Ralf Mikut

Karlsruhe Institute of Technology | KIT · Institute for Automation and Applied Informatics

We present the Real-time Accurate Cell-shape Extractor (RACE), a high-throughput image analysis framework for automated three-dimensional cell segmentation in large-scale images. RACE is 55–330 times faster and 2–5 times more accurate than state-of-the-art methods. We demonstrate the generality of RACE by extracting cell-shape information from enti...

In Energy Lab 2.0, the interplay of different forms of energy on different value chains is investigated. Novel concepts to stabilize the volatile energy supply of renewables by the use of storage systems and mainly by applying to-be-developed tools and algorithms of the information and communication technology sector are sought. Hence, a key elemen...

A new era in developmental biology has been ushered in by recent advances in the quantitative imaging of all-cell morphogenesis in living organisms. Here we have developed a light-sheet fluorescence microscopy-based framework with single-cell resolution for identification and characterization of subtle phenotypical changes of millimeter-sized organ...

Automated analysis of multi-dimensional microscopy images has become an integral part of modern research in life science. Most available algorithms that provide sufficient segmentation quality, however, are infeasible for a large amount of data due to their high complexity. In this contribution we present a fast parallelized segmentation method tha...

The development and application of data mining algorithms requires the use of powerful software tools. As the number of available tools continues to grow, the choice of the most suitable tool becomes increasingly difficult. This paper attempts to support the decision‐making process by discussing the historical development and presenting a range of...

Laser-scanning confocal microscopy of the human cornea acquires in vivoimages of corneal tissues with cellular resolution, which offers diagnostic potential for a variety of diseases. However, involuntary fixational eye movements induce motion artefacts that pose a challenge for accurate morphometric analysis and particularly for preceding image da...

Optimizing smart grid operations relies on critical decision-making informed by uncertainty quantification, making probabilistic forecasting a vital tool. Designing such forecasting models involves three key challenges: accurate and unbiased uncertainty quantification, workload reduction for data scientists during the design process, and limitation...

Renewable energies and their operation are becoming increasingly vital for the stability of electrical power grids since conventional power plants are progressively being displaced, and their contribution to redispatch interventions is thereby diminishing. In order to consider renewable energies like Wind Power (WP) for such interventions as a subs...

Forecasting the locally distributed Wind Power (WP) generation is crucial for future energy systems, demanding scalable WP forecasting models to keep pace with the increasing number of smart grid applications. Therefore, we propose AutoWP, which is a weighted ensemble of WP curves that represent different site conditions. This representation is ach...

Microfluidic Live-Cell Imaging (MLCI) generates high-quality data that allows biotechnologists to study cellular growth dynamics in detail. However, obtaining these continuous data over extended periods is challenging, particularly in achieving accurate and consistent real-time event classification at the intersection of imaging and stochastic biol...

The increasing penetration of renewable energy sources introduces significant challenges to power grid stability, primarily due to their inherent variability. A new opportunity for grid operation is the smart integration of electricity production combined with battery storages in residential buildings. This study explores how residential battery sy...

Microfluidic Live-Cell Imaging (MLCI) generates high-quality data that allows biotechnologists to study cellular growth dynamics in detail. However, obtaining these continuous data over extended periods is challenging, particularly in achieving accurate and consistent real-time event classification at the intersection of imaging and stochastic biol...

Tracking the development of living cells in live-cell time-lapses reveals crucial insights into single-cell behavior and presents tremendous potential for biomedical and biotechnological applications. In microbial live-cell imaging (MLCI), a few to thousands of cells have to be detected and tracked within dozens of growing cell colonies. The challe...

Achieving net-zero carbon emissions necessitates the major transformation of electrical grids into smart grids. In this context, urban districts play a crucial role in the flexible balancing of electricity demand and supply, which involves solving decentralized optimization problems. Such optimization problems rely on forecasts of local demand and...

Distribution system operators (DSOs) must cope with new challenges such as the reconstruction of distribution grids along climate neutrality pathways or the ability to manage and control consumption and generation in the grid. In order to meet the challenges, measurements within the distribution grid often form the basis for DSOs. Hence, it is an u...

Thermal management of power electronics and Electronic Control Units is crucial in times of increasing power densities and limited assembly space. Electric and autonomous vehicles are a prominent application field. Thermal Interface Materials are used to transfer heat from a semiconductor to a heatsink. They are applied along a dispense path onto t...

Brain organoids represent a useful tool for modeling of neurodevelopmental disorders and can recapitulate brain volume alterations such as microcephaly. To monitor organoid growth, brightfield microscopy images are frequently used and evaluated manually which is time-consuming and prone to observer-bias. Recent software applications for organoid ev...

