EVENTS

Our events in the areas of Big Data and Research Innovation include a diverse set of topics such as Future, Strategy, Technology, Applications, and Management.

If you feel that your event or event series should be part of this event calendar, just contact us!

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Tuesday, March 05th, 2024 | 14:00 p.m.

Al for biomedical imaging: computational superresolution and more - BNITM seminar series "AI in Biology and Medicine".

BNITM, Bernhard-Nocht-Straße 74, 20359 Hamburg

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.

René Werner, Institute for Applied Medical Informatics, UKE

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

 

 

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Tuesday 05th - Thursday 07th March, 2024 | 10:00 - 17:00 a.m.

Data Literacy mit Fokus auf Dateninterpretation durch Data Mining

Campus Lehre (N55), UKE

Dr. Sonja Hänzelmann and Dr. Fabian Hausmann, Institute of Medical Systems Biology, UKE

In diesem intensiven 3-tägigen Kurs werden Sie in die Welt der Data Literacy (Die Fähigkeit, kompetent mit großen Datenmengen umzugehen) eingeführt. Der Kurs bietet eine praxisnahe Herangehensweise an biomedizinische Probleme, bei denen die Teilnehmer:innen lernen, wie sie relevante Erkenntnisse aus komplexen Datensätzen gewinnen können.

Topics:
Grundlagen der Dateninterpretation und Data Literacy: Verständnis von Schlüsselbegriffen und Konzepten im Bereich Data Literacy
Python für die Datenanalyse: Einführung in die Programmiersprache Python für Datenanalyse und -manipulation
Einführung in Data Mining-Techniken: Überblick über verschiedene Data Mining-Methoden und ihre Anwendungen im biomedizinischen Bereich.
Praktische Anwendung von Clustering, Klassifizierung und automatischer Mustererkennung
Anwendung auf biomedizinische Probleme: Bearbeitung eines ausgewählten biomedizinischen Problems durch ein Gruppenprojekt
Visualisierung und Interpretation der Ergebnisse: Effektive Kommunikation von Analyseergebnissen durch Datenvisualisierung
Interpretation und Diskussion der gewonnenen Erkenntnisse im biomedizinischen Kontext

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Tuesday, March 12th, 2024 | 14:00 p.m.

Predicting clinical response to treatment in inpatients with depression - BNITM seminar series "AI in Biology and Medicine".

BNITM, Bernhard-Nocht-Straße 74, 20359 Hamburg

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

 

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Tuesday 12th - Thursday 13th March, 2024 | 09:00 - 12:00 a.m.

Introduction to Data analysis in R

Seminar room 1.65, Center for Molecular Neurobiology Hamburg (ZMNH), Falkenried 94, 20251 HH

Dr. Behnam Yousefi, Institute of medical systems biology, UKE

This workshop is for students, researchers, and clinicians keen to learn the R programming language and data analysis relevant to biomedicine. The course is designed to be practical and comprehensive with no specific background requirements. We will focus on fundamentals of data analysis with examples of real-life data in biomedicine, such as gene expression. By the end of the course, participants will be familiar with the essentials of data analysis, including statistical tests, linear regression, principal component analysis, clustering and data visualization. The workshop will be in presence and therefore each participant should bring their own laptop (no ipads).

Topics:
Basics of R programming language
Statistical tests
Linear regression
Principal component analysis (PCA)
Clustering
Data visualization

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Wednesday, March 27th, 2024 | 16:00 -18:00 p.m.

Seminar Series Computation & Data

hybrid session: digital and at HSU

The project hpc.bw establishes the seminar series “Computation & Data” at HSU. The goal of this interdisciplinary seminar is to bring together researchers and foster exchange on the development of algorithms, methods and software. The seminar series is scheduled for the last Wednesday every month, with two presentations per hybrid session (digital and on-site at HSU).

