Project acronym ACDC
Project Algorithms and Complexity of Highly Decentralized Computations
Researcher (PI) Fabian Daniel Kuhn
Host Institution (HI) ALBERT-LUDWIGS-UNIVERSITAET FREIBURG
Call Details Starting Grant (StG), PE6, ERC-2013-StG
Summary "Many of today's and tomorrow's computer systems are built on top of large-scale networks such as, e.g., the Internet, the world wide web, wireless ad hoc and sensor networks, or peer-to-peer networks. Driven by technological advances, new kinds of networks and applications have become possible and we can safely assume that this trend is going to continue. Often modern systems are envisioned to consist of a potentially large number of individual components that are organized in a completely decentralized way. There is no central authority that controls the topology of the network, how nodes join or leave the system, or in which way nodes communicate with each other. Also, many future distributed applications will be built using wireless devices that communicate via radio.
The general objective of the proposed project is to improve our understanding of the algorithmic and theoretical foundations of decentralized distributed systems. From an algorithmic point of view, decentralized networks and computations pose a number of fascinating and unique challenges that are not present in sequential or more standard distributed systems. As communication is limited and mostly between nearby nodes, each node of a large network can only maintain a very restricted view of the global state of the system. This is particularly true if the network can change dynamically, either by nodes joining or leaving the system or if the topology changes over time, e.g., because of the mobility of the devices in case of a wireless network. Nevertheless, the nodes of a network need to coordinate in order to achieve some global goal.
In particular, we plan to study algorithms and lower bounds for basic computation and information dissemination tasks in such systems. In addition, we are particularly interested in the complexity of distributed computations in dynamic and wireless networks."
Summary
"Many of today's and tomorrow's computer systems are built on top of large-scale networks such as, e.g., the Internet, the world wide web, wireless ad hoc and sensor networks, or peer-to-peer networks. Driven by technological advances, new kinds of networks and applications have become possible and we can safely assume that this trend is going to continue. Often modern systems are envisioned to consist of a potentially large number of individual components that are organized in a completely decentralized way. There is no central authority that controls the topology of the network, how nodes join or leave the system, or in which way nodes communicate with each other. Also, many future distributed applications will be built using wireless devices that communicate via radio.
The general objective of the proposed project is to improve our understanding of the algorithmic and theoretical foundations of decentralized distributed systems. From an algorithmic point of view, decentralized networks and computations pose a number of fascinating and unique challenges that are not present in sequential or more standard distributed systems. As communication is limited and mostly between nearby nodes, each node of a large network can only maintain a very restricted view of the global state of the system. This is particularly true if the network can change dynamically, either by nodes joining or leaving the system or if the topology changes over time, e.g., because of the mobility of the devices in case of a wireless network. Nevertheless, the nodes of a network need to coordinate in order to achieve some global goal.
In particular, we plan to study algorithms and lower bounds for basic computation and information dissemination tasks in such systems. In addition, we are particularly interested in the complexity of distributed computations in dynamic and wireless networks."
Max ERC Funding
1 148 000 €
Duration
Start date: 2013-11-01, End date: 2018-10-31
Project acronym CapReal
Project Performance Capture of the Real World in Motion
Researcher (PI) Christian Theobalt
Host Institution (HI) MAX-PLANCK-GESELLSCHAFT ZUR FORDERUNG DER WISSENSCHAFTEN EV
Call Details Starting Grant (StG), PE6, ERC-2013-StG
Summary Computer graphics technology for realistic rendering has improved
dramatically; however, the technology to create scene models to be rendered,
e.g., for movies, has not developed at the same pace. In practice, the state
of the art in model creation still requires months of complex manual design,
and this is a serious threat to progress. To attack this problem, computer
graphics and computer vision researchers jointly developed methods that
capture scene models from real world examples. Of particular importance is
the capturing of moving scenes. The pinnacle of dynamic scene capture
technology in research is marker-less performance capture. From multi-view
video, they capture dynamic surface and texture models of the real world.
Performance capture is hardly used in practice due to profound limitations:
recording is usually limited to indoor studios, controlled lighting, and
dense static camera arrays. Methods are often limited to single objects, and
reconstructed shape detail is very limited. Assumptions about materials,
reflectance, and lighting in a scene are simplistic, and we cannot easily
modify captured data.
In this project, we will pioneer a new generation of performance capture
techniques to overcome these limitations. Our methods will allow the
reconstruction of dynamic surface models of unprecedented shape detail. They
will succeed on general scenes outside of the lab and outdoors, scenes with
complex material and reflectance distributions, and scenes in which lighting
is general, uncontrolled, and unknown. They will capture dense and crowded
scenes with complex shape deformations. They will reconstruct conveniently
modifiable scene models. They will work with sparse and moving sets of
cameras, ultimately even with mobile phones. This far-reaching,
multi-disciplinary project will turn performance capture from a research
technology into a practical technology, provide groundbreaking scientific
insights, and open up revolutionary new applications.
Summary
Computer graphics technology for realistic rendering has improved
dramatically; however, the technology to create scene models to be rendered,
e.g., for movies, has not developed at the same pace. In practice, the state
of the art in model creation still requires months of complex manual design,
and this is a serious threat to progress. To attack this problem, computer
graphics and computer vision researchers jointly developed methods that
capture scene models from real world examples. Of particular importance is
the capturing of moving scenes. The pinnacle of dynamic scene capture
technology in research is marker-less performance capture. From multi-view
video, they capture dynamic surface and texture models of the real world.
Performance capture is hardly used in practice due to profound limitations:
recording is usually limited to indoor studios, controlled lighting, and
dense static camera arrays. Methods are often limited to single objects, and
reconstructed shape detail is very limited. Assumptions about materials,
reflectance, and lighting in a scene are simplistic, and we cannot easily
modify captured data.
In this project, we will pioneer a new generation of performance capture
techniques to overcome these limitations. Our methods will allow the
reconstruction of dynamic surface models of unprecedented shape detail. They
will succeed on general scenes outside of the lab and outdoors, scenes with
complex material and reflectance distributions, and scenes in which lighting
is general, uncontrolled, and unknown. They will capture dense and crowded
scenes with complex shape deformations. They will reconstruct conveniently
modifiable scene models. They will work with sparse and moving sets of
cameras, ultimately even with mobile phones. This far-reaching,
multi-disciplinary project will turn performance capture from a research
technology into a practical technology, provide groundbreaking scientific
insights, and open up revolutionary new applications.
Max ERC Funding
1 480 800 €
Duration
Start date: 2013-09-01, End date: 2018-08-31
Project acronym CHROMOTHRIPSIS
Project Dissecting the Molecular Mechanism of Catastrophic DNA Rearrangement in Cancer
Researcher (PI) Jan Oliver Korbel
Host Institution (HI) EUROPEAN MOLECULAR BIOLOGY LABORATORY
Call Details Starting Grant (StG), LS2, ERC-2013-StG
Summary Recent cancer genome analyses have led to the discovery of a process involving massive genome structural rearrangement (SR) formation in a one-step, cataclysmic event, coined chromothripsis. The term chromothripsis (chromo from chromosome; thripsis for shattering into pieces) stands for a hypothetical process in which individual chromosomes are pulverised, resulting in a multitude of fragments, some of which are lost to the cell whereas others are erroneously rejoined. Compelling evidence was presented that chromothripsis plays a crucial role in the development, or progression of a notable subset of human cancers – thus, tumorigensis models involving gradual acquisitions of alterations may need to be revised in these cancers.
Presently, chromothripsis lacks a mechanistic basis. We recently showed that in childhood medulloblastoma brain tumours driven by Sonic Hedgehog (Shh) signalling, chromothripsis is linked with predisposing TP53 mutations. Thus, rather than occurring in isolation, chromothripsis appears to be prone to happen in conjunction with (or instigated by) gradually acquired alterations, or in the context of active signalling pathways, the inference of which may lead to further mechanistic insights. Using such rationale, I propose to dissect the mechanism behind chromothripsis using interdisciplinary approaches. First, we will develop a computational approach to accurately detect chromothripsis. Second, we will use this approach to link chromothripsis with novel factors and contexts. Third, we will develop highly controllable cell line-based systems to test concrete mechanistic hypotheses, thereby taking into account our data on linked factors and contexts. Fourth, we will generate transcriptome data to monitor pathways involved in inducing chromothripsis, and such involved in coping with the massive SRs occurring. We will also combine findings from all these approaches to build a comprehensive model of chromothripsis and its associated pathways.
Summary
Recent cancer genome analyses have led to the discovery of a process involving massive genome structural rearrangement (SR) formation in a one-step, cataclysmic event, coined chromothripsis. The term chromothripsis (chromo from chromosome; thripsis for shattering into pieces) stands for a hypothetical process in which individual chromosomes are pulverised, resulting in a multitude of fragments, some of which are lost to the cell whereas others are erroneously rejoined. Compelling evidence was presented that chromothripsis plays a crucial role in the development, or progression of a notable subset of human cancers – thus, tumorigensis models involving gradual acquisitions of alterations may need to be revised in these cancers.
Presently, chromothripsis lacks a mechanistic basis. We recently showed that in childhood medulloblastoma brain tumours driven by Sonic Hedgehog (Shh) signalling, chromothripsis is linked with predisposing TP53 mutations. Thus, rather than occurring in isolation, chromothripsis appears to be prone to happen in conjunction with (or instigated by) gradually acquired alterations, or in the context of active signalling pathways, the inference of which may lead to further mechanistic insights. Using such rationale, I propose to dissect the mechanism behind chromothripsis using interdisciplinary approaches. First, we will develop a computational approach to accurately detect chromothripsis. Second, we will use this approach to link chromothripsis with novel factors and contexts. Third, we will develop highly controllable cell line-based systems to test concrete mechanistic hypotheses, thereby taking into account our data on linked factors and contexts. Fourth, we will generate transcriptome data to monitor pathways involved in inducing chromothripsis, and such involved in coping with the massive SRs occurring. We will also combine findings from all these approaches to build a comprehensive model of chromothripsis and its associated pathways.
Max ERC Funding
1 471 964 €
Duration
Start date: 2014-04-01, End date: 2019-01-31
Project acronym FLAMMASEC
Project "Inflammasome-induced IL-1 Secretion: Route, Mechanism, and Cell Fate"
Researcher (PI) Olaf Groß
Host Institution (HI) UNIVERSITAETSKLINIKUM FREIBURG
Call Details Starting Grant (StG), LS6, ERC-2013-StG
Summary "Inflammasomes are intracellular danger-sensing protein complexes that are important for host protection. They initiate inflammation by controlling the activity of the proinflammatory cytokine interleukin-1β (IL-1β). Unlike most other cytokines, IL-1β is produced and retained in the cytoplasm in an inactive pro-form. Inflammasome-dependent maturation of proIL-1β is mediated by the common component of all inflammasomes, the protease caspase-1. Caspase-1 also controls the secretion of IL-1β, but the mechanism and route of secretion are unknown. We have recently demonstrated that the ability of caspase-1 to control IL-1β secretion is not dependent on its protease activity, but rather on a scaffold or adapter function of caspase-1. Furthermore, we and others could show that caspase-1 can control the secretion of non-substrates like IL-1α. These insights provide us with new and potentially revealing means to investigate the downstream effector functions of caspase-1, including the route and mechanism of IL-1 secretion. We will develop new tools to study the process of IL-1 secretion by microscopy and the novel mode-of-action of caspase-1 through the generation of transgenic models.
Despite the important role of IL-1 in host defence against infection, dysregulated inflammasome activation and IL-1 production has a causal role in a number of acquired and hereditary auto-inflammatory conditions. These include particle-induced sterile inflammation (as is seen in gout and asbestosis), hereditary periodic fever syndromes, and metabolic diseases like diabetes and atherosclerosis. Currently, recombinant proteins that block the IL-1 receptor or deplete secreted IL-1 are used to treat IL-1-dependent diseases. These are costly treatments, and are also therapeutically cumbersome since they are not orally available. We hope that a better understanding of caspase-1-mediated secretion of IL-1 will unveil mechanisms that may serve as targets for future therapies for these diseases."
Summary
"Inflammasomes are intracellular danger-sensing protein complexes that are important for host protection. They initiate inflammation by controlling the activity of the proinflammatory cytokine interleukin-1β (IL-1β). Unlike most other cytokines, IL-1β is produced and retained in the cytoplasm in an inactive pro-form. Inflammasome-dependent maturation of proIL-1β is mediated by the common component of all inflammasomes, the protease caspase-1. Caspase-1 also controls the secretion of IL-1β, but the mechanism and route of secretion are unknown. We have recently demonstrated that the ability of caspase-1 to control IL-1β secretion is not dependent on its protease activity, but rather on a scaffold or adapter function of caspase-1. Furthermore, we and others could show that caspase-1 can control the secretion of non-substrates like IL-1α. These insights provide us with new and potentially revealing means to investigate the downstream effector functions of caspase-1, including the route and mechanism of IL-1 secretion. We will develop new tools to study the process of IL-1 secretion by microscopy and the novel mode-of-action of caspase-1 through the generation of transgenic models.
Despite the important role of IL-1 in host defence against infection, dysregulated inflammasome activation and IL-1 production has a causal role in a number of acquired and hereditary auto-inflammatory conditions. These include particle-induced sterile inflammation (as is seen in gout and asbestosis), hereditary periodic fever syndromes, and metabolic diseases like diabetes and atherosclerosis. Currently, recombinant proteins that block the IL-1 receptor or deplete secreted IL-1 are used to treat IL-1-dependent diseases. These are costly treatments, and are also therapeutically cumbersome since they are not orally available. We hope that a better understanding of caspase-1-mediated secretion of IL-1 will unveil mechanisms that may serve as targets for future therapies for these diseases."
Max ERC Funding
1 495 533 €
Duration
Start date: 2014-03-01, End date: 2019-02-28
Project acronym IBDlipids
Project Lipid antigens in intestinal inflammation and tumor development
Researcher (PI) Sebastian Zeißig
Host Institution (HI) TECHNISCHE UNIVERSITAET DRESDEN
Call Details Starting Grant (StG), LS6, ERC-2013-StG
Summary Lipids play crucial roles in metabolism, immunity and cancer. In addition to their function as inflammatory mediators, lipids serve as antigens presented by CD1d and activate a subset of T cells called natural killer T (NKT) cells. While NKT cells are critical for human immunity, their uncontrolled activation contributes to inflammatory bowel disease (IBD), a group of diseases characterized by chronic intestinal inflammation and an increased risk of colorectal cancer (CRC). Specifically, NKT cells are the major source of pathogenic TH2 cytokines in the inflammatory bowel disease ulcerative colitis (UC), are sufficient to cause intestinal inflammation in mice, and are required for colitis and colitis-associated cancer in a mouse model of UC. These observations suggest that targeting of lipid antigen presentation may be of therapeutic value in IBD, where current therapies are of limited efficacy and aim at control rather than cure of disease.
Here, I propose to identify the lipid antigens responsible for NKT cell-mediated intestinal inflammation and colitis-associated cancer in human IBD and mouse models of intestinal inflammation and to develop therapeutic strategies for interference with pathogenic lipid antigen presentation. Specifically, I propose to characterize the intestinal inflammation- and cancer-associated CD1d lipidome based on novel in vitro and in vivo models of cleavable CD1d and a recently established lipidomics approach. Furthermore, I propose to develop strategies for inhibition of the generation, loading and presentation of inflammation- and cancer-associated lipid antigens. These studies combine biochemical, immunological and high-throughput technologies in an interdisciplinary manner to provide the knowledge required for the generation of novel, efficacious therapies for the treatment of IBD. These studies will have major implications for IBD and other inflammatory, infectious, and neoplastic diseases at mucosal barriers.
Summary
Lipids play crucial roles in metabolism, immunity and cancer. In addition to their function as inflammatory mediators, lipids serve as antigens presented by CD1d and activate a subset of T cells called natural killer T (NKT) cells. While NKT cells are critical for human immunity, their uncontrolled activation contributes to inflammatory bowel disease (IBD), a group of diseases characterized by chronic intestinal inflammation and an increased risk of colorectal cancer (CRC). Specifically, NKT cells are the major source of pathogenic TH2 cytokines in the inflammatory bowel disease ulcerative colitis (UC), are sufficient to cause intestinal inflammation in mice, and are required for colitis and colitis-associated cancer in a mouse model of UC. These observations suggest that targeting of lipid antigen presentation may be of therapeutic value in IBD, where current therapies are of limited efficacy and aim at control rather than cure of disease.
