... develops Artificial Intelligence, Machine Learning, and Deep Learning models and applications for european projects.

I am a scientist specializing in Data Analytics, Access, and Applications at SCC, with a PhD in Mathematics from the University of Porto.

Currently, I am actively involved in the AI4EOSC and iMagine projects, both dedicated to advancing services for the development of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) models and applications within the European Open Science Cloud (EOSC).

The iMagine project focuses specifically on providing services for aquatic data sciences. These initiatives build upon the technological framework established by the DEEP-Hybrid-DataCloud H2020 project, which successfully delivered the DEEP platform, enabling the efficient utilization of computing resources across pan-European e-Infrastructures.

Kontakt: Dr. Khadijeh Alibabaei

... Researches data analytics and optimization of environmental science simulations.

I work in the Data Analytics, Access and Application (D3A) department at SCC. My research focuses on data analysis and optimization of simulations of high spatial and temporal resolution from environmental sciences. For optimization, I use machine learning methods and other techniques.

Furthermore, I am involved in the VFORWaTer project, in which a virtual research environment for water and terrestrial environmental research is being developed. The goal of the research environment is to facilitate access to hydrological data, their processing and their publication.

My research interests are data mining, machine learning and software development.

Contact: Elnaz Azmi

...leads the team of the CAMMP project (Computational And Mathematical Modeling Program)

As team leader, I support the PhD students and student assistants of the CAMMP team in the organisation and implementation of CAMMP activities and related educational research. I prepared for this position by completing my PhD in mathematics education on the teaching and learning of machine learning methods for engineering students.

My own research projects deal with educational research on the accessibility of complex mathematical content and the effectiveness of different teaching-learning formats. I collaborate with researchers from other universities and institutions such as the AI-Campus.

Contact: Katharina Bata

... answers questions about the creation of KIT websites.

There are about 900 web presences at KIT, which are maintained by the respective institutes and administrative departments. For this purpose, the content management system OpenText is used, which allows easy creation and editing of web pages without programming knowledge in a uniform KIT design.

In a team of three people, I advise the editors on how to implement their ideas in OpenText and answer questions ranging from the setup of a web server to the visually appealing design of the web presence.

I also work on projects that aim to digitize business processes and integrate different software systems. For example, KIT is currently working on a research information system that compiles data on research projects, publications, and innovations in order to report them to internal and external parties.

Contact: Larissa Beinhorn

...researches and develops solutions in the field of machine learning operations (MLOps).

I am a researcher in D3A at SCC and have a PhD in Information Systems from University of Klagenfurt. Since when I joined KIT at the end of 2019, I have been actively working in EOSC-related EU projects and managing/leading different tasks. Currently, involved in two of them: AI4EOSC and Skills4EOSC.

The former aims to deliver an enhanced set of services for the development of AI, ML and DL models and applications in the EOSC. The services will make use of advanced features such as distributed, federated and split learning; provenance metadata; event-driven data processing services or provisioning of AI/ML/DL services based on serverless computing.

The latter aims to create an EOSC-ready European workforce; Skills for the European Open Science commons: creating a training ecosystem for Open and FAIR science.

Past project: EOSC-Pillar
Previous experience: 10 years in teaching Informatics subjects: Algorithms and Databases to bachelor students

Contact: Dr. Lisana Berberi

... develops web services and conceptualizes algorithms for scientific data.

I'm a Scientific Research Software Developer in the department Data Analytics, Access, and Applications (D3A) at SCC, with a master degree in Telecommuncations and Informations Systems from the National Institute of Posts and Telecommunications in Rabat, Morocco, in 2017.

Passionate about exploring emerging technologies and their applications in scientific research, I am particularly interested in leveraging innovative approaches to data analysis, modeling and visualization. Currently, I'm working on the BMBF project Data Competence for Photonic Nanotechnologies (DAPHONA) focusing on developing web services and algorithms conception for scientific data.

Contact: Kaoutar Boussaoud

...operates a monitoring architecture to collect, store and visualize data.

