machine learning

Events

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Wednesday, October 09th - Tursday, November 14th 2024

KI und Wir

various places

Die Veranstaltungsreihe beschäftigt sich in diesem Herbst unter dem Titel KI und Wir mit den rasanten und grundlegenden Veränderungen unserer Gesellschaft durch künstliche Intelligenz.

Vom 9. Oktober bis zum 14. November diskutieren Expert:innen aus Wissenschaft, Politik und Praxis mit dem Hamburger Publikum über das Potenzial von ChatGPT und Co. Wie können die neuen Technologien Medizin und Klimaschutz voranbringen oder auch in der Kunst genutzt werden? Wo kann KI beim Lernen in Schule, Hochschule und darüber hinaus unterstützen? Welche Regulierungen oder Transparenzvorschriften brauchen wir dabei? Um diese und andere Fragen geht es in vielfältigen Formaten von Podiumsdiskussionen über Ausstellungen bis hin zu interaktiven Workshops, die zum

Mitdiskutieren, Dazulernen und Ausprobieren einladen. Die Veranstaltungen finden u.a. an der Uni Hamburg statt. Viele UHH-Mitglieder tragen aktiv zum Programm bei.

Institutions

  • UHH
  • HIAS
  • Körber Stiftung
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Tuesday 28th - Thursday 30th May, 2024 | 09:00 - 12:00 a.m.

Machine Learning in Practice (intermediate level)

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

learn_bAIome offers workshops and trainings in biomedical AI/data science with tailored formats that take into account background, programming skills and intensity to provide unique, focused, and effective courses. These courses are free and open to students, clinicians, and researchers across academic institutions in Hamburg.

This workshop is open to students, researchers, and clinicians wanting to learn how machine learning is applied for biomedical datasets, the different classes of machine learning algorithms that may be used, as well as the best practices in selecting and evaluating algorithms, and their limitations.  The aim of the course is to provide concepts and tools to navigate the use of machine learning in the biomedical landscape. The course will use biological datasets and there will be hands-on components as well as discussions. Participants should already have taken an introduction to machine learning and be familiar with Python programming. The workshop will be in presence and therefore each participant should bring their own laptop (no ipads).

Topics

  • Taxonomy of machine learning algorithms
  • Linear regression, logistic regression and related methods
  • Decision trees
  • Support Vector Machines
  • Bias & Variance, curse of dimensionality
  • Representation learning
  • Neural networks and deep learning: MLPs, transformers, CNNs
  • Applications to RNAseq and imaging data

 

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Tuesday, February 13th, 2024 | 14:00 p.m.

Machine learning of MCMV infection dynamics - 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.

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

 

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Wednesday, May 31th, 2023 | 10-13

ML deployment with AWS

online

Tentative agenda for the AWS Immersion Day on May 31st

Time

Title

Type

10:00 am

Introduction to ML on AWS: Amazon SageMaker and managed services.

Presentation

10:30 am

Training and Deploying models on Amazon SageMaker

Presentation

11:00 am

Account claiming and first lab

LAB

11:45 am

Break

 

12:00 pm

Second Lab

LAB

12:40 pm

Advanced topics (MLOps), and final Q&A

Presentation

It will be assumed that participants know basic Python, know how to work on a Jupyter Notebook, understand basic commands on libraries such as Pandas and SciKit Learn, and have a high level understanding of what is Pytorch/ Tensorflow. Each participant will be given an test AWS account that will be active until Friday afternoon so it is suggested that each participant works on its own laptop. We will do 2 labs together, but there will more labs available for those interested into doing further tests or exploring other features not covered during the 3 hours.

In order to participate, please send your first name and email address to adeline.scharfenberg@uni-hamburg.de 

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Monday, September 25tt, 2023 & Wendsday 27th, 2023 | 09.00-18.00

MLE Days 2023 - Summer School and Conference for Machine Learning in Engineering

Hamburg University of Technology (TUHH)

On September, 25th to 27th, 2023 the third MLE Days on machine learning in engineering will take place on the campus of the Hamburg University of Technology (TUHH). This year, it combines a summer school with a one-day startup-challenge. Participation is free of charge.

The Summer School teaches insights into the world of machine learning with a focus on engineering. It provides sessions about fundamentals of machine learning, concrete application examples, as well as hands-on sessions to try out and consolidate lessons learned. Keynote talks complete the program. Three parallel tracks are provided to allow participants to choose contributions adapted to their interest and machine learning experience. The use cases range from sensor and image processing, to electrical engineering and materials science, to aviation and maritime logistics. A poster session and an elevator pitch event allow participants to present their own work on machine learning topics. The best posters and pitches will be selected by a jury and awarded prizes. A networking event allows attendees to establish contacts with selected corporate partners and sponsors from start-ups and medium-sized businesses to large corporations. In the startup-challenge attendees learn how to turn machine learning ideas into a business.