Sebastian Brandstäter (UniBw M):  Sensitivity Analysis for Biomechanical Models

Ruben Horn (HSU): Energy Efficiency of Molecular(- Continuum) Simulations

Feel free to subscribe the seminar newsletter by sending an e-mail to info-hpc-bw@hsu-hh.de with the subject line „Subscription Seminar Computation & Data”

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Tuesday 09th & 10th April, 2024 | 09:00 - 12:00 a.m.

Introduction to Machine Learning in Python

Seminar room 1.65, Center for Molecular Neurobiology Hamburg (ZMNH), Falkenried 94, 20251 HH

Dr. Behnam Yousefi, Institute of medical systems biology, UKE

This workshop is open to students, researchers, and clinicians keen to learn the essentials of machine learning and implementing it via Python. The aim of the course is to provide a comprehensive map of machine learning (and deep learning) methods with no specific background requirements. A little background in python can be helpful, though. We will focus on fundamentals of machine learning, validation methods, linear and nonlinear models, and feature reduction. The students will also get familiarized with the Python packages of Sci-kit Learn and Pytorch. The workshop will be in presence and therefore each participant should bring their own laptop (no ipads).

Topics:
Types of machine learning: supervised and unsupervised
Validation  metrics and cross validation
Introduction to linear and nonlinear models include: Linear regression, Random forest, support vector machines, deep neural networks.
Feature reduction.
Regularization.

 

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Tuesday, April 16th, 2024 | 17:00 - 19:00 p.m.

Künstliche Intelligenz in der biometrischen Gesichtserkennung

In den letzten Jahren haben sich intelligente, KI-basierte Gesichtserkennungssysteme weltweit verbreitet und werden zunehmend in kritische Entscheidungsprozesse wie Finanzen, öffentliche Sicherheit und Forensik integriert. In diesem Vortrag wird erläutert, wie KI-basierte Gesichtserkennung funktioniert, und es werden einige der aktuellen Herausforderungen untersucht, mit denen sie konfrontiert ist.

Dr.-Ing. Philipp Terhörst: Forschungsgruppenleiter "Responsible AI for Biometrics", Uni Paderborn

Biometrische Verifikation bezeichnet die automatische Überprüfung der Identität einer Person anhand ihrer Verhaltens- und biologischen Merkmale. Unter den verschiedenen biometrischen Modalitäten ist die Gesichtserkennung eine der am häufigsten verwendeten. Sie bietet eine hohe Einzigartigkeit und lässt sich leicht in offenen Umgebungen erfassen. In den letzten Jahren haben sich Gesichtserkennungssysteme weltweit verbreitet und werden zunehmend in kritische Entscheidungsprozesse wie Finanzen, öffentliche Sicherheit und Forensik integriert. Der wachsende Einfluss dieser Systeme auf das tägliche Leben der Menschen wird durch die erhebliche Verbesserung ihrer Erkennungsleistung vorangetrieben. Diese Fortschritte basieren auf der Anpassung von KI-Techniken für die Gesichtserkennung. Allerdings gehen mit diesem Erfolg auch eine Reihe von Problemen einher, darunter Datenschutz, Fairness und Zuverlässigkeit. In diesem Vortrag wird erläutert, wie KI-basierte Gesichtserkennung funktioniert, und es werden einige der aktuellen Herausforderungen untersucht, mit denen sie konfrontiert ist.

Die Veranstaltung ist kostenfrei, aber bitte auf der HNF-Seite anmelden.

Institution

  • Universität Paderborn
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Wednesday, April 17th, 2024 | 17:00 -19:00 p.m.

Ethics in Technology and the Future of Morality

Audimax II, TUHH, Am Schwarzenberg Campus 1, 21073 Hamburg

This event will be part of TUHH’s flagship series "Lectures for Future" and marks the beginning of my appointment at TUHH as well as of our new Institute for Ethics in Technology. Prof. Dominic Wilkinson (University of Oxford), Prof. Alena Buyx (Technical University of Munich, Chair of the German Ethics Council) and Dr Andrew Graham (University of Oxford) will contribute to the event.