With a Bachelor and a Master in Informatics Engineering from University of Palermo (Italy), I am a computer scientist in the department Scientific Data Management (SDM) at SCC since 2012. Currently I am responsible for the maintenance and development of a monitoring architecture hosted at SDM to collect, store and display metrics and logs from hosts and applications mostly involved in the Large Scale Data Facility (LSDF), tape libraries and the Grid Computing Centre Karlsruhe (GridKa).

Monitoring data like server metrics (CPU/Memory/Disk/Network), storage operations (I/O Statistics) or visualizing real-time sensors data such as temperature/pressure/humidity/power consumption in server rooms are very important to provide a complete picture of availability, performance and resource efficiency.  Our monitoring architecture includes a 5-nodes cluster based on Opensearch search engine to collect logs from many sources, InfluxDB as timeseries database and Grafana as powerful visualization tool to query and visualize data using a various range of visualization components (graphs, maps, histograms…) and dynamic dashboards.

My interests are also in configuration management, big data analytics, software development, DevOps and programming in various computer languages like Bash, Java, Python, PHP, Javascript. Past projects I was involved: Global Grid User Support (GGUS) ticket system and Smart Data Innovation Lab (SDIL)

I appreciate KIT as a family-friendly employer and I take advantage of its flexible working time models and childcare facilities.

Contact: Evelina Buttitta

...researches in the Helmholtz Metadata Collaboration Platform, which aims to make data more understandable.

After the completion of a computer science master’s degree at KIT, I joined Data Exploitation Methods department (DEM) and have been working in the Helmholtz Metadata Collaboration Platform (HMC). The aim of HMC is the enrichment of data with standardized metadata, which are essential for their understanding, their finding and their re-use. This work is motivated by the large amount of unique research data that is generated in the various Helmholtz centers.

DEM is part of the HMC and I contribute to the team by the development and implementation of basic services, which form the technical basis of the platform, e.g. Collection API.

Contact: Sabrine Chelbi

... researches on artificial intelligence methods for the energy system as a Helmholtz AI consultant.

Artificial Intelligence (AI) has become a central part of our daily lives: from face-recognition algorithms for smartphones over voice-assistants like Alexa or Siri, to personalized movie recommendations on Netflix. But also scientific research has benefited immensely from the advances in AI in the past decade, leading to novel insights and innovation in many domains. As an example the development of future energy systems in order to implement the transition towards renewable energy sources and thus tackle climate change relies heavily on modern AI methods.

The goal of our Helmholtz AI consulting team is to bring expertise on state-of-the-art AI methods to research groups in the field of “Energy” all across the Helmholtz Association. As such, we offer consulting with respect to application, implementation and validation for these algorithms, and help groups to access the necessary compute resources here at SCC.

Being an AI consultant offers new prospects and challenges every day, as the applications of AI in energy research are numerous and divers: Be it the prediction of electrical load or solar surface irradiation for photovoltaic installations, or the monitoring and control of production processes for solar cells, AI can assist in understanding and improving all of them.

Contact: Dr. Charlotte Debus

I am a researcher in the department Scientific Data Management (SDM) at SCC, and I hold a PhD in Computer Science from Université de Rennes. 

Currently, I'm working in the context of NFDI4Ing and bwIDM projects, which aims to build a data transfer federation. This federation enables researchers to access and transfer data between different storage systems using their home organization's user account. By applying my experience in distributed systems and security, I contribute to the projects` goal in the SDM department.

Contact: Dr. Mozhdeh Farhadi

... supports collaboration at KIT with groupware solutions and central desktops.

Project and research groups need groupware platforms to collaborate reliably and efficiently. Such a platform is provided, among others, by the KIT team pages on our SharePoint servers. I advise and support researchers and employees in administration on the application possibilities, such as document and image libraries, appointment and task management, and simple workflows. Together with them I develop suitable solutions. I also support the Remote Desktop Service, which has its strengths when it comes to making standard software usable independent of platform and location, even over slow networks.
But not only service support is important to me, I also actively support equal opportunities at KIT.

Contact: Sabine Grindler

...conducts research & development in the field of research data management and analysis at KIT and works at her doctorate in computer philology at the TU Darmstadt.

Small humanities subjects often gain unique and detailed insights into fascinating events of human history in their research. The results of such research must be preserved in the long term, also with regard to their data, and made digitally reusable. In the so-called information infrastructure project of the Collaborative Research Center Episteme in Motion, this task is being implemented within the framework of a multifaceted interdisciplinary collaborative project of the history of knowledge with a pilot character.