The MLE Days are organized by the Machine Learning in Engineering research initiative of the TUHH (MLE@TUHH) in collaboration with the Helmholtz Center Hereon, DASHH, and the Career Center of TUHH, the AI.Startup.Hub, and AI.HAMBURG. The MLE initiative joins the competencies in the field of machine learning at the Hamburg University of Technology with the goal of transferring knowledge towards business and industry. Students, PhD students, postdocs, and professors from all disciplines of the TUHH are engaged together with colleagues from the Helmholtz Center Hereon to make methods and applications of machine learning known, to network, and to foster scientific exchange.

Join us to discover the new applications of machine learning in engineering practice!

Institutions

  • Hamburg University of Technology (TUHH) 
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Tuesday, April 1th, 2025 | 09:00 - 17:00

MLE Days 2025

TUHH, Building H, mainly room H 0.16

The event will feature presentations MLE members and partners, as well as networking opportunities. Its primary objective is to foster stronger connections and collaborations within the MLE network and with strategic partners.
Further details will be provided in due course.

Join us to discover the new applications of machine learning in engineering practice!

Institutions

  • Hamburg University of Technology (TUHH) 
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Tuesday, January 16th, 2024 | 18:15 p.m.

Paper Dragon or Machine Tamer: the AI Act’s Approach to Solving Ethical and Societal Concerns Around Generative AI

hybrid: on-site at ESA 1, W 221 or via webinar access

With the launch of ChatGPT last year and the ensuing debate about the benefits and potential risks of generative AI, also the work on the European AI Act shifted into a higher gear. The European Council and Parliament, working on their respective compromise texts, had to find ways to accommodate this new phenomenon. The attempts to adapt the AI Act went hand in hand with a lively public debate on what was so new and different about generative AI, whether it raised new, not yet anticipated risks, and how to best address a technology whose societal implications are not yet well understood. Most importantly, was the AI Act outdated even before is adopted? In my presentation I would like to discuss the different approaches that the Council and Parliament adopted to governing Generative AI, the most salient points of discussion and the different approaches proposed to solve some of the key ethical and societal concerns around the rise of generative AI.

Prof. Dr. Natali Helberger (Universiteit van Amsterdam, NL)
Natali Helberger is Distinguished University Professor of Law and Digital Technology, with a special focus on AI, at the University of Amsterdam and a member of the Institute for Information Law (IViR). Her research on AI and automated decision systems focuses on its impact on society and governance. Helberger co-founded the Research Priority Area Information, Communication, and the Data Society, which has played a leading role in shaping the international discussion on digital communication and platform governance. She is a founding member of the Human(e) AI research program and leads the Digital Transformation Initiative at the Faculty of Law. Since 2021, Helberger has also been director of the AI, Media & Democracy Lab, and since 2022, scientific director of the Algosoc (Public Values in the Algorithmic Society) Gravitation Consortium. A major focus of the Algosoc program is to mentor and train the next generation of interdisciplinary researchers. She is a member of several national and international research groups and committees, including the Council of Europe's Expert Group on AI and Freedom of Expression.

Institutions

  • UHH
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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, January 27th, 2024 | 18:15 - 19:45 p.m.

Public Lecture Series: Taming the Machines. A Fallibilist Approach to AI Value Alignment

UHH, Main Building, ESA 1 Ost Raum O221
Artificial Intelligence (AI) technologies have become central to numerous aspects of our lives, and are significantly reshaping them. These include our homes, our workplaces, industries in general, schools and academia, but also government, law enforcement and warfare. While AI technologies present many opportunities, they have also been shown to reinforce existing injustices, to threaten human rights, and to exacerbate the climate crisis. This begs the question: How can we collectively and meaningfully shape the digital society we live in, and who is to decide on the agenda? 
This lecture series invites viewpoints from different relevant disciplines to explore how we can preserve and advance human values through the development and use of AI technologies. Key questions include: How does AI impact our fundamental social, political, and economic structures? What does it mean to lead a meaningful life in the AI age? What design and regulatory decisions should we make to ensure digital transformations are fair and sustainable?  
To explore these and other related questions, this public lecture series invites distinguished international researchers to present and discuss their work. To get the latest updates and details how to attend the lectures, please visit http://uhh.de/inf-eit.
 

