data science

If you are looking for the third edition of our Incubator Summer Academy, you can end your search right here! As of this year, the jointly organized summer school by the five Information & Data Science platforms Helmholtz AI, Helmholtz Imaging, HIFIS, HIDA and HMC, is rebranded to the

All platforms have teamed up to design a course program that not only covers a great variety of skills, tools, and topics in the field of Information & Data Science suitable for participants with varying degrees of previous knowledge. We created course packages and transferred them into a coordinated two-week summer school program, allowing participants to select course packages that best suit their interest and experience level.
Have a look at all course packages

The Helmholtz Summer School is open to all researchers and staff in the Helmholtz Association. Additionally, a small number of seats are reserved for Master students, doctoral and postdoctoral researchers from other research institutions and universities.
We are excited to present three specialized courses:

1. Regularization in Image Reconstruction: From Model to Data Driven Methods (Course 10)
2. Introduction to Image Registration (Course 11)
3. 3D Visualization (Course 12)

Registration will open on August 12 at noon and close on August 25, 2024. Questions? Write us at hida-courses@helmholtz.de. Agenda & Registration (registration opens August 12)

HITeC e.V. ist das Forschungs- und Technologietransferzentrum des Fachbereichs Informatik der Universität Hamburg. Aufgrund seines unabhängigen Status bietet HITeC flexible und professionelle Kooperationsmöglichkeiten. HITeC-Lösungen basieren auf neuesten Forschungsergebnissen und verschaffen Vorteile durch innovative Technologien.

Das House of Computing and Data Science (HCDS) der Universität Hamburg fördert gemeinsam mit wissenschaftlichen Partner:innen in der Metropolregion die interdisziplinäre Erforschung und Anwendung innovativer digitaler Methoden. Es unterstützt die Nutzung der Potentiale der Digitalisierung und Künstlicher Intelligenz in der Forschung und bietet einen niederschwelligen Zugang zu digitalen Methoden. Das Methodenkompetenzzentrum des HCDS ermöglicht verschiedenen Disziplinen und Projekten den Austausch und die Zusammenarbeit in den Cross-Disciplinary Labs, die an der Schnittstelle zwischen Methoden- und Anwendungswissenschaften angesiedelt sind. Darüber hinaus koordiniert das HCDS das Netzwerk "KIEZ of Computing and Data Science", eine Plattform zur Vernetzung aller Bereiche der Datenwissenschaft, Computation und maschinelles Lernen in der Metropolregion Hamburg.

Institution

• Maritimes Cluster Norddeutschland

The School of Electrical Engineering, Computer Science and Mathematics at the Hamburg University of Technology (TUHH) is pleased to share another inaugural lecture and research talk from the field of Data Science with the entire TUHH and with the public as part of its colloquium.

Program:

• Welcome
  Prof. Dr.-Ing. Irina Smirnova, Vizepräsidentin Forschung, TUHH
  Prof. Dr.-Ing. Gerhard Bauch, Studiendekan EIM, TUHH
• Inaugural Lecture “From obeying AIs to collaborative agents: a human-centric view“
  Dr. Pierre-Alexandre Murena, Human-Centric Machine Learning Institute, TUHH
• Guest talk “Towards machines that understand people”
  Dr. Andrew Howes, University of Exeter
• Get together
  Foyer, Building II, TUHH Campus

Online participation via Zoom is also possible. You will get the zoom link after registration

Once again, the five platforms Helmholtz.AI, Helmholtz Imaging, HIFIS, HIDA and HMC have teamed up to createa second edition of the Incubator Summer Academy on 18-29 September 2023! We have designed a joint program with a variety course packages covering state of the art Data Science methods and skills, as well as networking opportunities in our Summer Academy Gathertown space!

Ranging from fundamental course packages as for instance “Python”, or “Introduction to Scienctific Metadata” to advanced topics as “Machine Learning Based Image analysis”, the program offers participants to select course packages that best suit their experience levels and interests.