As a humanities scholar and computer scientist in 'personal union', my daily project work focuses not only on research and development in the field of research data management and analysis, but also on building communicative bridges between the humanities and information science. In the context of my dissertation project with Prof. Dr. Andrea Rapp at the TU Darmstadt (Computer Philology), I also show how quantitative data analysis can be used to gain new perspectives on digitized cultural heritage by applying algorithms and tools for image segmentation and image similarity search to 16th century book illustrations.

Contact: Dr. Germaine Götzelmann

... PhD in the project Computational And Mathematical Modeling Program - CAMMP.

To apply mathematics and make it comprehensible, that is what I see as a desirable goal for mathematics education. Therefore, I decided to do a PhD in the CAMMP project after my state examination as a teacher at the KIT in mathematics and physics.

In the context of this project I am creating workshops for students in which mathematical problems are treated in an authentic and realistic way. Specifically, a workshop on the detection of the Higgs boson is to be created. A statistical analysis of the data of the Cern experiment will be carried out in order to make a well-founded decision about the existence of the Higgs particle with the help of a likelihood quotient test. Another workshop is being created on the topic of word prediction on smartphones, modeling the mathematical problem with Markov chains.

My research interests are text mining, statistical testing, Markov chains, mathematical modeling.

Contact: Stephanie Hofmann

... heads the Scientific Computing & Mathematics department.

The department Scientific Computing & Mathematics, unifies three aspects of high-performance computing. The interdisciplinary research group Computational Science and Mathematical Methods focuses on modeling and numerical methods. Researchers from SCC and the Institute for Applied and Numerical Mathematics join forces with external partners from industry and academia. Together with the DKFZ, for example, we are developing new methods to better differentiate between cancerous and healthy tissue in order to target radiation therapies more precisely and efficiently.

Experts from our Simulation and Data Life Cycle Labs support researcher groups who run simulations on our supercomputers. We help implement their models and host training sessions to get researchers started in high-performance computing.

And for the scientists of tomorrow CAMMP and Simulated Worlds offer workshops and project days for Highschool students. Together with our experts students will learn how to solve real-world problems using mathematical modeling.

Contact: Dr. Jasmin Hörter

... operates the KITnet data network together with her colleagues in the Networks and Telecommunications department.

Highly efficient and highly available data networks form the basis for successful digitization of services and up-to-date education of students with the associated teaching offer. High-performance connections to the Internet guarantee a high quality of KIT's international presence with simultaneous fast availability of documents available worldwide for researchers and students.

In addition to network hardware such as copper and fiber optic cables, routers, switches, and WLAN components, it operates remote access solutions for remote access (VPN) and essential basic services for successful network operation (firewall, DHCP). In addition, she is the central contact person for the Information Systems department for organization and operational resources in the operation of the SAP system, for Facility Management in the implementation of VoIP solutions and for network-specific questions from external service providers.

Together with her colleagues, Ms. Huck ensures a functioning 7*24 operation of the network services.

Contact: Elena Huck

I come from Delhi in India and Computer Science is my passion. With Bachelors, Masters and a PhD in Computer Science and Engineering, I joined KIT in 2022. My research interests include Data Mining, Sentiment Analysis and Opinion Mining, Machine Learning and Natural Language Processing.

In the Department Data Exploitation Methods (DEM) at SCC, I am researching new methods for research data management and analysis. Together with specialists from different disciplines, I work on the information infrastructure project of the Collaborative Research Center 'Metaphors of Religion', where I store the multilingual religious data from different time frames and provide different facilities for annotating, analysing and querying it.

Contact: Dr. Vandana Jha

... heads the research group Methods for Big Data at SCC, researches and teaches at the KIT Department of Informatics.

Since August 2024, I have been leading the newly established Methods for Big Data (MBD) research group at SCC of KIT. With a joint appointment in the Department of Informatics and the Scientific Computing Center (SCC), my research agenda at MBD focuses on developing innovative statistical and mathematical techniques that leverage Bayesian statistics and machine learning. The goal is to enhance model robustness, improve data efficiency, and quantify uncertainties in complex systems.

