RESEARCH TRACK

Valuable and Responsible AI Systems

 

In the Summit research track, EAISI researchers and partners will present their latest findings, specifically around the theme of the real power of AI. In the midst of AI developments that lead to doubts or even fear, we put some necessary focus on the positive influence AI has and will have on our lives and the real world around us. Please join the discussions and get to know in detail what is happening in the center of Brainport’s AI research.

 

At EAISI 900+ AI-researchers do research on AI systems where the physical, digital, and human worlds come together. EAISI aims to get to a better understanding, better designs, better models, and better decisions in the application areas of Health, Mobility, and High-Tech Systems.

TIMETABLE

11:30  Duo presentation | Zaharah Bukhah & Kasper Hendriks
12:00  Pitches | Patricia Kahr, Andrii Kompanets & Apoorva Singh
12:20  Presentation | Fons van der Sommen
12:40  Presentation | Carlos Zednik
13:00  Lunch break & Expo
14:20  Presentation | Remco Duits
14:40  Duo presentation | Josette Gevers & Travis Wiltshire 
15:05  Duo presentation | Aaqib Saeed & Hareld Kemps
15:30  Jakub Tomczak
15:50  Elena Torta
16:15  Central closing | with mayor Jeroen Dijsselbloem
16:30  Expo, networking & drinks
18:00  End Time

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Zaharah Bukhsh (duo talk)

Assistant professor at Eindhoven University of Technology

Decision-making with deep reinforcement learning

Deep learning has revolutionized data-driven models, enabling the mastery of complex tasks by learning from vast amounts of (labeled) data.

View profile on TU/e website

Kasper Hendriks (duo talk)

Innovation engineer at Vanderlande


Decision-making with deep reinforcement learning

Deep learning has revolutionized data-driven models, enabling the mastery of complex tasks by learning from vast amounts of (labeled) data. 

View profile on LinkedIn

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Patricia Kahr

PhD Candidate in the Human-Technology Interaction group.

Performance is Not Everything! Learning What Promotes Trustworthy Human-AI Collaborations. Insights from a Case Study in Logistics Planning

An important area of research on human-AI interaction focuses on promoting trust and reliance in AI decision support systems. 

View profile on TU/e website

Andrii Kompanets

PhD Candidate at the Steel Structures group at TU/e

AI-aided visual inspection of steel bridges

Automating the current bridge visual inspection practices using drones and image processing techniques is a prominent way to make these inspections more effective, robust, and less expensive. 

View profile on TU/e website

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Apoorva Singh

PhD Candidate at the Department of Applied Physics and Science Education, TU/e

Predictive modeling of large-scale pedestrian dynamics using AI

The current research work, supported by the EAISI EMDAIR project “AICrowd”, aims at quantitatively modelling the dynamics of pedestrian crowds, using tools from AI and System Identification. 

View profile on TU/e website

Fons van der Sommen

Associate Professor Video Coding & Architectures, TU/e

Robust, self-critical AI for oncology

While the capabilities of modern AI systems keep surpassing expectations for a wide range of applications, their development has mostly driven by their accuracy on standardized data sets. 

View profile on TU/e website

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Carlos Zednik

Assistant Professor, TU/e

Cognitive models to understand knowledge-representation in large language models

Harnessing the power of large language models while retaining control over their behavior is one of the central challenges of contemporary artificial intelligence. 

View profile on TU/e website

Remco Duits

Associate Professor TU/e
Head of the Geometric Learning and Differential Geometry group, Cluster: CASA. Department: Mathematics and Computer Science. EAISI, TU/e.

New Geometric Learning for Medical and Industrial Image Analysis

Our geometrically interpretable networks achieve better classification results in image processing with both less training data and less network complexity. 

View profile on TU/e website 
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Josette Gevers (duo talk)

Full Professor TU/e

 

 


An AI-based feedback system for team support during crisis events

Wearable technology offers a groundbreaking opportunity to provide teams with real-time feedback to enhance their effectiveness in high-stakes crisis environments, such as medical emergencies. 

View profile on TU/e website

Travis Wiltshire (duo talk)

Assistant Professor in the Department of Cognitive Science and Artificial Intelligence, Tilburg University

An AI-based feedback system for team support during crisis events

Wearable technology offers a groundbreaking opportunity to provide teams with real-time feedback to enhance their effectiveness in high-stakes crisis environments, such as medical emergencies. 

View profile on Tilburg University website

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Aaqib Saeed (duo talk)

Assistant professor Industrial Design and Mathematics and Computer Science TU/e


Decentralized AI for Sensing and Health

The ubiquity of interconnected systems has given rise to a world enriched with omnipresent computing, where computing is so ingrained in our daily lives that we often fail to realize our interactions with these platforms. 

View profile Aaqib on TU/e website

Hareld Kemps (duo talk)

Full Professor Remote Patient Management in Chronic Cardiac Care / Cardiologist at Máxima Medical Center

Decentralized AI for Sensing and Health

The ubiquity of interconnected systems has given rise to a world enriched with omnipresent computing, where computing is so ingrained in our daily lives that we often fail to realize our interactions with these platforms.

View profile Maxima MC website

View profile on TU/e website

Image
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Jakub Tomczak

Associate professor TU/e

Generative AI Systems

Jakub M. Tomczak is an Associate Professor and the Head of the Generative AI group at the Eindhoven University of Technology. He serves as a Program Chair of NeurIPS 2024. He is the founder of Amsterdam AI Solutions. His research interests are Generative AI, Deep Learning and Probabilistic Modeling.