Here, I propose to identify the lipid antigens responsible for NKT cell-mediated intestinal inflammation and colitis-associated cancer in human IBD and mouse models of intestinal inflammation and to develop therapeutic strategies for interference with pathogenic lipid antigen presentation. Specifically, I propose to characterize the intestinal inflammation- and cancer-associated CD1d lipidome based on novel in vitro and in vivo models of cleavable CD1d and a recently established lipidomics approach. Furthermore, I propose to develop strategies for inhibition of the generation, loading and presentation of inflammation- and cancer-associated lipid antigens. These studies combine biochemical, immunological and high-throughput technologies in an interdisciplinary manner to provide the knowledge required for the generation of novel, efficacious therapies for the treatment of IBD. These studies will have major implications for IBD and other inflammatory, infectious, and neoplastic diseases at mucosal barriers.
Max ERC Funding
1 500 000 €
Duration
Start date: 2014-01-01, End date: 2018-12-31
Project acronym IHEARU
Project Intelligent systems' Holistic Evolving Analysis of Real-life Universal speaker characteristics
Researcher (PI) Bjoern Wolfgang Schuller
Host Institution (HI) UNIVERSITAT PASSAU
Call Details Starting Grant (StG), PE6, ERC-2013-StG
Summary "Recently, automatic speech and speaker recognition has matured to the degree that it entered the daily lives of thousands of Europe's citizens, e.g., on their smart phones or in call services. During the next years, speech processing technology will move to a new level of social awareness to make interaction more intuitive, speech retrieval more efficient, and lend additional competence to computer-mediated communication and speech-analysis services in the commercial, health, security, and further sectors. To reach this goal, rich speaker traits and states such as age, height, personality and physical and mental state as carried by the tone of the voice and the spoken words must be reliably identified by machines. In the iHEARu project, ground-breaking methodology including novel techniques for multi-task and semi-supervised learning will deliver for the first time intelligent holistic and evolving analysis in real-life condition of universal speaker characteristics which have been considered only in isolation so far. Today's sparseness of annotated realistic speech data will be overcome by large-scale speech and meta-data mining from public sources such as social media, crowd-sourcing for labelling and quality control, and shared semi-automatic annotation. All stages from pre-processing and feature extraction, to the statistical modelling will evolve in ""life-long learning"" according to new data, by utilising feedback, deep, and evolutionary learning methods. Human-in-the-loop system validation and novel perception studies will analyse the self-organising systems and the relation of automatic signal processing to human interpretation in a previously unseen variety of speaker classification tasks. The project's work plan gives the unique opportunity to transfer current world-leading expertise in this field into a new de-facto standard of speaker characterisation methods and open-source tools ready for tomorrow's challenge of socially aware speech analysis."
Summary
"Recently, automatic speech and speaker recognition has matured to the degree that it entered the daily lives of thousands of Europe's citizens, e.g., on their smart phones or in call services. During the next years, speech processing technology will move to a new level of social awareness to make interaction more intuitive, speech retrieval more efficient, and lend additional competence to computer-mediated communication and speech-analysis services in the commercial, health, security, and further sectors. To reach this goal, rich speaker traits and states such as age, height, personality and physical and mental state as carried by the tone of the voice and the spoken words must be reliably identified by machines. In the iHEARu project, ground-breaking methodology including novel techniques for multi-task and semi-supervised learning will deliver for the first time intelligent holistic and evolving analysis in real-life condition of universal speaker characteristics which have been considered only in isolation so far. Today's sparseness of annotated realistic speech data will be overcome by large-scale speech and meta-data mining from public sources such as social media, crowd-sourcing for labelling and quality control, and shared semi-automatic annotation. All stages from pre-processing and feature extraction, to the statistical modelling will evolve in ""life-long learning"" according to new data, by utilising feedback, deep, and evolutionary learning methods. Human-in-the-loop system validation and novel perception studies will analyse the self-organising systems and the relation of automatic signal processing to human interpretation in a previously unseen variety of speaker classification tasks. The project's work plan gives the unique opportunity to transfer current world-leading expertise in this field into a new de-facto standard of speaker characterisation methods and open-source tools ready for tomorrow's challenge of socially aware speech analysis."
Max ERC Funding
1 498 200 €
Duration
Start date: 2014-01-01, End date: 2018-12-31
Project acronym IL-22 AND IL-22BP
Project Identifying the immune and microbial network controlling the IL-22 – IL-22bp axis to open the doors for targeted therapies
Researcher (PI) Samuel Huber
Host Institution (HI) UNIVERSITAETSKLINIKUM HAMBURG-EPPENDORF
Call Details Starting Grant (StG), LS6, ERC-2013-StG
Summary Chronic mucosal inflammation and tissue damage predisposes patients to the development of colorectal cancer. One hypothesis is that the same factors important for wound healing, if left unchecked, also promote tumorigenesis. Tight control by a sensor of tissue damage should induce these factors to promote tissue repair, while limiting their activity to prevent development of cancer.