Programme:

  • Opening address by the President and Vice-President of Hamburg University of Technology
  • Lecture by Prof. Maximilian Kiener: (TUHH): "Ethics in Technology and the Future of Morality"
  • Input by Prof. Dominic Wilkinson (University of Oxford): "AI and the Future of Informed Consent"
  • Input by Prof. Alena Buyx (TU Munich, Chair of the German Ethics Council) "Humans and Machines"
  • Moderated discussion led by Dr Andrew Graham (University of Oxford).
  • Reception and Get-together

Institution

  • Institute for Ethics in Technology
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Tuesday, April 23th, 2024 | 14:00 p.m.

Systems Biology of Cancer - BNITM seminar series "AI in Biology and Medicine".

BNITM, Bernhard-Nocht-Straße 74, 20359 Hamburg

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.

Angela Relógio, Medical School Hamburg MSH

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

 

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Saturday, August 31th, 2024

The International Workshop on Computational Paleography (3rd edition)

Grand Hyatt Athens Hotel, Athens, Greece

Computational paleography merges computational methods with the study of ancient scripts, transcending traditional humanities boundaries through technology. It unites experts in manuscripts, computer science, and natural sciences, breaking down chronological and geographical barriers. This interdisciplinary approach allows for detailed analysis of ancient documents, benefiting from advancements in computer vision and analytical techniques. The aim is to facilitate collaboration and discussion among specialists, enhancing understanding and access to cultural heritage, thereby enriching society.
The workshop is planned for half a day with a keynote talk, oral presentations, and lively discussions. Submitted papers will be peer-reviewed and accepted submissions will be presented in the workshop and published with ICDAR proceedings in the Springer Lecture Notes in Computer Science (LNCS) series.

Institution

  • Centre for the Study of Manuscript Cultures, ICDAR, IAPR
Thursday, December 12th, 2024 | 18:15-19:45 p.m

Developing a Language to Talk About AI: AI Philosophy

UHH, Main Building, West Wing, Edmund-Siemers-Allee 1, Room 221

Prof. Dr. Vincent Cornelius Müller, Lehrstuhl für Theory and Ethics of Artificial Intelligence, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen

Taming the Machine. The Ethics in Information Technology Public Lecture Series

This semester’s edition of "Taming the Machines" explores the interrelated ethical, political, and technological aspects of Artificial Intelligence (AI) in an interdisciplinary way. 
 
AI-driven technologies are increasingly shaping the world we live in, sparking growing ethical scrutiny. As a result, it appears more and more urgent that societies collectively address how and in what way the further development of such technologies might be tangibly influenced. And, importantly, by whom this task should be advanced and according to which agendas? Ethicists, legislators, designers, and engineers, each bring distinct expertise and capacities to the multiplicity of social issues raised by these technologies, yet the perspectives and approaches they offer may or may not be complimentary or even simultaneously realisable (let alone mutually satisfactory). Amidst the rising tensions surrounding the AI driven transformation of our shared social space, particularly in the domain of governance and regulation, this lecture series asks how we might best accompany innovation in AI and realise ethically desirable future outcomes. In other words, to delve into the questions of what it means to live well in a society that is increasingly driven by AI tools? What design and regulative choices ought we make? What social infrastructures and normative frameworks might be needed for the future handling of emerging technologies? How could or should openness to innovation be reconciled with defending and developing the ideals of a free and democratic society under the rule of law? 
 
To explore these and other related questions, this public lecture series invites distinguished researchers from computer science, philosophy, and political theory to present and discuss their work. To get the latest updates and details how to attend the lectures, please visit https://www.inf.uni-hamburg.de/en/inst/ab/eit/taming-the-machines/winter23-24.html

Institutions

  • UHH, Ethik in der Informationstechnologie, Koordination: Prof. Dr. Judith Simon

Universität Hamburg
Adeline Scharfenberg
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Universität Hamburg
Adeline Scharfenberg
Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein. 

Universität Hamburg
Adeline Scharfenberg
Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein.