Prof. Dr. Adrian Ulges graduated from TU Kaiserslautern. He received a diploma in computer science in 2005. In 2009, he completed his Ph.D in computer science. He has remained an active researcher at the German Research Center for Artificial Intelligence (DFKI) in Kaiserslautern Germany from 2005 till 2011. His research interests are in machine learning, computer vision, and multimedia analysis. He worked with Google as an intern in 2005, at Mountain View and as a visiting scientist in 2011 in Zurich. Since 2013, he has been a full professor at RheinMain University of Applied Sciences (HSRM), with interests in applied mathematics and machine learning. Adrian’s work has been awarded a Google Research Award in 2010, and his publication record includes over 30 peer-reviewed papers.

Prof. Dr. Ulrich Schwanecke received his Master’s degree in Mathematics and Computer Science from the Johannes Gutenberg University Mainz in 1997. From 1997 to 2000 he worked as a research assistant at TU Darmstadt from where he received his Ph.D in 2000. Subsequently, he held a postdoctoral position for one year at the Max-Planck Institute for Computer Science in Saarbrücken. From 2001 to 2003 he worked as a researcher at Daimler AG in Ulm. Since October 2003, he has been a full professor for Computer Science in the Faculty of Design -Computer Science- Media at RheinMain University of Applied Sciences.

Prof. Dr. Faisal Shafait has 15+ years of research and teaching experience in Artificial Intelligence and Machine Learning with a primary focus on computer vision and document image analysis. He completed his PhD in Computer Engineering from Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau (RPTU), Germany in 2008 with highest distinction. Currently, he is working as a Professor and is heading the Department of Computing at the School of Electrical Engineering and Computer Science (SEECS), NUST, Pakistan as well as the Deep Learning Lab (DLL) under National Center of Artificial Intelligence (NCAI), NUST, Pakistan. Dr. Shafait has made a significant international reputation in the field of Artificial Intelligence by earning 10,900+ citations with i10 and h indices of 159 and 52 (Google Scholar) respectively. He received the prestigious IAPR/ICDAR Young Investigator Award by the International Association of Pattern Recognition (IAPR) in 2019 and has recently been included in the list of the World’s Top 2% Scientists compiled by Stanford University.

Prof. Dr. Muhammad Fahim Khokhar is a Tenured Professor at the Institute of Environmental Sciences and Engineering (IESE), School of Civil and Environmental Engineering (SCEE), National University of Sciences and Technology (NUST), Islamabad, Pakistan. He serves as the Director of the Climate Change and Atmospheric Research Group (C-CARGO) at IESE-NUST. Dr. Khokhar’s research expertise spans satellite remote sensing, air quality monitoring, climate change impacts, and environmental monitoring systems. His work focuses on understanding atmospheric processes, carbon dynamics in forest ecosystems, and developing innovative approaches for climate change mitigation through environmental science and engineering. Dr. Khokhar has made significant contributions to Pakistan’s environmental research landscape and has been instrumental in advancing our understanding of carbon pools in ancient forests and their role in climate regulation.

Dr Nosheen Abid is a Postdoctoral Researcher in the Department of Computer Science and Media Technology at Malmö University in Sweden. Her current research centres on the project “Human-robot collaborative learning for ultralight electric utility vehicles”, which integrates end-to-end imitation learning and interactive machine learning to advance autonomous, human-collaborative transport systems. She completed her PhD at Luleå University of Technology, where she developed an innovative Unsupervised Curriculum Learning (UCL) framework applied to Earth-observation imagery. Since 2016, her work has spanned multiple international AI domains including remote sensing, document & image understanding, and medical image analysis, blending academic research with real-world applications. With a multidisciplinary background across AI sub-fields, Dr Abid brings unique expertise at the intersection of deep learning, computer vision, and human-robot interaction.