Prof. Dr. Ibo van de Poel, Delft University of Technology, NL

Value alignment is important to ensure that AI systems remain aligned with human intentions, preferences, and values. It has been suggested that it can best be achieved by building AI systems that can track preferences or values in real-time. In my talk, I argue against this idea of real-time value alignment. First, I show that the value alignment problem is not unique to AI, but applies to any technology, thus opening up alternative strategies for attaining value alignment. Next, I argue that due to uncertainty about appropriate alignment goals, real-time value alignment may lead to harmful optimization and therefore will likely do more harm than good. Instead, it is better to base value alignment on a fallibilist epistemology, which assumes that complete certainty about the proper target of value alignment is and will remain impossible. Three alternative principles for AI value alignment are proposed: 1) adopt a fallibilist epistemology regarding the target of value alignment; 2) focus on preventing serious misalignments rather than aiming for perfect alignment; 3) retain AI systems under human control even if it comes at the cost of full value alignment.

Institutions

  • UHH
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Tuesday, December 09th, 2024 | 18:15 - 19:45 p.m.

Public Lecture Series: Taming the Machines. AI and the Future of Work

UHH, Main Building, ESA 1 Ost Raum O221
Artificial Intelligence (AI) technologies have become central to numerous aspects of our lives, and are significantly reshaping them. These include our homes, our workplaces, industries in general, schools and academia, but also government, law enforcement and warfare. While AI technologies present many opportunities, they have also been shown to reinforce existing injustices, to threaten human rights, and to exacerbate the climate crisis. This begs the question: How can we collectively and meaningfully shape the digital society we live in, and who is to decide on the agenda? 
This lecture series invites viewpoints from different relevant disciplines to explore how we can preserve and advance human values through the development and use of AI technologies. Key questions include: How does AI impact our fundamental social, political, and economic structures? What does it mean to lead a meaningful life in the AI age? What design and regulatory decisions should we make to ensure digital transformations are fair and sustainable?  
To explore these and other related questions, this public lecture series invites distinguished international researchers to present and discuss their work. To get the latest updates and details how to attend the lectures, please visit http://uhh.de/inf-eit.
 

Prof. Dr. Kate Vredenburgh, London School of Economics, GB

Current AI regulation in the EU and globally focus on trustworthiness and accountability, as seen in the AI Act and AI Liability instruments. Yet, they overlook a critical aspect: environmental sustainability. This talk addresses this gap by examining the ICT sector's significant environmental impact. AI technologies, particularly generative models like GPT-4, contribute substantially to global greenhouse gas emissions and water consumption.
The talk assesses how existing and proposed regulations, including EU environmental laws and the GDPR, can be adapted to prioritize sustainability. It advocates for a comprehensive approach to sustainable AI regulation, beyond mere transparency mechanisms for disclosing AI systems' environmental footprint, as proposed in the EU AI Act. The regulatory toolkit must include co-regulation, sustainability-by-design principles, data usage restrictions, and consumption limits, potentially integrating AI into the EU Emissions Trading Scheme. This multidimensional strategy offers a blueprint that can be adapted to other high-emission technologies and infrastructures, such as block chain, the meta-verse, or data centers. Arguably, it is crucial for tackling the twin key transformations of our society: digitization and climate change mitigation.

Institutions

  • UHH
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Tuesday, June 04th, 2024 | 18:15 - 19:45 p.m.

Public Lecture Series: Taming the Machines. Ethics in the Age of Generative AI

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

Taming the Machines — Horizons of Artificial Intelligence. The Ethics in Information Technology Public Lecture Series

This summer‘s „Taming the Machine“ lecture series sheds light on the ethical, political, legal, and societal dimensions of Artificial Intelligence (AI).
This lecture series brings together perspectives from ethics, politics, law, geography, and media studies to assess the potential for preserving and developing human values in the design, dissemination, and application of AI technologies. How does AI challenge our most fundamental social, political, and economic institutions? How can we bolster (or even improve) them in times of technological disruption? What regulations are needed to render AI environments fairer and more transparent? What needs to be done to make them more sustainable? In what sense could (and even should) we hold AI accountable?
To explore these and other related questions, this public lecture series invites distinguished international researchers to present and discuss their work. To get the latest updates and details how to attend the lectures, please visit http://uhh.de/inf-eit.

Prof. Dr. Louise Amoore, Durham University, Durham, UK

Institutions

  • UHH
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Tuesday, July 09th, 2024 | 18:15 - 19:45 p.m.

Public Lecture Series: Taming the Machines. Frontier AI Regulation: from Trustworthiness to Sustainability

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

Taming the Machines — Horizons of Artificial Intelligence. The Ethics in Information Technology Public Lecture Series

This summer‘s „Taming the Machine“ lecture series sheds light on the ethical, political, legal, and societal dimensions of Artificial Intelligence (AI).
This lecture series brings together perspectives from ethics, politics, law, geography, and media studies to assess the potential for preserving and developing human values in the design, dissemination, and application of AI technologies. How does AI challenge our most fundamental social, political, and economic institutions? How can we bolster (or even improve) them in times of technological disruption? What regulations are needed to render AI environments fairer and more transparent? What needs to be done to make them more sustainable? In what sense could (and even should) we hold AI accountable?
To explore these and other related questions, this public lecture series invites distinguished international researchers to present and discuss their work. To get the latest updates and details how to attend the lectures, please visit http://uhh.de/inf-eit.

