It is unclear why such modulation occurs in areas which process visual input. In humans, little is known about the influence of body movements on sensory brain areas mainly due to the technical challenges of measuring brain responses during pronounced muscle activity. However, psychophysical studies in humans show that also percept and perceptual demands are connected to the rate of movements. These two lines of evidence suggest a general link between rhythmic body movements and perceptual processes.
The main aim of the proposed research is to decode the relationship between body movements and percept and to identify the underlying mechanism. To this end human non-invasive recordings from electro- and magnetoencephalography (EEG, MEG) as well as invasive human and animal multi-electrode recordings collected during movement execution will be analyzed. Directly relating perceptual processes and their underlying neuronal oscillations to rhythmic body movements offers an approach circumventing some of the methodological problems.
This research could uncover a new mechanism of how our system modulates perceptual processes through body movements. The proof of such a mechanism would constitute a ground-breaking step in understanding perception during natural behavior. We need to keep in mind that in the awake state our body is constantly in motion. However, up to now, the vast majority of studies which investigate sensory brain responses are conducted under strict movement suppression. Besides facilitating exciting new insights, this research can strengthen the assumption that the knowledge we have gathered about artificial situations generalizes to our natural behavior.
Max ERC Funding
1 422 907 €
Duration
Start date: 2016-07-01, End date: 2021-06-30
Project acronym BCOOL
Project Barocaloric materials for energy-efficient solid-state cooling
Researcher (PI) Javier Eduardo Moya Raposo
Host Institution (HI) THE CHANCELLOR MASTERS AND SCHOLARS OF THE UNIVERSITY OF CAMBRIDGE
Call Details Starting Grant (StG), PE8, ERC-2015-STG
Summary Cooling is essential for food and drinks, medicine, electronics and thermal comfort. Thermal changes due to pressure-driven phase transitions in fluids have long been used in vapour compression systems to achieve continuous refrigeration and air conditioning, but their energy efficiency is relatively low, and the working fluids that are employed harm the environment when released to the atmosphere. More recently, the discovery of large thermal changes due to pressure-driven phase transitions in magnetic solids has led to suggestions for environmentally friendly solid-state cooling applications. However, for this new cooling technology to succeed, it is still necessary to find suitable barocaloric (BC) materials that satisfy the demanding requirements set by applications, namely very large thermal changes in inexpensive materials that occur near room temperature in response to small applied pressures.
I aim to develop new BC materials by exploiting phase transitions in non-magnetic solids whose structural and thermal properties are strongly coupled, namely ferroelectric salts, molecular crystals and hybrid materials. These materials are normally made from cheap abundant elements, and display very large latent heats and volume changes at structural phase transitions, which make them ideal candidates to exhibit extremely large BC effects that outperform those observed in state-of-the-art BC magnetic materials, and that match applications.
My unique approach combines: i) materials science to identify materials with outstanding BC performance, ii) advanced experimental techniques to explore and exploit these novel materials, iii) materials engineering to create new composite materials with enhanced BC properties, and iv) fabrication of BC devices, using insight gained from modelling of materials and device parameters. If successful, my ambitious strategy will culminate in revolutionary solid-state cooling devices that are environmentally friendly and energy efficient.
Summary
Cooling is essential for food and drinks, medicine, electronics and thermal comfort. Thermal changes due to pressure-driven phase transitions in fluids have long been used in vapour compression systems to achieve continuous refrigeration and air conditioning, but their energy efficiency is relatively low, and the working fluids that are employed harm the environment when released to the atmosphere. More recently, the discovery of large thermal changes due to pressure-driven phase transitions in magnetic solids has led to suggestions for environmentally friendly solid-state cooling applications. However, for this new cooling technology to succeed, it is still necessary to find suitable barocaloric (BC) materials that satisfy the demanding requirements set by applications, namely very large thermal changes in inexpensive materials that occur near room temperature in response to small applied pressures.