IL-22, a prototypical tissue repair factor, plays an important role in a wide variety of intestinal disease including infection, wound healing, colitis, and cancer. Indeed, IL-22 has protective and detrimental effects dependent on the milieu and disease suggesting that proper regulation is required. IL-22 expression is directly regulated, additionally a soluble IL-22 receptor (IL-22 binding protein; IL-22bp), can bind and neutralize IL-22. We reported recently that sensing of intestinal tissue damage and components of the microbiota via the NLRP3 or NLRP6 inflammasomes led to a down regulation of IL-22bp, thereby increasing bioavailability of IL-22. IL-22, which is induced during intestinal tissue damage, exerted protective properties during the peak of damage, but promoted tumor development if not controlled by IL-22bp during the recovery phase.
Accordingly a spatial and temporal regulation of IL-22 is crucial. Hence, global administration or blockade of IL-22 is unlikely to be therapeutically beneficial. We are using several newly generated conditional knock-out (cCasp1-/-, cIL-18R-/-, cIL-18-/-, cIL-22R1-/-), knock-in (IL-22 BFP), and gnotobiotic mice, aiming to analyze the cellular and microbial network regulating the IL-22 – IL-22bp axis at a resolution previously unfeasible. Our results will provide novel insights into the network between microflora, epithelium, and immune system regulating tissue regeneration and tumor development, and can lead to therapies for potentially a wide variety of intestinal diseases, such as infection, colon cancer, IBD, or wound healing.
Summary
Chronic mucosal inflammation and tissue damage predisposes patients to the development of colorectal cancer. One hypothesis is that the same factors important for wound healing, if left unchecked, also promote tumorigenesis. Tight control by a sensor of tissue damage should induce these factors to promote tissue repair, while limiting their activity to prevent development of cancer.
IL-22, a prototypical tissue repair factor, plays an important role in a wide variety of intestinal disease including infection, wound healing, colitis, and cancer. Indeed, IL-22 has protective and detrimental effects dependent on the milieu and disease suggesting that proper regulation is required. IL-22 expression is directly regulated, additionally a soluble IL-22 receptor (IL-22 binding protein; IL-22bp), can bind and neutralize IL-22. We reported recently that sensing of intestinal tissue damage and components of the microbiota via the NLRP3 or NLRP6 inflammasomes led to a down regulation of IL-22bp, thereby increasing bioavailability of IL-22. IL-22, which is induced during intestinal tissue damage, exerted protective properties during the peak of damage, but promoted tumor development if not controlled by IL-22bp during the recovery phase.
Accordingly a spatial and temporal regulation of IL-22 is crucial. Hence, global administration or blockade of IL-22 is unlikely to be therapeutically beneficial. We are using several newly generated conditional knock-out (cCasp1-/-, cIL-18R-/-, cIL-18-/-, cIL-22R1-/-), knock-in (IL-22 BFP), and gnotobiotic mice, aiming to analyze the cellular and microbial network regulating the IL-22 – IL-22bp axis at a resolution previously unfeasible. Our results will provide novel insights into the network between microflora, epithelium, and immune system regulating tissue regeneration and tumor development, and can lead to therapies for potentially a wide variety of intestinal diseases, such as infection, colon cancer, IBD, or wound healing.
Max ERC Funding
1 498 392 €
Duration
Start date: 2014-01-01, End date: 2018-12-31
Project acronym LIA
Project Light Field Imaging and Analysis
Researcher (PI) Bastian Goldlücke
Host Institution (HI) UNIVERSITAT KONSTANZ
Call Details Starting Grant (StG), PE6, ERC-2013-StG
Summary One of the most fundamental challenges in computer vision is to reliably establish correspondence - how to match a location in one image to its counterpart in another. It lies at the heart of numerous important problems, for example stereo, optical flow, tracking and the reconstruction of scene geometry from several photographs. The most popular approaches to solve these problems are based on the simplification that a scene point looks the same from wherever and whenever it is observed. However, this is fundamentally wrong, since its color changes with viewing direction and illumination. This invariably leads to failures when dealing with reflecting or transparent surfaces or changes in lighting, which commonly occur in natural scenes.
