Robotics & Artificial Intelligence

Prof. Nadja Klein
Faculty of Economics and Business Administration

Emmy Noether Research Group in Statistics and Data Science

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Expertise

Professor Klein is an expert in statistics, and her research has been successfully used in many interdisciplinary applications, including the fields of medicine, ecology, life sciences, and economics. 

Her research interests cover those on Bayesian Computational Methods and Bayesian Deep Learning, which allow for uncertainty quantification and better interpretability in several model classes, but are also scalable to large data sets and highly-parameterized models.

Beyond that Prof. Klein also works in distributional regression models, which are particularly useful in analysing complete distributions of quantities of interest in the presence of complex associations with influential variables. These models also allow to model dynamics in space and time, thus relating her research to spatial statistics.

Furthermore, Prof. Klein works on general smoothing and shrinkage methods in the context of statistical and machine learning as well as on network analysis.

 

  • Newsenselab: Transferbonus for analyses of migraine data
  • Zalando: Master thesis on Bayesian models in e-commerce
  • Deutsche Kreditbank AG
  • Lufthansa Technik AG
  • since 2021:  Experiment (Volkswagenstiftung)
  • 2019–2020: Transferbonus with Newsenselab (Humboldt Innovation GmbH)
  • since 2019:  Emmy Noether Research Group
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Profilbild Professor Akbik
Faculty of Mathematics and Natural Sciences
Department of Computer Science

Chair of Machine Learning

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Expertise

Prof. Dr. Alan Akbik conducts research in the field of machine learning (ML) and natural language processing (NLP). His goal is to enable machines to capture, understand, and use natural language like a human.

To this end, he has developed one of the world's leading deep learning frameworks for NLP, which is already being used in over 1,000 research and industrial projects.

https://indd.adobe.com/view/d0350ae0-6591-4f69-ad02-6d2508979a8f

Scientific Services

Consulting in:

  • Deep Learning
  • Natural Language Processing (NLP)
  • Machine Learning (ML)
  • 3 Patents at IBM Research
  • Zalando Outstanding Achievement Award
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Profilbild Bojdys
CC BY 4.0
Faculty of Mathematics and Natural Sciences
Department of Chemistry

Functional Nanomaterials

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Expertise

Professor Bojdys research focuses on the design of covalent organic polymers with applications as organic transistor devices and on light-reactive polymers (e.g., Nat. Commun. 2019. DOI: 10.1038/s41467-019-11264-z). He and his team cooperate with established battery and coating companies and with a Berlin SME.

Recently, Professor Bojdys and his team successfully licensed their patent for high capacitance anodes (WO2020DE100294, DE102019110450), built from their materials. They aim to further develop their technology with industrial partners within the newly established European Innovation Council (EIC).

Since 2018, Professor Bojdys has been a member of the "Young Scientists" at the World Economic Forum (WEF) and further serves on their advisory board since 2019.

Scientific Services
  • Gas sorption analysis: Quantachrome Instruments Autosorb IQ (probegases: N2, Ar).
  • Robotic synthesis & formulation: ChemSpeed ASW 2000
  • X-ray diffractometers (Cu and Mo radiation, transmittance, Bragg-Brentano and reflectonomy configuration).
  • WO/2020/216408 - RECHARGEABLE LITHIUM-ION BATTERY ANODE, AND METHOD FOR PRODUCING A RECHARGEABLE LITHIUM-ION BATTERY ANODE
  • WO/2016/027042 - TWO-DIMENSIONAL CARBON NITRIDE MATERIAL AND METHOD OF PREPARATION
  • ERC Proof of Concept Grant (Ultra-high energy storage Li-anode materials - LiAnMAT)
  • ERC Starting Grant (Beyond Graphene Materials - BEGMAT)
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Profilbild Schlingloff
Faculty of Mathematics and Natural Sciences
Department of Computer Science

Software Engineering

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Expertise

Our daily life more and more depends on computational systems embedded in common appliances. Just think of advanced driver assistance systems in cars, medical devices, or indsutrial supervisory control and data acquisition systems. Since such systems also realise safety-critical tasks, it is all the more important to provide effective and efficient quality assurance for them. The specification, verification and testing theory group researches methods for model-based development and model checking, logical verification, and automated testing of safety-critical software. Prog. Schlingloff is chief scientist of the system quality center at Fraunhofer FOKUS, Berlin, and chairman of the boards of GFaI e.V. and ZeSys e.V.