I aim to develop new BC materials by exploiting phase transitions in non-magnetic solids whose structural and thermal properties are strongly coupled, namely ferroelectric salts, molecular crystals and hybrid materials. These materials are normally made from cheap abundant elements, and display very large latent heats and volume changes at structural phase transitions, which make them ideal candidates to exhibit extremely large BC effects that outperform those observed in state-of-the-art BC magnetic materials, and that match applications.
My unique approach combines: i) materials science to identify materials with outstanding BC performance, ii) advanced experimental techniques to explore and exploit these novel materials, iii) materials engineering to create new composite materials with enhanced BC properties, and iv) fabrication of BC devices, using insight gained from modelling of materials and device parameters. If successful, my ambitious strategy will culminate in revolutionary solid-state cooling devices that are environmentally friendly and energy efficient.
Max ERC Funding
1 467 521 €
Duration
Start date: 2016-04-01, End date: 2021-03-31
Project acronym BEACON
Project Hybrid Digital-Analog Networking under Extreme Energy and Latency Constraints
Researcher (PI) Deniz Gunduz
Host Institution (HI) IMPERIAL COLLEGE OF SCIENCE TECHNOLOGY AND MEDICINE
Call Details Starting Grant (StG), PE7, ERC-2015-STG
Summary The objective of the BEACON project is to (re-)introduce analog communications into the design of modern wireless networks. We argue that the extreme energy and latency constraints imposed by the emerging Internet of Everything (IoE) paradigm can only be met within a hybrid digital-analog communications framework. Current network architectures separate source and channel coding, orthogonalize users, and employ long block-length digital source and channel codes, which are either suboptimal or not applicable under the aforementioned constraints. BEACON questions these well-established design principles, and proposes to replace them with a hybrid digital-analog communications framework, which will meet the required energy and latency constraints while simplifying the encoding and decoding processes. BEACON pushes the performance of the IoE to its theoretical limits by i) exploiting signal correlations that are abundant in IoE applications, given the foreseen density of deployed sensing devices, ii) taking into account the limited and stochastic nature of energy availability due to, for example, energy harvesting capabilities, iii) using feedback resources to improve the end-to-end signal distortion, and iv) deriving novel converse results to identify fundamental performance benchmarks.
The results of BEACON will not only shed light on the fundamental limits on the performance any coding scheme can achieve, but will also lead to the development of unconventional codes and communication protocols that can approach these limits, combining digital and analog communication techniques. The ultimate challenge for this project is to exploit the developed hybrid digital-analog networking theory for a complete overhaul of the physical layer design for emerging IoE applications, such as smart grids, tele-robotics and smart homes. For this purpose, a proof-of-concept implementation test-bed will also be built using software defined radios and sensor nodes.
Summary
The objective of the BEACON project is to (re-)introduce analog communications into the design of modern wireless networks. We argue that the extreme energy and latency constraints imposed by the emerging Internet of Everything (IoE) paradigm can only be met within a hybrid digital-analog communications framework. Current network architectures separate source and channel coding, orthogonalize users, and employ long block-length digital source and channel codes, which are either suboptimal or not applicable under the aforementioned constraints. BEACON questions these well-established design principles, and proposes to replace them with a hybrid digital-analog communications framework, which will meet the required energy and latency constraints while simplifying the encoding and decoding processes. BEACON pushes the performance of the IoE to its theoretical limits by i) exploiting signal correlations that are abundant in IoE applications, given the foreseen density of deployed sensing devices, ii) taking into account the limited and stochastic nature of energy availability due to, for example, energy harvesting capabilities, iii) using feedback resources to improve the end-to-end signal distortion, and iv) deriving novel converse results to identify fundamental performance benchmarks.