In various applications, probabilistic forecasts are required to quantify the inherent uncertainty associated with the forecast. However, many existing forecasting methods still only generate point forecasts. Although methods exist to generate probabilistic forecasts from these point forecasts, these are often limited to prediction intervals or mus...

Measures for balancing the electrical grid, such as peak shaving, require accurate peak forecasts for lower aggregation levels of electrical loads. Thus, the Big Data Energy Analytics Laboratory (BigDEAL) challenge—organised by the BigDEAL—focused on forecasting three different daily peak characteristics in low aggregated load time series. In parti...

Unsupervised clustering of wafer map defect patterns is challenging because the appearance of certain defect patterns varies significantly. This includes changing shape, location, density, and rotation of the defect area on the wafer. We present a harvesting approach, which can cluster even challenging defect patterns of wafer maps well. Our approa...

The nanoscale arrangement of ligands can have a major effect on the activation of membrane receptor proteins and thus cellular communication mechanisms. Here we report on the technological development and use of tailored DNA origami-based molecular rulers to fabricate “Multiscale Origami Structures As Interface for Cells” (MOSAIC), to enable the sy...

Computational agents support humans in many areas of life and are therefore found in heterogeneous contexts. This means that agents operate in rapidly changing environments and can be confronted with huge state and action spaces. In order to perform services and carry out activities satisfactorily, i.e. in a goal-oriented manner, agents require pri...

The increasing number of recorded energy time series enables the automated operation of smart grid applications such as load analysis, load forecasting, and load management. However, to perform well, these applications usually require clean data that well represents the typical behavior of the underlying system. Unfortunately, recorded time series...

To successfully increase the share of renewable energy sources in the power system and for counteract their fluctuating nature in view of system stability, forecasts are required that suit downstream applications, such as demand side management or management of energy storage systems. However, whilst many forecast models to create these forecasts e...

Thermal Interface Materials (TIMs) are widely used in electronic packaging. Increasing power density and limited assembly space pose high demands on thermal management. Large cooling surfaces need to be covered efficiently. When joining the heatsink, previously dispensed TIM spreads over the cooling surface. Recommendations on the dispense pattern...

As Electric Vehicle (EV) demand increases, so does the demand for efficient Smart Charging (SC) applications. However, SC is only acceptable if the EV user’s mobility requirements and risk preferences are fulfilled, i.e. their respective EV has enough charge to make their planned journey. To fulfill these requirements and risk preferences, the SC a...

Cerebral organoids recapitulate the structure and function of the developing human brain in vitro , offering a large potential for personalized therapeutic strategies. The enormous growth of this research area over the past decade with its capability for clinical translation makes a non-invasive, automated analysis pipeline of organoids highly desi...

The workshop proceedings contain the contributions of the 33rd workshop "Computational Intelligence" which will take place from 23.11. - 24.11.2023 in Berlin. The focus is on methods, applications and tools for ° Fuzzy systems, ° Artificial Neural Networks, ° Evolutionary algorithms and ° Data mining methods as well as the comparison of methods on...

The workshop proceedings contain the contributions of the 33rd workshop "Computational Intelligence" which will take place from 23.11. - 24.11.2023 in Berlin. The focus is on methods, applications and tools for ° Fuzzy systems, ° Artificial Neural Networks, ° Evolutionary algorithms and ° Data mining methods as well as the comparison of methods on...

The workshop proceedings contain the contributions of the 33rd workshop "Computational Intelligence" which will take place from 23.11. - 24.11.2023 in Berlin. The focus is on methods, applications and tools for ° Fuzzy systems, ° Artificial Neural Networks, ° Evolutionary algorithms and ° Data mining methods as well as the comparison of methods on...

Renewable energy systems depend on the weather, and weather information, thus, plays a crucial role in forecasting time series within such renewable energy systems. However, while weather data are commonly used to improve forecast accuracy, it still has to be determined in which input shape this weather data benefits the forecasting models the most...

In the smart grid of the future, accurate load forecasts on the level of individual clients can help to balance supply and demand locally and to prevent grid outages. While the number of monitored clients will increase with the ongoing smart meter rollout, the amount of data per client will always be limited. We evaluate whether a Transformer load...

In production, quality monitoring is essential to detect defective elements. State-of-the-art approaches are single-sensor systems (SSS) and multi-sensor systems (MSS). Yet, these approaches might not be suitable: Nowadays, one component may comprise several hundred meters of the weld seam, necessitating high-speed welding to produce enough compone...

A touch-evoked response of zebrafish larvae provides information on the mechanism of the gene functional expressions. Recently, an automated system has been developed for precise and repeated touch-response experimentation with minor human intervention. To quantify the collected data, we propose a fully automated multi-larvae touch-response behavio...