  • Major German company for communication and sensors: Student semester project for the design and implementation of a system for distributed control of indoor air quality.
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Profilbild Pinkwart
Faculty of Mathematics and Natural Sciences
Department of Computer Science

Computer Science Education / Computer Science and Society

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Expertise

Prof. Pinkwart’s research group investigates a range of topics including adaptive educational technologies, computer supported collaborative learning, computer science education methods (especially in the fields of programming and modeling), social media and cooperative systems, and socio-technical systems. In addition, they develop multimodal human-computer interaction methods using interactive surfaces, mobile devices and 3D technologies. Prof. Pinkwart is a well-known member of numerous national and international committees and projects in basic and applied research. His team can offer specialised expertise in computer-assisted education and training, especially in the field of mobile and ubiquitous learning and teaching scenarios, computer-based group learning methods, and adaptive mechanisms in e-learning. In this context, Prof. Pinkwart and his team realise numerous research projects and co-operate with several educational institutions and companies. Concerning socio-technical systems, Prof. Pinkwart’s team conducts research on issues of design, implementation and evaluation of group-oriented software applications (e.g. online communities).

Scientific Services
  • interactive table (multi-touch)
  • electronic boards
  • tablets (20x)
  • co-operation with IT companies: consulting for didactical concepts applied to online courses in the fields of media production and e-learning
  • co-operation with e-learning companies: formation of study groups in large online courses
  • co-operation with automotive supplier: designing human-machine interfaces for production machines 
  • co-operation with automotive manufacturer: multimodal control concepts for car infotainment systems
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Profilbild Leser
Faculty of Mathematics and Natural Sciences
Department of Computer Science

Knowledge Management in Bioinformatics

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Expertise

The research of Prof. Leser and his group is focused on all aspects of management, integration and analysis of heterogeneous, large and distributed data sets including natural language texts (text-mining and information extraction). This encompasses subjects such as data warehouses and ETL, graph databases, deep web and semantic web, machine learning, similarity search, scientific workflows, statistical methods of data analysis as well as methods for assessing and securing data quality. The team of Professor Leser conducts research in a variety of interdisciplinary projects, especially with colleagues from the life sciences covering the range from basic molecular biology to Systems Medicine.

https://indd.adobe.com/view/d0350ae0-6591-4f69-ad02-6d2508979a8f

Scientific Services

Very good IT-facilities:

  • several state-of-the-art parallel computer cluster (20-80 CPUs, 1 TB main memory)
  • cluster with 60+ cores
  • 50TB+ storage
  • For an IT service provider: Consultancy  and prototype development in the field of master data standardisation and integration
  • For an IT-manufacturer: Development and valuation of algorithms for analysing data quality
  • For an international pharmaceutical company: Consultancy and development of text-mining-procedures in biomarker development
  • For a medium-sized biotech company: Joint system development (partly funded by the German Federal Ministry for Economic Affairs and Energy) in the field of human genotype changes evaluation
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Profilbild Hafner
Faculty of Mathematics and Natural Sciences
Department of Computer Science

Adaptive Systems

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Expertise

Professor Hafner‘s research in Adaptive Systems is concerned with extracting principles of intelligence from biological systems and transferring them to artificial systems. We focus on the transfer of cognitive skills to autonomous robots. The challenge not only lies in building intelligent autonomous robots, but also in gaining insights into biological systems through robot experiments. Our main research themes are sensorimotor learning, internal models for prediction, attentional processes, and spatial cognition. The methodological approaches cover evolutionary algorithms, neural learning, and information theory. We use various types of mobile robots as research platforms, e.g. humanoid, mobile, flying and underwater robots, as well as software simulations. Professor Hafner is IEEE Senior Member and Principal Investigator in several projects funded by the EU.