We therefore propose to radically rethink the underlying assumptions and work with light fields to describe the visual appearance of a scene. Compared to a traditional image, a light field offers information not only about the amount of incident light, but also the direction where it is coming from. In effect, the light field implicitly captures scene geometry and reflectance properties. In the following, we will argue that variational algorithms based on light field data have the potential to considerably advance the state-of-the-art in all image analysis applications related to lighting-invariant robust matching, geometry reconstruction or reflectance estimation.
Since computational cameras are currently making rapid progress, we believe that light fields will soon become a focus of computer vision research. Already, commercial plenoptic cameras allow to easily capture the light field of a scene and are suitable for real-world applications, while a recent survey even predicted that in about 20 years time, every consumer camera will be a light field camera. Our research will investigate fundamental mathematical tools and algorithms which will substantially contribute to drive this development.
Summary
One of the most fundamental challenges in computer vision is to reliably establish correspondence - how to match a location in one image to its counterpart in another. It lies at the heart of numerous important problems, for example stereo, optical flow, tracking and the reconstruction of scene geometry from several photographs. The most popular approaches to solve these problems are based on the simplification that a scene point looks the same from wherever and whenever it is observed. However, this is fundamentally wrong, since its color changes with viewing direction and illumination. This invariably leads to failures when dealing with reflecting or transparent surfaces or changes in lighting, which commonly occur in natural scenes.
We therefore propose to radically rethink the underlying assumptions and work with light fields to describe the visual appearance of a scene. Compared to a traditional image, a light field offers information not only about the amount of incident light, but also the direction where it is coming from. In effect, the light field implicitly captures scene geometry and reflectance properties. In the following, we will argue that variational algorithms based on light field data have the potential to considerably advance the state-of-the-art in all image analysis applications related to lighting-invariant robust matching, geometry reconstruction or reflectance estimation.
Since computational cameras are currently making rapid progress, we believe that light fields will soon become a focus of computer vision research. Already, commercial plenoptic cameras allow to easily capture the light field of a scene and are suitable for real-world applications, while a recent survey even predicted that in about 20 years time, every consumer camera will be a light field camera. Our research will investigate fundamental mathematical tools and algorithms which will substantially contribute to drive this development.
Max ERC Funding
1 466 100 €
Duration
Start date: 2014-07-01, End date: 2019-06-30
Project acronym PROTECTC
Project Identify novel pathways to enhance the induction of protective CD8+ T cell responses
Researcher (PI) Dietmar Zehn
Host Institution (HI) TECHNISCHE UNIVERSITAET MUENCHEN
Call Details Starting Grant (StG), LS6, ERC-2013-StG
Summary There is an urgent need for progress in developing prophylactic and therapeutic vaccination strategies that induce polyfunctional, strongly protective cytotoxic CD8 T cell responses. These could shield us from pathogens against which the presently available, neutralizing antibody-inducing vaccine approaches confer limited or no protection and they could be used to eliminate tumors or chronic infections. In contrast to this need, we currently fail to induce effector and memory CD8 T cells in numbers high enough to effectively impact an infection or the growth of tumors. As protective CD8 T cell responses are readily generated during several viral infections, we need to improve our insight into how pathogen protection is naturally achieved, identify why immune protection sometimes fails, and use this knowledge to develop novel vaccine strategies. We will use a well balanced approach of hypothesis stimulated and unbiased multisystem observations to exploit novel mechanisms and to find ways to augment the CD8 T cell response to a vaccine. We have established model systems that are uniquely suited to extract and test molecules that determine T cell differentiation and expansion magnitude. Along with that we aim to enhance our insight of immune responses in vaccinated individuals to prevent creating situation in which vaccines fail to confer protection or may cause adverse effects. We recently made very unexpected observations that challenge our current concept of T cell differentiation in chronic infections, which proposes that T cells terminally differentiate and become senescent. We therefore aim to redefine our understanding of T cell responses in such infections. This will also be pursued to unravel novel strategies to reactivate T cells in persisting infections. Overall, the project will strongly further our insight into CD8 T cell responses during infections and will support the development of more effective vaccine strategies to induce antigen-specific CD8 T cells
Summary