The results of BEACON will not only shed light on the fundamental limits on the performance any coding scheme can achieve, but will also lead to the development of unconventional codes and communication protocols that can approach these limits, combining digital and analog communication techniques. The ultimate challenge for this project is to exploit the developed hybrid digital-analog networking theory for a complete overhaul of the physical layer design for emerging IoE applications, such as smart grids, tele-robotics and smart homes. For this purpose, a proof-of-concept implementation test-bed will also be built using software defined radios and sensor nodes.
Max ERC Funding
1 496 350 €
Duration
Start date: 2016-10-01, End date: 2021-09-30
Project acronym BEAM-EDM
Project Unique Method for a Neutron Electric Dipole Moment Search using a Pulsed Beam
Researcher (PI) Florian Michael PIEGSA
Host Institution (HI) UNIVERSITAET BERN
Call Details Starting Grant (StG), PE2, ERC-2016-STG
Summary My research encompasses the application of novel methods and strategies in the field of low energy particle physics. The goal of the presented program is to lead an independent and highly competitive experiment to search for a CP violating neutron electric dipole moment (nEDM), as well as for new exotic interactions using highly sensitive neutron and proton spin resonance techniques.
The measurement of the nEDM is considered to be one of the most important fundamental physics experiments at low energy. It represents a promising route for finding new physics beyond the standard model (SM) and describes an important search for new sources of CP violation in order to understand the observed large baryon asymmetry in our universe. The main project will follow a novel concept based on my original idea, which plans to employ a pulsed neutron beam at high intensity instead of the established use of storable ultracold neutrons. This complementary and potentially ground-breaking method provides the possibility to distinguish between the signal due to a nEDM and previously limiting systematic effects, and should lead to an improved result compared to the present best nEDM beam experiment. The findings of these investigations will be of paramount importance and will form the cornerstone for the success of the full-scale experiment intended for the European Spallation Source. A second scientific question will be addressed by performing spin precession experiments searching for exotic short-range interactions and associated light bosons. This is a vivid field of research motivated by various extensions to the SM. The goal of these measurements, using neutrons and protons, is to search for additional interactions such new bosons mediate between ordinary particles.
Both topics describe ambitious and unique efforts. They use related techniques, address important questions in fundamental physics, and have the potential of substantial scientific implications and high-impact results.
Summary
My research encompasses the application of novel methods and strategies in the field of low energy particle physics. The goal of the presented program is to lead an independent and highly competitive experiment to search for a CP violating neutron electric dipole moment (nEDM), as well as for new exotic interactions using highly sensitive neutron and proton spin resonance techniques.
The measurement of the nEDM is considered to be one of the most important fundamental physics experiments at low energy. It represents a promising route for finding new physics beyond the standard model (SM) and describes an important search for new sources of CP violation in order to understand the observed large baryon asymmetry in our universe. The main project will follow a novel concept based on my original idea, which plans to employ a pulsed neutron beam at high intensity instead of the established use of storable ultracold neutrons. This complementary and potentially ground-breaking method provides the possibility to distinguish between the signal due to a nEDM and previously limiting systematic effects, and should lead to an improved result compared to the present best nEDM beam experiment. The findings of these investigations will be of paramount importance and will form the cornerstone for the success of the full-scale experiment intended for the European Spallation Source. A second scientific question will be addressed by performing spin precession experiments searching for exotic short-range interactions and associated light bosons. This is a vivid field of research motivated by various extensions to the SM. The goal of these measurements, using neutrons and protons, is to search for additional interactions such new bosons mediate between ordinary particles.
Both topics describe ambitious and unique efforts. They use related techniques, address important questions in fundamental physics, and have the potential of substantial scientific implications and high-impact results.