https://indd.adobe.com/view/d0350ae0-6591-4f69-ad02-6d2508979a8f

  • Local company for automation and robotics: Student semester project for the development of a collaborative fleet management system for autonomous transport robots.
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Profilbild Grass
Faculty of Mathematics and Natural Sciences
Department of Computer Science

Wireless Broadband Communication Systems

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Expertise

Research at the chair of Wireless Broadband Communication systems within the computer engineering group focuses on communication systems for ultra-high data rates. Professor Eckhard Grass and his research group develop and investigate systems operating at ultra-high frequencies and research techniques and methods to improve the efficiency and reliability of wireless communication. The main reserach and developement focus is physical layers (PHY) and MAC layers.

Scientific Services
  • Complete toolchain for modelling, simulation, design and test of communication systems
  • Software Defined Radio (SDR) modules
  • Various FPGA platforms and toolchains for FPGA design
  • Modules for mm-wave communications
  • Measurement equipment such as oscillosocopes, spectrum analyzers, arbitrary waveform generators
  • Development of a system for high-speed wireless communication with simultaneous distance measurement for a renowned automotive supplier
  • mm-wave communication system with integrated positioning of mobile nodes for augmented reality applications for German industrial equipment supplier
  • Joint development of a system for secure wireless communication for industry 4.0 together German industry partners
  • mm-wave connections for 5G transport networks with European industry partners
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Profilbild Eisert
Faculty of Mathematics and Natural Sciences
Department of Computer Science

Visual Computing

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Expertise

The chair of Visual Computing develops new methods for the analysis and synthesis of image and video data. This includes algorithms for estimating shape, material, motion and deformation from monocular and multi-view camera systems. Both in national and international collaborations, those algorithms are exploited in applications like multimedia, VR/AR, industry, medicine, and security.

Scientific Services
  • Various cameras
  • Multispectral sensors, 3D sensors
  • Lighting and calibration systems
  • Development of new methods for automatic inspection and damage classification of sewer networks with a water supply company
  • Development of augmented reality systems for automobile production processes with a car manufacturer
  • Analysis of multispectral imaging for tissue classification in collaboration with medical technology manufacturer
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Profilbild Schmidt
Faculty of Life Sciences
Albrecht Daniel Thaer-Institute of Agricultural and Horticultural Sciences

Department of Crop and Animal Sciences, Biosystems Engineering

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Company testimonials

G.F. Schreinzer Positronik, Steinbeis GmbH & Co. KG, Steinbeis GmbH & Co. KG, Pronova Analysentechnik GmbH & Co. KG, newtec Umwelt­technik GmbH

Expertise

Biosystems engineering works at the interface between engineering and biological production processes. Prof. Schmidt and his team develop engineering solutions for a sustainable agricultural production of crops and other environmental friendly technologies. Prof. Schmidt’s research thus leads to innovative plant farming methods in greenhouses, outdoors and other intensive crop farming systems. Alternative energy supply systems (low energy greenhouses) and closed material cycles for intensive crop farming (water hygiene, sensor systems and algorithms for fully automated nutrient solution supply in closed cycles) are Prof. Schmidt’s research area. His main activity herein is the development of sensors for gas analyses, climate measurement technology and that of software supporting decision making in automation systems. Moreover, the team also provides energetic assessments in complete production systems and parts thereof as well as process analyses.