The MBD group is actively engaged in several high-impact projects, demonstrating the breadth and interdisciplinary nature of our research.  From a methodological perspective, we bring a unique expertise towards advancing distributional regression models for high-dimensional data via statistical learning and scalable methods to overcome limitations of existing regression methods. We are also pioneering efforts in deep learning, investigating the potential of Bayesian statistics to develop robust and data-efficient methods. Many more details about our activities and achievements can be found at our website: kleinlab-statml.github.io.

I am also an Emmy Noether Research Group Leader and have received numerous accolades, including memberships in AcademiaNet, Junge Akademie, and the Humboldt Network, awarded by the Alexander von Humboldt Foundation. I completed my doctoral studies in Mathematics at Georg-August-Universität Göttingen and later undertook a postdoctoral fellowship at the University of Melbourne as a Feodor-Lynen fellow. Before joining KIT, I was a Professor of Statistics and Data Science at Humboldt-Universität zu Berlin.

... is researching hybrid algorithms in the field of quantum machine learning.

Today's quantum computers belong to the so-called NISQ devices, since they have only a small number of qubits, which are also very error-prone. Nevertheless, the advantages over classical computers can already be investigated on this basis. In particular, the use of hybrid algorithms, where parameterizable circuits for quantum computers are trained by classical optimization methods, are promising.

My team and I are investigating such hybrid algorithms and are concerned not only with practical implementations in the area of quantum machine learning, but also with scalability and generalization for future devices and potential use cases.

I also actively advocate for the sustainable development of research software and its importance in science.

Contact: Dr. Eileen Kühn

...researches as a PhD at the research group Methods for Big Data

I joined KIT SCC as a PhD student in July 2024, as part of the Methods for Big Data research group, led by Prof. Dr. Nadja Klein. Before this, I earned a Bachelor's degree in Applied Statistics from the Communication University of China and furthered my studies in Finance and Economics as an exchange student at Feng Chia University. I graduated with a Master's degree in Statistics from the joint masters program in Berlin, a collaboration between the Technical University of Berlin, Free University of Berlin, Humboldt University of Berlin, and Charité Berlin, with a focus on quantitative economic research and data science.

My research interests are broad, encompassing causal inference, time series analysis, machine learning, and explainable artificial intelligence (XAI). Currently, I'm working on the application of semi-structured distributional regression from a Bayesian perspective to enhance the explainability of genomic prediction in the DeSBi project P5. This project integrates deep learning and statistical methods in biomedical applications, aiming to develop innovative approaches in the field.

Contact: Dingyi Lai

... enables and organizes communication and data exchange across institution boundaries.

Successful teamwork in science requires good communication and cooperation, and simple tools are necessary for this.

Besides real-time communication, asynchronous communication also plays a major role. For this purpose, I operate a mailing list server for KIT employees and students as well as a mailing list service for German scientific institutions on behalf of the DFN-Verein. In addition, I support the list owners in the administration of their mailing lists, which can also be used to send encrypted e-mails.

For collaborative editing and easy and flexible exchange of documents across university boundaries, we operate the cloud service bwSync&Share, which I am jointly responsible for coordinating.

Contact: Sabine Lorenz

... works as an experiment representative at the Grid Computing Centre Karlsruhe (GridKa).

GridKa supports four main LHC experiments (Alice, Atlas, CMS, LHCb). It is also the German regional grid computing center for non-LHC HEP experiments (Belle2, BaBar, Auger, Compass). All these experiments produce terabytes and/or petabytes of data every year, which should be stored securely and used reliably and quickly when needed.

I work as a representative of the ATLAS experiment at GridKa. My work involves communication between GridKa and the ATLAS experiment, coordinating GridKa's participation in ATLAS-specific testing of services, tracking incidents and issues, and working with GridKa experts. I am also responsible for other services in the LHC environment, not just ATLAS. This includes a wide range of tasks such as administration, maintenance, development, testing and deployment of software.

Contact: Dr. Haykuhi Musheghyan

... works in the tape group in hardware and process monitoring.