Max ERC Funding
1 404 062 €
Duration
Start date: 2017-04-01, End date: 2022-03-31
Project acronym Becoming Social
Project Social Interaction Perception and the Social Brain Across Typical and Atypical Development
Researcher (PI) Kami KOLDEWYN
Host Institution (HI) BANGOR UNIVERSITY
Call Details Starting Grant (StG), SH4, ERC-2016-STG
Summary Social interactions are multifaceted and subtle, yet we can almost instantaneously discern if two people are cooperating or competing, flirting or fighting, or helping or hindering each other. Surprisingly, the development and brain basis of this remarkable ability has remained largely unexplored. At the same time, understanding how we develop the ability to process and use social information from other people is widely recognized as a core challenge facing developmental cognitive neuroscience. The Becoming Social project meets this challenge by proposing the most complete investigation to date of the development of the behavioural and neurobiological systems that support complex social perception. To achieve this, we first systematically map how the social interactions we observe are coded in the brain by testing typical adults. Next, we investigate developmental change both behaviourally and neurally during a key stage in social development in typically developing children. Finally, we explore whether social interaction perception is clinically relevant by investigating it developmentally in autism spectrum disorder. The Becoming Social project is expected to lead to a novel conception of the neurocognitive architecture supporting the perception of social interactions. In addition, neuroimaging and behavioural tasks measured longitudinally during development will allow us to determine how individual differences in brain and behaviour are causally related to real-world social ability and social learning. The planned studies as well as those generated during the project will enable the Becoming Social team to become a world-leading group bridging social cognition, neuroscience and developmental psychology.
Summary
Social interactions are multifaceted and subtle, yet we can almost instantaneously discern if two people are cooperating or competing, flirting or fighting, or helping or hindering each other. Surprisingly, the development and brain basis of this remarkable ability has remained largely unexplored. At the same time, understanding how we develop the ability to process and use social information from other people is widely recognized as a core challenge facing developmental cognitive neuroscience. The Becoming Social project meets this challenge by proposing the most complete investigation to date of the development of the behavioural and neurobiological systems that support complex social perception. To achieve this, we first systematically map how the social interactions we observe are coded in the brain by testing typical adults. Next, we investigate developmental change both behaviourally and neurally during a key stage in social development in typically developing children. Finally, we explore whether social interaction perception is clinically relevant by investigating it developmentally in autism spectrum disorder. The Becoming Social project is expected to lead to a novel conception of the neurocognitive architecture supporting the perception of social interactions. In addition, neuroimaging and behavioural tasks measured longitudinally during development will allow us to determine how individual differences in brain and behaviour are causally related to real-world social ability and social learning. The planned studies as well as those generated during the project will enable the Becoming Social team to become a world-leading group bridging social cognition, neuroscience and developmental psychology.
Max ERC Funding
1 500 000 €
Duration
Start date: 2017-04-01, End date: 2022-03-31
Project acronym BEGMAT
Project Layered functional materials - beyond 'graphene'
Researcher (PI) Michael Janus Bojdys
Host Institution (HI) HUMBOLDT-UNIVERSITAET ZU BERLIN
Call Details Starting Grant (StG), PE5, ERC-2015-STG
Summary There is an apparent lack of non-metallic 2D-matrials for the construction of electronic devices, as only five materials of the “graphene family” are known: graphene, hBN, BCN, fluorographene, and graphene oxide – none of them with a narrow bandgap close to commercially used silicon. This ERC-StG proposal, BEGMAT, outlines a strategy for design, synthesis, and application of layered, functional materials that will go beyond this exclusive club. These materials “beyond graphene” (BEG) will have to meet – like graphene – the following criteria:
(1) The BEG-materials will feature a transfer of crystalline order from the molecular (pm-range) to the macroscopic level (cm-range),
(2) individual, free-standing layers of BEG-materials can be addressed by mechanical or chemical exfoliation, and
(3) assemblies of different BEG-materials will be stacked as van der Waals heterostructures with unique properties.
In contrast to the existing “graphene family”,
(4) BEG-materials will be constructed in a controlled way by covalent organic chemistry in a bottom-up approach from abundant precursors free of metals and critical raw materials (CRMs).
Moreover – and unlike – many covalent organic frameworks (COFs),
(5) BEG-materials will be fully aromatic, donor-acceptor systems to ensure that electronic properties can be addressed on macroscopic scale.
The potential to make 2D materials “beyond graphene” is a great challenge to chemical bond formation and material design. In 2014 the applicant has demonstrated the feasibility of the concept to expand the “graphene family” with triazine-based graphitic carbon, a compound highlighted as an “emerging competitor for the miracle material” graphene. Now, the PI has the opportunity to build a full-scale research program on layered functional materials that offers unique insights into controlled, covalent linking-chemistry, and that addresses practicalities in device manufacture, and structure-properties relationships.
Summary
There is an apparent lack of non-metallic 2D-matrials for the construction of electronic devices, as only five materials of the “graphene family” are known: graphene, hBN, BCN, fluorographene, and graphene oxide – none of them with a narrow bandgap close to commercially used silicon. This ERC-StG proposal, BEGMAT, outlines a strategy for design, synthesis, and application of layered, functional materials that will go beyond this exclusive club. These materials “beyond graphene” (BEG) will have to meet – like graphene – the following criteria:
(1) The BEG-materials will feature a transfer of crystalline order from the molecular (pm-range) to the macroscopic level (cm-range),
(2) individual, free-standing layers of BEG-materials can be addressed by mechanical or chemical exfoliation, and
(3) assemblies of different BEG-materials will be stacked as van der Waals heterostructures with unique properties.
In contrast to the existing “graphene family”,
(4) BEG-materials will be constructed in a controlled way by covalent organic chemistry in a bottom-up approach from abundant precursors free of metals and critical raw materials (CRMs).
Moreover – and unlike – many covalent organic frameworks (COFs),
(5) BEG-materials will be fully aromatic, donor-acceptor systems to ensure that electronic properties can be addressed on macroscopic scale.
The potential to make 2D materials “beyond graphene” is a great challenge to chemical bond formation and material design. In 2014 the applicant has demonstrated the feasibility of the concept to expand the “graphene family” with triazine-based graphitic carbon, a compound highlighted as an “emerging competitor for the miracle material” graphene. Now, the PI has the opportunity to build a full-scale research program on layered functional materials that offers unique insights into controlled, covalent linking-chemistry, and that addresses practicalities in device manufacture, and structure-properties relationships.
Max ERC Funding
1 362 538 €
Duration
Start date: 2016-08-01, End date: 2021-07-31
Project acronym BeyondBlackbox
Project Data-Driven Methods for Modelling and Optimizing the Empirical Performance of Deep Neural Networks
Researcher (PI) Frank Roman HUTTER
Host Institution (HI) ALBERT-LUDWIGS-UNIVERSITAET FREIBURG
Call Details Starting Grant (StG), PE6, ERC-2016-STG
Summary Deep neural networks (DNNs) have led to dramatic improvements of the state-of-the-art for many important classification problems, such as object recognition from images or speech recognition from audio data. However, DNNs are also notoriously dependent on the tuning of their hyperparameters. Since their manual tuning is time-consuming and requires expert knowledge, recent years have seen the rise of Bayesian optimization methods for automating this task. While these methods have had substantial successes, their treatment of DNN performance as a black box poses fundamental limitations, allowing manual tuning to be more effective for large and computationally expensive data sets: humans can (1) exploit prior knowledge and extrapolate performance from data subsets, (2) monitor the DNN's internal weight optimization by stochastic gradient descent over time, and (3) reactively change hyperparameters at runtime. We therefore propose to model DNN performance beyond a blackbox level and to use these models to develop for the first time:
1. Next-generation Bayesian optimization methods that exploit data-driven priors to optimize performance orders of magnitude faster than currently possible;
2. Graybox Bayesian optimization methods that have access to -- and exploit -- performance and state information of algorithm runs over time; and
3. Hyperparameter control strategies that learn across different datasets to adapt hyperparameters reactively to the characteristics of any given situation.
DNNs play into our project in two ways. First, in all our methods we will use (Bayesian) DNNs to model and exploit the large amounts of performance data we will collect on various datasets. Second, our application goal is to optimize and control DNN hyperparameters far better than human experts and to obtain:
4. Computationally inexpensive auto-tuned deep neural networks, even for large datasets, enabling the widespread use of deep learning by non-experts.
Summary
Deep neural networks (DNNs) have led to dramatic improvements of the state-of-the-art for many important classification problems, such as object recognition from images or speech recognition from audio data. However, DNNs are also notoriously dependent on the tuning of their hyperparameters. Since their manual tuning is time-consuming and requires expert knowledge, recent years have seen the rise of Bayesian optimization methods for automating this task. While these methods have had substantial successes, their treatment of DNN performance as a black box poses fundamental limitations, allowing manual tuning to be more effective for large and computationally expensive data sets: humans can (1) exploit prior knowledge and extrapolate performance from data subsets, (2) monitor the DNN's internal weight optimization by stochastic gradient descent over time, and (3) reactively change hyperparameters at runtime. We therefore propose to model DNN performance beyond a blackbox level and to use these models to develop for the first time:
1. Next-generation Bayesian optimization methods that exploit data-driven priors to optimize performance orders of magnitude faster than currently possible;
2. Graybox Bayesian optimization methods that have access to -- and exploit -- performance and state information of algorithm runs over time; and
3. Hyperparameter control strategies that learn across different datasets to adapt hyperparameters reactively to the characteristics of any given situation.
DNNs play into our project in two ways. First, in all our methods we will use (Bayesian) DNNs to model and exploit the large amounts of performance data we will collect on various datasets. Second, our application goal is to optimize and control DNN hyperparameters far better than human experts and to obtain:
4. Computationally inexpensive auto-tuned deep neural networks, even for large datasets, enabling the widespread use of deep learning by non-experts.
Max ERC Funding
1 495 000 €
Duration
Start date: 2017-01-01, End date: 2021-12-31
Project acronym BIAF
Project Bird Inspired Autonomous Flight
Researcher (PI) Shane Paul Windsor
Host Institution (HI) UNIVERSITY OF BRISTOL
Call Details Starting Grant (StG), PE8, ERC-2015-STG
Summary The agile and efficient flight of birds shows what flight performance is physically possible, and in theory could be achieved by unmanned air vehicles (UAVs) of the same size. The overall aim of this project is to enhance the performance of small scale UAVs by developing novel technologies inspired by understanding how birds are adapted to interact with airflows. Small UAVs have the potential to dramatically change current practices in many areas such as, search and rescue, surveillance, and environmental monitoring. Currently the utility of these systems is limited by their operational endurance and their inability to operate in strong turbulent winds, especially those that often occur in urban environments. Birds are adapted to be able to fly in these conditions and actually use them to their advantage to minimise their energy output.
This project is composed of three tracks which contain elements of technology development, as well as scientific investigation looking at bird flight behaviour and aerodynamics. The first track looks at developing path planning algorithms for UAVs in urban environments based on how birds fly in these areas, by using GPS tracking and computational fluid dynamics alongside trajectory optimization. The second track aims to develop artificial wings with improved gust tolerance inspired by the features of feathered wings. Here, high speed video measurements of birds flying through gusts will be used alongside wind tunnel testing of artificial wings to discover what features of a bird’s wing help to alleviate gusts. The third track develops novel force and flow sensor arrays for autonomous flight control based on the sensor arrays found in flying animals. These arrays will be used to make UAVs with increased agility and robustness. This unique bird inspired approach uses biology to show what is possible, and engineering to find the features that enable this performance and develop them into functional technologies.