Prof. Dr. Philipp Hacker, European University Viadrina, Frankfurt (Oder), D
 
Current AI regulation in the EU and globally focus on trustworthiness and accountability, as seen in the AI Act and AI Liability instruments. Yet, they overlook a critical aspect: environmental sustainability. This talk addresses this gap by examining the ICT sector's significant environmental impact. AI technologies, particularly generative models like GPT-4, contribute substantially to global greenhouse gas emissions and water consumption.
The talk assesses how existing and proposed regulations, including EU environmental laws and the GDPR, can be adapted to prioritize sustainability. It advocates for a comprehensive approach to sustainable AI regulation, beyond mere transparency mechanisms for disclosing AI systems' environmental footprint, as proposed in the EU AI Act. The regulatory toolkit must include co-regulation, sustainability-by-design principles, data usage restrictions, and consumption limits, potentially integrating AI into the EU Emissions Trading Scheme. This multidimensional strategy offers a blueprint that can be adapted to other high-emission technologies and infrastructures, such as block chain, the meta-verse, or data centers. Arguably, it is crucial for tackling the twin key transformations of our society: digitization and climate change mitigation.

Institutions

  • UHH
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Tuesday, December 02th, 2024 | 18:15 - 19:45 p.m.

Public Lecture Series: Taming the Machines. Frontier AI Regulation: from Trustworthiness to Sustainability

UHH, Main Building, ESA 1 Ost Raum O221
Artificial Intelligence (AI) technologies have become central to numerous aspects of our lives, and are significantly reshaping them. These include our homes, our workplaces, industries in general, schools and academia, but also government, law enforcement and warfare. While AI technologies present many opportunities, they have also been shown to reinforce existing injustices, to threaten human rights, and to exacerbate the climate crisis. This begs the question: How can we collectively and meaningfully shape the digital society we live in, and who is to decide on the agenda? 
This lecture series invites viewpoints from different relevant disciplines to explore how we can preserve and advance human values through the development and use of AI technologies. Key questions include: How does AI impact our fundamental social, political, and economic structures? What does it mean to lead a meaningful life in the AI age? What design and regulatory decisions should we make to ensure digital transformations are fair and sustainable?  
To explore these and other related questions, this public lecture series invites distinguished international researchers to present and discuss their work. To get the latest updates and details how to attend the lectures, please visit http://uhh.de/inf-eit.
 

Prof. Dr. Philipp Hacker, European University Viadrina, Frankfurt (Oder), DE

Current AI regulation in the EU and globally focus on trustworthiness and accountability, as seen in the AI Act and AI Liability instruments. Yet, they overlook a critical aspect: environmental sustainability. This talk addresses this gap by examining the ICT sector's significant environmental impact. AI technologies, particularly generative models like GPT-4, contribute substantially to global greenhouse gas emissions and water consumption.
The talk assesses how existing and proposed regulations, including EU environmental laws and the GDPR, can be adapted to prioritize sustainability. It advocates for a comprehensive approach to sustainable AI regulation, beyond mere transparency mechanisms for disclosing AI systems' environmental footprint, as proposed in the EU AI Act. The regulatory toolkit must include co-regulation, sustainability-by-design principles, data usage restrictions, and consumption limits, potentially integrating AI into the EU Emissions Trading Scheme. This multidimensional strategy offers a blueprint that can be adapted to other high-emission technologies and infrastructures, such as block chain, the meta-verse, or data centers. Arguably, it is crucial for tackling the twin key transformations of our society: digitization and climate change mitigation.

Institutions

  • UHH

People

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Johannes Lederer

Professor of Mathematics
Chair of Mathematics of Data-Driven Methods
johannes.lederer@uni-hamburg.de
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Kay Grünewald

Scientific Director, CSSB
Professor for Structural Cell Biology of Viruses
Head of Department, Structural Cell Biology of Viruses
kay.gruenewald@cssb-hamburg.de
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Lennart Wittkuhn

Postdoctoral Research Scientist
lennart.wittkuhn@uni-hamburg.de
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Philipp Neumann

Head of the container-based HPC center at HSU
IT-Gruppenleitung
philipp.neumann@hsu-hh.de
Institutions

Institutions

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Max Planck Institute for the Structure and Dynamics of Matter

Scientific Support Unit researching the use of computation to accelerate and support research. 

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MLE Machine Learning in Engineering

MLE ist eine Initiative zur Bündelung der Kompetenzen im Bereich Machine Learning an der Technischen Universität Hamburg mit dem Ziel des Wissenstransfers in Richtung Wirtschaft und Industrie.

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. 

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