View profile on LinkedIn

Elena Torta

Assistant Professor Robotics at TU/e

Collaborative robots for real-world applications: experiences from the EAISI Impuls  research projects  AMBER and TOWR

How can we increase the level of autonomy of collaborative robots? How can we leverage prior knowledge and machine learning to improve the performance of robotic navigation systems? In this talk we are going to explore these questions and more by looking at recent research results from the EAISI Impuls projects AMBER and TOWR

View profile on LinkedIn
Image
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Zaharah Bukhsh (duo talk)

Assistant professor at Eindhoven University of Technology

Decision-making with deep reinforcement learning

Deep learning has revolutionized data-driven models, enabling the mastery of complex tasks by learning from vast amounts of (labeled) data.

View profile on TU/e website

Image

Kasper Hendriks (duo talk)

Innovation engineer at Vanderlande

Decision-making with deep reinforcement learning

Deep learning has revolutionized data-driven models, enabling the mastery of complex tasks by learning from vast amounts of (labeled) data. 

View profile on LinkedIn

Image

Patricia Kahr

PhD Candidate in the Human-Technology Interaction group.

Performance is Not Everything! Learning What Promotes Trustworthy Human-AI Collaborations. Insights from a Case Study in Logistics Planning

An important area of research on human-AI interaction focuses on promoting trust and reliance in AI decision support systems. 

View profile on TU/e website

Image

Andrii Kompanets

PhD Candidate at the Steel Structures group at TU/e

AI-aided visual inspection of steel bridges

Automating the current bridge visual inspection practices using drones and image processing techniques is a prominent way to make these inspections more effective, robust, and less expensive. 

View profile on TU/e website

Image

Apoorva Singh

PhD Candidate at the Department of Applied Physics and Science Education, TU/e

Predictive modeling of large-scale pedestrian dynamics using AI

The current research work, supported by the EAISI EMDAIR project “AICrowd”, aims at quantitatively modelling the dynamics of pedestrian crowds, using tools from AI and System Identification. 

View profile on TU/e website
Image

Fons van der Sommen

Associate Professor Video Coding & Architectures, TU/e

Robust, self-critical AI for oncology

While the capabilities of modern AI systems keep surpassing expectations for a wide range of applications, their development has mostly driven by their accuracy on standardized data sets. 

View profile on TU/e website

Image

Carlos Zednik

Assistant Professor, TU/e

Cognitive models to understand knowledge-representation in large language models

Harnessing the power of large language models while retaining control over their behavior is one of the central challenges of contemporary artificial intelligence. 

View profile on TU/e website

Image

Remco Duits

Associate Professor TU/e
Head of the Geometric Learning and Differential Geometry group, Cluster: CASA. Department: Mathematics and Computer Science. EAISI, TU/e.

New Geometric Learning for Medical and Industrial Image Analysis

Our geometrically interpretable networks achieve better classification results in image processing with both less training data and less network complexity. 

View profile on TU/e website 
Image

Josette Gevers (duo talk)

Full Professor TU/e

An AI-based feedback system for team support during crisis events

Wearable technology offers a groundbreaking opportunity to provide teams with real-time feedback to enhance their effectiveness in high-stakes crisis environments, such as medical emergencies. 

View profile on TU/e website

Image

Travis Wiltshire (duo talk)

Assistant Professor in the Department of Cognitive Science and Artificial Intelligence, Tilburg University

An AI-based feedback system for team support during crisis events

Wearable technology offers a groundbreaking opportunity to provide teams with real-time feedback to enhance their effectiveness in high-stakes crisis environments, such as medical emergencies. 

View profile on Tilburg University website

Image

Aaqib Saeed (duo talk)

Assistant professor Industrial Design and Mathematics and Computer Science TU/e


Decentralized AI for Sensing and Health

The ubiquity of interconnected systems has given rise to a world enriched with omnipresent computing, where computing is so ingrained in our daily lives that we often fail to realize our interactions with these platforms. 

View profile Aaqib on TU/e website
Image

Hareld Kemps (duo talk)

Full Professor Remote Patient Management in Chronic Cardiac Care / Cardiologist at Máxima Medical Center

Decentralized AI for Sensing and Health

The ubiquity of interconnected systems has given rise to a world enriched with omnipresent computing, where computing is so ingrained in our daily lives that we often fail to realize our interactions with these platforms.

View profile Maxima MC website

View profile on TU/e website

Image

Jakub Tomczak

Associate professor TU/e

Generative AI Systems

Jakub M. Tomczak is an Associate Professor and the Head of the Generative AI group at the Eindhoven University of Technology. He serves as a Program Chair of NeurIPS 2024. He is the founder of Amsterdam AI Solutions. His research interests are Generative AI, Deep Learning and Probabilistic Modeling.

View profile on LinkedIn

Image

Elena Torta

Assistant Professor Robotics at TU/e

Collaborative robots for real-world applications: experiences from the EAISI Impuls  research projects  AMBER and TOWR

How can we increase the level of autonomy of collaborative robots? How can we leverage prior knowledge and machine learning to improve the performance of robotic navigation systems? In this talk we are going to explore these questions and more by looking at recent research results from the EAISI Impuls projects AMBER and TOWR

View profile on LinkedIn
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MORNING PROGRAM

09:00
10:00


10:20
11:00
11:30

 

Walk in with tea/coffee
Welcome | Carlo van de Weijer
Opening with delegate
Martijn van Gruijthuijsen
Keynote | Nathan van de Wouw
Coffee break
Morning Track

AFTERNOON PROGRAM

13:00
14:15
16:15

16:30
18:00

 

Lunch break & Expo
Afternoon Track
Central closing with mayor
Jeroen Dijsselbloem
Expo, networking & drinks
End Time

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