Summary
The agile and efficient flight of birds shows what flight performance is physically possible, and in theory could be achieved by unmanned air vehicles (UAVs) of the same size. The overall aim of this project is to enhance the performance of small scale UAVs by developing novel technologies inspired by understanding how birds are adapted to interact with airflows. Small UAVs have the potential to dramatically change current practices in many areas such as, search and rescue, surveillance, and environmental monitoring. Currently the utility of these systems is limited by their operational endurance and their inability to operate in strong turbulent winds, especially those that often occur in urban environments. Birds are adapted to be able to fly in these conditions and actually use them to their advantage to minimise their energy output.
This project is composed of three tracks which contain elements of technology development, as well as scientific investigation looking at bird flight behaviour and aerodynamics. The first track looks at developing path planning algorithms for UAVs in urban environments based on how birds fly in these areas, by using GPS tracking and computational fluid dynamics alongside trajectory optimization. The second track aims to develop artificial wings with improved gust tolerance inspired by the features of feathered wings. Here, high speed video measurements of birds flying through gusts will be used alongside wind tunnel testing of artificial wings to discover what features of a bird’s wing help to alleviate gusts. The third track develops novel force and flow sensor arrays for autonomous flight control based on the sensor arrays found in flying animals. These arrays will be used to make UAVs with increased agility and robustness. This unique bird inspired approach uses biology to show what is possible, and engineering to find the features that enable this performance and develop them into functional technologies.
Max ERC Funding
1 998 546 €
Duration
Start date: 2016-04-01, End date: 2021-03-31
Project acronym BIGCODE
Project Learning from Big Code: Probabilistic Models, Analysis and Synthesis
Researcher (PI) Martin Vechev
Host Institution (HI) EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH
Call Details Starting Grant (StG), PE6, ERC-2015-STG
Summary The goal of this proposal is to fundamentally change the way we build and reason about software. We aim to develop new kinds of statistical programming systems that provide probabilistically likely solutions to tasks that are difficult or impossible to solve with traditional approaches.
These statistical programming systems will be based on probabilistic models of massive codebases (also known as ``Big Code'') built via a combination of advanced programming languages and powerful machine learning and natural language processing techniques. To solve a particular challenge, a statistical programming system will query a probabilistic model, compute the most likely predictions, and present those to the developer.
Based on probabilistic models of ``Big Code'', we propose to investigate new statistical techniques in the context of three fundamental research directions: i) statistical program synthesis where we develop techniques that automatically synthesize and predict new programs, ii) statistical prediction of program properties where we develop new techniques that can predict important facts (e.g., types) about programs, and iii) statistical translation of programs where we investigate new techniques for statistical translation of programs (e.g., from one programming language to another, or to a natural language).
We believe the research direction outlined in this interdisciplinary proposal opens a new and exciting area of computer science. This area will combine sophisticated statistical learning and advanced programming language techniques for building the next-generation statistical programming systems.
We expect the results of this proposal to have an immediate impact upon millions of developers worldwide, triggering a paradigm shift in the way tomorrow's software is built, as well as a long-lasting impact on scientific fields such as machine learning, natural language processing, programming languages and software engineering.
Summary
The goal of this proposal is to fundamentally change the way we build and reason about software. We aim to develop new kinds of statistical programming systems that provide probabilistically likely solutions to tasks that are difficult or impossible to solve with traditional approaches.
These statistical programming systems will be based on probabilistic models of massive codebases (also known as ``Big Code'') built via a combination of advanced programming languages and powerful machine learning and natural language processing techniques. To solve a particular challenge, a statistical programming system will query a probabilistic model, compute the most likely predictions, and present those to the developer.
Based on probabilistic models of ``Big Code'', we propose to investigate new statistical techniques in the context of three fundamental research directions: i) statistical program synthesis where we develop techniques that automatically synthesize and predict new programs, ii) statistical prediction of program properties where we develop new techniques that can predict important facts (e.g., types) about programs, and iii) statistical translation of programs where we investigate new techniques for statistical translation of programs (e.g., from one programming language to another, or to a natural language).