In the biomedical environment, experiments assessing dynamic processes are primarily performed by a human acquisition supervisor. Contemporary implementations of such experiments frequently aim to acquire a maximum number of relevant events from sometimes several hundred parallel, non-synchronous processes. Since in some high-throughput experiments...

Nowadays, Machine Learning (ML) is experiencing tremendous popularity that has never been seen before. The operationalization of ML models is governed by a set of concepts and methods referred to as Machine Learning Operations (MLOps). Nevertheless, researchers, as well as professionals, often focus more on the automation aspect and neglect the con...

Computational agents support humans in many areas of life and are therefore found in heterogeneous contexts. This means that agents operate in rapidly changing environments and can be confronted with huge state and action spaces. In order to perform services and carry out activities in a goal-oriented manner, agents require prior knowledge and ther...

Communication is crucial for organismic interactions, from bacteria, to fungi, to humans. Humans may use the visual sense to monitor the environment before starting acoustic interactions. In comparison, fungi, lacking a visual system, rely on a cell-to-cell dialogue based on secreted signaling molecules to coordinate cell fusion and establish hypha...

The opportunistic yeast Candida albicans is the most common cause of candidiasis. With only four classes of antifungal drugs on the market, resistance is becoming a problem in the treatment of fungal infections, especially in immunocompromised patients. The development of novel antifungal drugs with different modes of action is urgent. In 2016, we...

Microfluidic droplets are an important tool for studying and mimicking biological systems, e.g., to examine with high throughput the interaction of biomolecular components and the functionality of natural cells, or to develop basic principles for the engineering of artificial cells. Of particular importance is the approach to generate a biomimetic...

Recent work uses Transformers for load forecasting, which are the state of the art for sequence modeling tasks in data-rich domains. In the smart grid of the future, accurate load forecasts must be provided on the level of individual clients of an energy supplier. While the total amount of electrical load data available to an energy supplier will i...

The Cell Tracking Challenge is an ongoing benchmarking initiative that has become a reference in cell segmentation and tracking algorithm development. Here, we present a significant number of improvements introduced in the challenge since our 2017 report. These include the creation of a new segmentation-only benchmark, the enrichment of the dataset...

The opportunistic yeast Candida albicans is the most common cause of candidiasis. With only four classes of antifungal drugs on the market, resistance is becoming a problem in the treatment of fungal infections, especially in immunocompromised patients. The development of novel antifungal drugs with different modes of action is urgent. In 2016, we...

p>As Electric Vehicle (EV) demand increases, so does the demand for efficient Smart Charging (SC) applications. How- ever, SC is only acceptable if the EV user’s mobility requirements and risk preferences are fulfilled, i.e. their respective EV has enough charge to make their planned journey. To fulfill these requirements and risk preferences, the...

p>As Electric Vehicle (EV) demand increases, so does the demand for efficient Smart Charging (SC) applications. How- ever, SC is only acceptable if the EV user’s mobility requirements and risk preferences are fulfilled, i.e. their respective EV has enough charge to make their planned journey. To fulfill these requirements and risk preferences, the...

Background Cerebral organoids simulate the structure and function of the developing human brain in vitro , offering a large potential for personalized therapeutic strategies. The enormous growth of this research area over the past decade with its capability for clinical translation makes a non-invasive, automated analysis pipeline of organoids high...

Nuclear detection, segmentation and morphometric profiling are essential in helping us further understand the relationship between histology and patient outcome. To drive innovation in this area, we setup a community-wide challenge using the largest available dataset of its kind to assess nuclear segmentation and cellular composition. Our challenge...

Ultrasonic metal welding (USMW) is a highly attractive joining technology due to high energy efficiency and solid-state joint formation. Various joining solutions for conductor materials can be realized with USMW. Still, a big challenge for complex industrial applications is an adequate process monitoring that allows to cope with inevitable and com...

Modelling, forecasting and overall understanding of the dynamics of the power grid and its frequency are essential for the safe operation of existing and future power grids. Much previous research was focused on large continental areas, while small systems, such as islands are less well-studied. These natural island systems are ideal testing enviro...

Probabilistic forecasts are essential for various downstream applications such as business development, traffic planning, and electrical grid balancing. Many of these probabilistic forecasts are performed on time series data that contain calendar-driven periodicities. However, existing probabilistic forecasting methods do not explicitly take these...

In various applications, probabilistic forecasts are required to quantify the inherent uncertainty associated with the forecast. However, numerous modern forecasting methods are still designed to create deterministic forecasts. Transforming these deterministic forecasts into probabilistic forecasts is often challenging and based on numerous assumpt...