There is an urgent need for progress in developing prophylactic and therapeutic vaccination strategies that induce polyfunctional, strongly protective cytotoxic CD8 T cell responses. These could shield us from pathogens against which the presently available, neutralizing antibody-inducing vaccine approaches confer limited or no protection and they could be used to eliminate tumors or chronic infections. In contrast to this need, we currently fail to induce effector and memory CD8 T cells in numbers high enough to effectively impact an infection or the growth of tumors. As protective CD8 T cell responses are readily generated during several viral infections, we need to improve our insight into how pathogen protection is naturally achieved, identify why immune protection sometimes fails, and use this knowledge to develop novel vaccine strategies. We will use a well balanced approach of hypothesis stimulated and unbiased multisystem observations to exploit novel mechanisms and to find ways to augment the CD8 T cell response to a vaccine. We have established model systems that are uniquely suited to extract and test molecules that determine T cell differentiation and expansion magnitude. Along with that we aim to enhance our insight of immune responses in vaccinated individuals to prevent creating situation in which vaccines fail to confer protection or may cause adverse effects. We recently made very unexpected observations that challenge our current concept of T cell differentiation in chronic infections, which proposes that T cells terminally differentiate and become senescent. We therefore aim to redefine our understanding of T cell responses in such infections. This will also be pursued to unravel novel strategies to reactivate T cells in persisting infections. Overall, the project will strongly further our insight into CD8 T cell responses during infections and will support the development of more effective vaccine strategies to induce antigen-specific CD8 T cells
Max ERC Funding
1 499 850 €
Duration
Start date: 2013-10-01, End date: 2018-09-30
Project acronym QMULT
Project Multipartite Quantum Information Theory
Researcher (PI) Matthias Christandl
Host Institution (HI) KOBENHAVNS UNIVERSITET
Call Details Starting Grant (StG), PE6, ERC-2013-StG
Summary Quantum information theory studies the way information is stored, transmitted and processed in quantum devices. Mathematically, quantum information theory extends Shannon's theory of information but differs from it by allowing both for stronger correlations known as entanglement and for non-commutative effects resulting in measurement uncertainty as required by the laws of quantum physics. Entanglement has been shown to be crucial for the advantages offered by quantum communication and computation.
In recent years, researchers have gained a good understanding of quantum information theory involving two parties, for instance in the transmission of quantum bits from a sender to a receiver. Yet the study of quantum protocols for communication tasks involving multiple parties, for instance the joint counting of online votes or the compression of data distributed in a network, is still in its infancy. The reason for this is two-fold: (i) a lack of understanding of entanglement among multiple particles and (ii) the non-commutative nature of quantum theory, two facts that pose major difficulties for the design of multiparty quantum coding schemes.
It is the goal of this research project to overcome these two main obstacles so that a comprehensive theory of quantum information can be developed. Just as the Internet, where a network of many interacting computers has replaced point-to-point communication channels such as phone lines, the future of quantum communication will involve communication among many parties. The multipartite quantum information theory explored in this project is therefore expected to impact not only current experiments but also our future communication infrastructure.
Summary
Quantum information theory studies the way information is stored, transmitted and processed in quantum devices. Mathematically, quantum information theory extends Shannon's theory of information but differs from it by allowing both for stronger correlations known as entanglement and for non-commutative effects resulting in measurement uncertainty as required by the laws of quantum physics. Entanglement has been shown to be crucial for the advantages offered by quantum communication and computation.
In recent years, researchers have gained a good understanding of quantum information theory involving two parties, for instance in the transmission of quantum bits from a sender to a receiver. Yet the study of quantum protocols for communication tasks involving multiple parties, for instance the joint counting of online votes or the compression of data distributed in a network, is still in its infancy. The reason for this is two-fold: (i) a lack of understanding of entanglement among multiple particles and (ii) the non-commutative nature of quantum theory, two facts that pose major difficulties for the design of multiparty quantum coding schemes.
It is the goal of this research project to overcome these two main obstacles so that a comprehensive theory of quantum information can be developed. Just as the Internet, where a network of many interacting computers has replaced point-to-point communication channels such as phone lines, the future of quantum communication will involve communication among many parties. The multipartite quantum information theory explored in this project is therefore expected to impact not only current experiments but also our future communication infrastructure.
Max ERC Funding
1 389 581 €
Duration
Start date: 2013-09-01, End date: 2019-05-31