We believe the research direction outlined in this interdisciplinary proposal opens a new and exciting area of computer science. This area will combine sophisticated statistical learning and advanced programming language techniques for building the next-generation statistical programming systems.
We expect the results of this proposal to have an immediate impact upon millions of developers worldwide, triggering a paradigm shift in the way tomorrow's software is built, as well as a long-lasting impact on scientific fields such as machine learning, natural language processing, programming languages and software engineering.
Max ERC Funding
1 500 000 €
Duration
Start date: 2016-04-01, End date: 2021-03-31
Project acronym BILUM
Project Novel applications based on organic biluminescence
Researcher (PI) Sebastian Reineke
Host Institution (HI) TECHNISCHE UNIVERSITAET DRESDEN
Call Details Starting Grant (StG), PE3, ERC-2015-STG
Summary Organic semiconducting molecules often make for very good luminescent materials. Fundamental excitations are localized on single molecules, which is in stark contrast to inorganic semiconductors, such that exchange interactions lead to energetically distinct singlet and triplet states. The singlet-excited state is the origin of conventional fluorescence. However, once an excitation is in the molecular triplet state, emission of photons is very unlikely, because spin conservation needs to be broken. Here, non-radiative recombination outcompetes the radiative.
Recent research efforts led to the discovery of highly efficient biluminescence. Here, in addition to the fluorescence from the singlet state, the phosphorescence (triplet state emission) is unlocked by suppression of non-radiative channels at room temperature. The dynamics of both states is vastly different with nanosecond fluorescence and millisecond phosphorescence. If both channels are highly luminescent, then there is no room for loss channels.
Within BILUM, the virtually unexplored phenomenon of biluminescence will be the central point: On the basic science side, efforts will be focussed on the detailed understanding of structure-property relationships that are key for efficient dual state emission. At the same time, with a curiosity driven engineering approach, known bilumophores will be carefully tested in different scenarios to set the ground for future applications. Biluminescence has the potential to access non-radiative triplet states that are in many cases system limiting, to serve as ultra-broadband emitters, to introduce persistent (ultra long-lived) emission, to store photonic energy, and to allow optical sensing with internal reference emission – all on the molecular level. New bilumophores will be identified through systematic screening that will employ quantum chemical calculations and developed through organic synthesis.
Summary
Organic semiconducting molecules often make for very good luminescent materials. Fundamental excitations are localized on single molecules, which is in stark contrast to inorganic semiconductors, such that exchange interactions lead to energetically distinct singlet and triplet states. The singlet-excited state is the origin of conventional fluorescence. However, once an excitation is in the molecular triplet state, emission of photons is very unlikely, because spin conservation needs to be broken. Here, non-radiative recombination outcompetes the radiative.
Recent research efforts led to the discovery of highly efficient biluminescence. Here, in addition to the fluorescence from the singlet state, the phosphorescence (triplet state emission) is unlocked by suppression of non-radiative channels at room temperature. The dynamics of both states is vastly different with nanosecond fluorescence and millisecond phosphorescence. If both channels are highly luminescent, then there is no room for loss channels.
Within BILUM, the virtually unexplored phenomenon of biluminescence will be the central point: On the basic science side, efforts will be focussed on the detailed understanding of structure-property relationships that are key for efficient dual state emission. At the same time, with a curiosity driven engineering approach, known bilumophores will be carefully tested in different scenarios to set the ground for future applications. Biluminescence has the potential to access non-radiative triplet states that are in many cases system limiting, to serve as ultra-broadband emitters, to introduce persistent (ultra long-lived) emission, to store photonic energy, and to allow optical sensing with internal reference emission – all on the molecular level. New bilumophores will be identified through systematic screening that will employ quantum chemical calculations and developed through organic synthesis.
Max ERC Funding
1 462 500 €
Duration
Start date: 2016-04-01, End date: 2021-03-31