The Incubator Summer Academy is open to all doctoral and postdoctoral researchers in the Helmholtz Association. Additionally, a small number of seats in our workshops are reserved for Master students, doctoral and postdoctoral students from other research institutions and universities.

More detailed information and registration: https://events.hifis.net

The ISM Lunchtime Seminars are online monthly events, which take place on Thursdays, 13:00-13:30h, and are open to all interested colleagues and students. ISM researchers and guest speakers present their work during a 15 min seminar, in the English language, followed by a brief Q&A session. We are happy to announce our next speaker: Prof. Dr. Angela Relόgio, Professor for Systems Medicine and Biostatistics

Title: Timing treatment: profiling the circadian clock and optimizing treatment timing in cancer.

Abstract: The biological clock (circadian clock) regulates several aspects of physiology and behaviour and plays avital role in human health. About half of all human genes are rhythmically expressed in at least one tissue, and the time for certain activities such as sleep, exercise, or medicine intake, can be optimized based on the internal circadian rhythm. Recent studies, including work from our group have highlighted a role for clock dysregulation in several hallmarks of cancer related to cell cycle, apoptosis or metabolism. Thus, scheduling anticancer drug administration over 24h may critically impact treatment success in a drug- and patient-specific manner. Our results suggest that, in addition to clock and pharmacological gene expression, the circadian dynamics of translation and cell death, plays an important role in the timing of drug toxicity. Systems biology approaches addressing the personalization of cancer chronotherapies are needed for patient benefit, and can be used to support personalized treatment scheduling, by predicting personalized drug toxicity based on the patient’s gene or protein expression profiles

Please follow the rules below to make these seminars a success:
- Please use your real name while entering the meeting. Participants with cryptic names will not be given access to the seminar.
- Please turn off your microphone while the seminar is taking place.
- Please feel free to ask questions!
Contact information
Please contact Dr. Deeksha Malhan (deeksha.malhan@medicalschool-hamburg.de) or Dr. Annakarina Mundorf (annakarina.mundorf@medicalschool-hamburg.de) for further information.

Institutions

• MSH

Learning to Optimize: How Machine Learning Drives Decisions at Companies like Uber

Have you ever wondered why and where taxi cars wait, or how smart Uber drivers make their decisions? This talk will delve into these intriguing questions. We will explore the concept of sequential decision-making and policy classes through a hands-on approach. Using taxi services as an example, we learn how service providers can optimize their decision-making. And guess what? There´s not as much magic behind it as you might think...so prepare to be surprised!

Distinguished Lecture Series in Business Analytics & Data Science

The Distinguished Lecture Series in Business Analytics & Data Science at Kühne Logistics University (KLU) presents public lectures on selected topics in analytics, data science, and their applications across various industries, including logistics and supply chain management. Targeted at students, alumni, industry professionals, and other interested individuals, the series offers insights into the latest advancements, trends, and challenges in these fields. Attendees gain valuable knowledge on how data-driven decision-making can transform business operations and enhance efficiency in today's digital economy.

bAIome Center for biomedical AI (UKE) and Bernhard Nocht Institute for Tropical Medicine (BNITM) will host the seminar series entitled “AI in biology and Medicine”. This series aims to capture a broad audience and promote cross institutional collaboration. Our expert speakers will give an overview and insight into particular AI/data science methods being developed in key areas of biology and medicine. We will have drinks and snacks following each seminar to facilitate exchange.

Lorenz Adlung, I Medical Clinic and Polyclinic, UKE: Machine learning of MCMV infection dynamics

For further details and hybrid links, please go to the webpage AI in Biology & Medicine

Diese Veratstaltungsreihe richtet sich an Teilnehmer:innen aus den Bereichen Wissenschaft & Forschung und die öffentliche Hand. Wir möchten Sie herzlich dazu einladen, an diesem Tag anwesend zu sein und an den Diskussionen und Matchmaking Aktivitäten und einem abschließendem Worlcafé teilzunehmen. Die Veranstaltung bietet die Möglichkeit, wertvolle Kontakte zu knüpfen, Ihr Wissen zu erweitern und innovative Ideen auszutauschen. Nehmen Sie diese Gelegenheit wahr, um gemeinsam mit Expert:innen und Fachleuten aus der Branche neue Impulse auch mit Hinblick auf die UITP Summits 2025 und 2027 in Hamburg zu setzen.