Scientific Services
  • Experimental greenhouses with energy and material flow analytics, CO2 enrichment, artificial lights and fog systems
  • Plant monitors for continuous measurement of photosynthesis, transpiration, tissue temperature, stomatal conductance, climate measurement, gas analyses (Co2, ethylene), soil moisture sensors
  • Freely programmable automation system for climate and process control in greenhouses
  • G.F. Schreinzer Positronik, Steinbeis GmbH & Co. KG: Development of an automation system for greenhouses based on measurement details of plants (Phytocontrol)
  • Steinbeis GmbH & Co. KG: National collaborative research project „The Low Energy Greenhouse“ („Zukunftsinitiative Niederigenergiegewächshaus“, ZINEG)
  • Pronova Analysentechnik GmbH & Co. KG: Development of ionselective sensors for continuous recording of ion proportion in circulating nutrient solution systems; Development of measuring device to analyse phytometric reactions in plants
  • newtec Umwelt­technik GmbH: Development of re-circulating irrigation system with reduced phytosanitary risk in greenhouses
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Profilbild Reulke
Faculty of Mathematics and Natural Sciences
Department of Computer Science

Computer Vision

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Expertise As professor of the chair of Computer Vision professor Reulke’s research is focused on classical methods of image processing and 3D reconstruction as well as modern approaches to machine learning. Typical areas of application are object detection and tracking of people and vehicles in public areas, the three-dimensional detection of environment, and the characterisation of sensors for these tasks. The applications relate to terrestrial camera systems, as well as optical sensors on airborne and space platforms. Simultaneously, we cooperate with a large number of SMEs in the Berlin area.
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Profilbild Härdle
Faculty of Economics and Business Administration
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Expertise

Prof. Haerdle’s main research interests are quantitative finance, esp. multivariate methods in banking and finance, dimension reduction techniques, and computational statistics. In his roles both as coordinator of the Collaborative Research Center “Economic Risk” (CRC 649) and director of the interdisciplinary Center for Applied Statistics and Economics (C.A.S.E.) he primarily investigates economic risks on a global scale. Prof. Haerdle’s research aims at facilitating the evaluation of such risks and to reduce uncertainty to improve economic actors’ decision-making.
Prof. Haerdle is Distinguished Visiting Professor Wang Yanan Institute for Studies in Economics (WISE) at Xiamen University, China, as well as director of the International Research Training Group “High Dimensional Non Stationary Time Series” (ITRG 1792). Among other distinctions he received the “Econometric Theory Multa Scripsit Award” in 2012.

Scientific Services
  • multivariate statistical analysis (factor analysis, cluster Analysis, etc.)
  • portfolio optimisation
  • risk management
  • hedging
  • pricing derivatives
  • functional data analysis
  • non- and semi-parametric methods
  • data visualisation
  • Ongoing cooperation with and lecturing for leading international financial institutions
  • Center for Applied Statistics and Economics (C.A.S.E.): interdisciplinary research centre with the goal to analyze and solve current complex economic problems and those arising in related fields with the help of quantitative methods and computing. Its research subjects range from weather risk, aging societies, crime to property markets
  • Collaborative Research Center “Economic Risk” (CRC 649): center of transdisciplinary research where insights from economics, mathematics and statistics converge to analyze economic risks and risk factors. The CRC offers an international platform for discussion of the latest research results and collaborations
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Profilbild Grunske
Faculty of Mathematics and Natural Sciences
Department of Computer Science

Software Engineering

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Expertise

At the Chair of Software Engineering, Prof. Grunske and his team specialise in methods of software technology relevant to the field of automated development and quality control of software systems. His work also involves probabilistic techniques on the basis of which the probable and less probable behaviour of a program can be modelled. This allows for easier discovery and correction of software anomalies. Such statistic models are used in the monitoring and debugging of programs during runtime as well as in testing software, which supports the development of safe and reliable software systems. Furthermore, Prof. Grunske develops methods that enable a precise definition of the quality requirements of software systems, the formalisation of verification conditions as well as the (technical) safety in embedded systems and process and performance management.

Scientific Services
  • Software engineering
  • Testing and verification
  • Statistics/probabilistic methods
  • Formalisation of application scenarios in cooperation with TWT GmbH: “Safe.Spec: Quality control of behaviour requirements”
  • Using software systems to derive probabilistic models that can be used as specification during the software engineering process: „EMPRESS: Extracting and Mining of Probabilistic Event Structures from Software Systems”
  • Development of evaluation methods for probabilistic models as well as machine learning based techniques for the transformation of models:  “ENSURE-II: ENsurance of Software evolution by Run-time cErtification”
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