AfterWork AI Talks - A week at Pennstate University

The latest workshop series offered participants exciting perspectives on current developments and challenges in the field of artificial intelligence.

Forum for current AI topics

Last week, the AfterWork AI Talks series organized by AI Grid took place, where experts from various fields shared their insights and discussed the latest trends in AI research. The workshops offered a platform for exchanging important topics and the latest developments in the field of artificial intelligence.

1. Detecting misinformation on social media

In the first workshop, Prof. Prasenjit Mitra from Penn State University spoke about early detection of misinformation on social media. He presented innovative approaches including the use of Graph Convolutional Networks (GCN) and multi-task learning to identify and analyze the spread of misinformation.

2. Fairness in society and AI

Prof. Hadi Hosseini, also from Penn State University, led the second workshop on the intersection of AI and economics, particularly in the area of collective decision-making. From resource distribution to integrating ethical considerations into AI systems, this talk offered insights into the challenges and solutions for fairness in AI.

3. Machine learning for nonlinear dynamic systems

Der dritte Vortrag, gehalten von Prof. Romit Maulik, konzentrierte sich auf die Anwendung von maschinellem Lernen zur Modellierung und Analyse nichtlinearer dynamischer Systeme, ein Bereich von großer Bedeutung für viele wissenschaftliche und technische Disziplinen.

4. LLMs & Deepfakes

In the final workshop, Prof. Dongwon Lee discussed the challenges and opportunities associated with Large Language Models (LLMs) and deepfakes. From preventative measures to recognizing texts and images generated by AI, this talk offered a deep insight into current research and future perspectives.

Unser Community-Feedback über die Digital-Workshop-Reihe

The feedback from participants underlines the importance of this type of community event: “Thank you for the interesting lectures! I haven't had any contact with the topic yet." In this way, researchers gain a broad insight into the topics of AI research and can develop important connections across the variety of topics.