Wir werden Ihnen nach der Sommerpause weitere Informationen zur Agenda und zur Anmeldung zukommen lassen. Sollten Sie bereits jetzt Fragen oder Anregungen haben, zögern Sie nicht, sich mit uns in Verbindung (pmo@new-mobility-solutions.de) zu setzen. Wir stehen Ihnen gerne zur Verfügung.

Institutions

• New Mobility Solutions GmbH, Innovations Kontakt Stelle, ARIC, Digital Hub Logistics. In Kooperation mit dem EDIH (European Digital Innovation Hub Hamburg)

Professor Bast completed her Ph.D. and Habilitation at the MPI for Informatics in Saarbrücken. She is a professor for computer science at the University of Freiburg since 2009. Her research focus is on all kinds of intelligent search in large data sets, with and without AI. The search technology developed in her group is used worldwide on a daily basis. During an extended research stay at Google, she developed a new public transport route planner for Google Maps. She has served as Dean of the Faculty of Engineering, and is still serving as Dean of Studies and Senator of the university. She was a member of the German Bundestag's Enquete Commission on Artificial Intelligence. She is a member of the committee that is responsible for the evaluation of the German Leibniz Institutes. She has received various research and teaching awards.

She is going to talk about QLever, which is a new SPARQL engine and triple store developed by her group, with several unique features. Notably, QLever is very fast, can handle hundreds of billions of triples on a standard PC, supports the incremental construction of SPARQL queries via context-sensitive autocompletion, supports SPARQL+Text queries on text linked to a knowledge graph, and supports very fast spatial joins on very large numbers of geometric objects as well as the visualization of very many such objects on a map. She will show many examples and demos, some performance comparisons with other engines, and will also take a look at what's under the hood. If time permits, she might also talk about the automatic translation of natural language questions to SPARQL queries via large language models, and about entity linking . Also a word or two about the rewards and challenges of writing and maintaining software that actually works in academia.

Institutions

• Leuphana Universität Lüneburg

The 6th preCICE Workshop will be held at the Helmut-Schmidt University of Hamburg on September 8-12, 2025. The workshop is a coming together of the preCICE community to share ideas, experiences and knowledge about using preCICE, and to learn from others in the process. Like always, we plan to have user and developer talks, hands-on training sessions, discussions with the developers about your applications and use cases, and plenty of opportunities for networking. Read more about how a preCICE workshop looks like.

The workshop will include a hands-on training course. The course is suited for both beginners and current preCICE users, since advanced topics will also be covered. We will extend the course by a new module on HPC.

In the developer talks, the maintainer team will present recent updates on dynamic meshes, mesh-particle coupling, and macro-micro coupling – to only mention a few highlights. And we will continue the standardization process of adapters and application cases, where you can help shaping the future.

Keep watching this space for updates on registration, the workshop program, and more.

Call for contributions
We are looking for talks and posters that could be beneficial for the wider preCICE community. Are you developing a new adapter (such as for G+Smo or ISSM last year)? Are you using preCICE for an exciting new application? Are you developing new methods that should not be missing from preCICE? If the answer to any of these questions was yes, we encourage you to submit a brief abstract for a 20 minutes talk. Are you revisiting one of the classical preCICE use cases? Did you already present your work in a previous workshop? Then we would be very happy to catch up with your work and we encourage you to present a poster. You do not need to submit a contribution to join this workshop. However, your contributions are very welcome!

bAIome Center for biomedical AI (UKE) and Bernhard Nocht Institute for Tropical Medicine (BNITM) will host the seminar series entitled “AI in biology and Medicine”. This series aims to capture a broad audience and promote cross institutional collaboration. Our expert speakers will give an overview and insight into particular AI/data science methods being developed in key areas of biology and medicine. We will have drinks and snacks following each seminar to facilitate exchange.