At the SCC, large amounts of data are stored in several tape libraries with tape drives on magnetic tapes (tape). For this purpose, the SCC provides extensive backup and archiving services. The data are on the one hand research data of scientists and on the other hand various data of KIT employees or their computers. I develop computer programs and graphics to monitor and optimize both the necessary hardware and the process of data storage. Furthermore, I am involved in communication and cooperation in the tape group.

At the employer KIT, I especially appreciate the support for the compatibility of work and family.

Contact: Karin Schaefer

... is a team player in the KIT Card project and a member of the bwCard project.

The KIT Card is a chip card and serves, among other things, as an ID for students and employees. Several organizational units at KIT work together so that the KIT Card can be used, for example, to open doors, pay for meals, or borrow books.

The tasks in the team are very diverse: We accompany and optimize all processes around the life cycle of the KIT Card, provide or adapt the technology and software for production, consider data protection aspects, coordinate the production and issuance of the cards, provide information, and answer user inquiries.

As one of the local coordinators for the bwCard project, I am working with the nine universities in Baden-Württemberg, with the goal of being able to use their own smart cards at all state universities. The establishment of a bwCard production community is also part of the project.

Contact: Gabriele Schramm

... is a doctoral student researching uncertainties in dose calculations for radiation therapy.

Radiation therapy is one of the most widely used forms of treatment for cancer. Optimized treatment plans related to the use of protons and carbon ions allow the dose distribution to be tailored to the tumor. However, this makes the planned dose more sensitive to errors and uncertainties, e.g. in patient positioning.

I am working on the quantification of the resulting uncertainties in the dose distribution. For this purpose I use and develop mathematical methods and implement them for use with treatment planning software. Efficient estimation of the impact of various uncertainties then allows determination of more robust treatment plans with minimal side effects for patients.

Contact: Pia Stammer

...researches how humanities and cultural studies can be enriched by research data management methods and is deputy head of the DEM department.

In the Data Exploitation Methods  (DEM) department, we research new methods for research data management and analysis. Together with expert scientists from various disciplines, we take an interdisciplinary look at research questions that were previously difficult to solve or even impossible to solve.

Especially in disciplines that have hardly worked digitally so far, for example the so-called 'small subjects' of the humanities and cultural studies, there is immense, still undecided potential of interdisciplinary research. Here we have the chance to enrich the methods and ways of working of the entire discipline.

As part of the Collaborative Research Center 980 'Episteme in Motion', in which about 50 humanities scholars are investigating the transformation of knowledge over several millennia, I am leading the information infrastructure project 'Books on the Move'. As a central task, we provide methods and tools - from sustainable storage of research data to annotation and visualization of specific phenomena - for the entire research network.

Contact: Dr. Danah Tonne

... researches as a PhD student at the interface between Data Science and Health Science.

Since summer 2020 I am doing research as a PhD student of the interdisciplinary graduate school HIDSS4Health in the interface between Data Science and Health Science. My focus is on improving automatic segmentation algorithms needed in tumor therapy to calculate each individual radiation plan.

For this project, I am associated with both the Computational Science and Mathematical Methods (CSMM) group at KIT and the Computational Patient Models group at the German Cancer Research Center. I received my master's degree in computer science from the University of Tübingen.

My research interests are machine learning, image segmentation and optimization.

Contact: Alexandra Walter

... works as a Helmholtz AI Consultant on artificial intelligence methods for energy research.

After graduation in physics from KIT and completing my PhD in computational biophysics at SCC, I switched to computer science as a research associate. Together with my colleauges, I work together with my colleagues on artificial intelligence (AI) methods for the energy system of tomorrow. AI is a growing component in our everyday lives, taking on increasingly important tasks in our digital society, besides tailored music recommendations on Spotify and personalized shopping ads on Instagram & Co. The application areas in energy research are as diverse as the field itself and range from load forecasting for energy systems and the development of new materials for batteries to the automated control of industrial plants.

Helmholtz AI's consulting concept is designed to enable scientists in the Helmholtz Association to use cutting-edge AI methods for their own research. As Helmholtz AI Consultants, we provide support with our expertise in AI methods and software engineering for concrete research projects. This interdisciplinary work is very diverse and offers, in addition to exciting research questions, many opportunities to learn new things and to get in touch with researchers beyond disciplinary boundaries.

Contact: Dr. Marie Weiel