Fatemeh Hadaeghi,Institute of Computational Neuroscience, UKE

For further details and hybrid links, please go to the webpage AI in Biology & Medicine

The presentation series “Train your engineering network” (TYEN) on diverse topics of Machine Learning addresses all interested persons at TUHH, from MLE partners as well as from the Hamburg region in general and aims at promoting the exchange of information and knowledge between these persons as well as their networking in a relaxed atmosphere. Thereby, the machine learning activities within MLE, TUHH and in the wider environment shall be made more visible, cooperations shall be promoted and also interested students shall be given an insight.

Organisers:

• Mijail Guillemard
• Robert Kräuter
• Gregor Vonbun-Feldbauer
• Jens-Peter M. Zemke

The series will be continued in the summer semester 2025. If you are interested in presenting, please contact the organizers.
The lectures will be in English.

In the digital transformation of science, research data is an essential basis of the research process and as diverse as the subject cultures in which they are created and used. In data-based or data-driven research, computational methods can be used to scale and transform the research process.
As a scientist, you should store your research data in a secure technical environment using established standards and compliance with data protection regulations. When using computer-aided methods - from statistics to artificial intelligence - and in interdisciplinary research and use of innovative digital methods, you need advice from an expert.
What does this mean in concrete terms for scientific practice? The experts give concrete tips and answer your questions. In addition, the participants have the opportunity to exchange perspectives, challenges and best practice examples and to be inspired.
All interested parties are invited to find out more about the services of the Center for Sustainable Research Data Management (CRDM) and - this time also present - the House of Computing and Data Science (HCDS) at Universität Hamburg from 12 p.m.
The information event is open to the university. Registration is free. The event will take place in German.

Part 1: "Adapter Fairness": "Current natural language processing (NLP) research tends to focus on only one or, less frequently, two dimensions -- e.g., performance, privacy, fairness, or efficiency -- at a time, which may lead to suboptimal conclusions and often overlooking the broader goal of achieving trustworthy NLP. Work on adapter modules focuses on improving performance and efficiency, with no investigation of unintended consequences on other aspects such as fairness. To address this gap, we conduct experiments on three text classification datasets by either (1) finetuning all parameters or (2) using adapter modules."

Part 2: "Knowledge Distillation vs. Pretraining from Scratch under a Fixed (Computation) Budget”: "Compared to standard language model (LM) pretraining (i.e., from scratch), Knowledge Distillation (KD) entails an additional forward pass through a teacher model that is typically substantially larger than the target student model. As such, KD in LM pretraining materially slows down throughput of pretraining instances vis-a-vis pretraining from scratch. Scaling laws of LM pretraining suggest that smaller models can close the gap to larger counterparts if trained on more data (i.e., processing more tokens)—and under a fixed computation budget, smaller models are able be process more data than larger models. We thus hypothesize that KD might, in fact, be suboptimal to pretraining from scratch for obtaining smaller LMs, when appropriately accounting for the compute budget.”

Part 3: Most likely, Duc will also discuss the ideas we have for his research stay with us (~Cross-cultural Hate Speech). Feedback is highly welcome!

Short Bio

I'm a PhD student at JGU Mainz, advised by Katharina von der Wense. My research focuses on analyzing and developing techniques that balance efficiency and fairness in NLP models. While numerous approaches have been developed to enhance the resource efficiency,
 their impact on model fairness remains largely unclear. Prior to this, I completed my bachelor's degree in "Mathematics in Business and Economics", and subsequently pursued a master's degree in "Data Science" with a strong emphasis on NLP. Following the completion
 of my master's degree, I transitioned into the industry, where I worked as a data scientist in the autonomous driving field.

Institution

• UHH, BWL Faculty, Professorship of Data Science

Institutions

• MSH