GHOST Day: AMLC aims at creating a friendly and vivid space for the exchange of experiences between machine learning practitioners and, most importantly, for an effective update of knowledge in the rapidly changing discipline of data analysis.
Our speakers include recognized representatives of the scientific community publishing at top-tier global conferences such as NeurIPS or ICML, and many experts from leading companies building machine learning-based products.
With the help of prestigious machine learning research centers and companies we've manage to organize 3 editions of the conference in the past, all of which were met with astoundingly positive feedback, both from the attendees as well as speakers and partners. You can find out more details about speakers and topics from our past events by navigating the top menu bar.
This time, GHOST Day: Applied Machine Learning Conference 2023 will be held at the Lecture Center of Poznań University of Technology (Piotrowo 2, Poznań, Poland), on April 21-22. Be sure to follow our announcements on social media (scroll to the bottom for links) to get constant updates, or contact us with any questions at firstname.lastname@example.org
Mateusz Malinowski is a Staff Research Scientist at DeepMind. His current work focuses on the intersection of computer vision, natural language understanding and reinforcement learning. He received his PhD (summa cum laude) from Saarland University. During his studies, he worked at Max Planck Institute for Informatics where he pioneered research in the area of Visual Question Answering which gained wide recognition in the scientific community. He was awarded multiple rewards such as Dr.-Eduard-Martin-Preis for the best doctoral candidate at Saarland University, and DAGM MVTec for the outstanding dissertation in Machine Learning, Computer Vision, and Pattern Recognition in German-speaking countries. He gladly shares his knowledge with others as a speaker during conferences and serves as a reviewer for highly respected AI journals.
Konrad Banachewicz is a Staff Data Scientist at Adevinta and a former Data Scientist at eBay. During his 20 years of industry experience he has worked with a variety of institutions on a wide range of data analysis problems. He holds a PhD in statistics from Vrije Universiteit Amsterdam where he worked on modeling problems in credit risk. Konrad is also a double Kaggle Grandmaster and a very active community contributor who is committed to sharing his knowledge with others through articles, videos and who has published the "The Kaggle Book", a guide to machine learning for competitive data science.
"Eyke Hüllermeier is a full professor at the Institute of Informatics at LMU Munich, Germany, where he heads the Chair of Artificial Intelligence and Machine Learning. He studied mathematics and business computing, received his PhD in computer science from Paderborn University in 1997, and a Habilitation degree in 2002. Prior to joining LMU, he held professorships at several other German universities (Dortmund, Magdeburg, Marburg, Paderborn) and spent two years as a Marie Curie fellow at the IRIT in Toulouse (France). His research interests are centered around methods and theoretical foundations of artificial intelligence, with a specific focus on machine learning, preference modeling, and reasoning under uncertainty. Besides, he is interested in the application of AI methods in other disciplines, ranging from the natural sciences and engineering to the humanities and social sciences. He has published more than 400 articles on related topics in top-tier journals and major international conferences, and several of his contributions have been recognized with scientific awards. Professor Hüllermeier serves on the editorial board of leading journals in AI and machine learning and is a regular member of the program committee of major AI conferences. Currently, he also serves as president of EuADS, the European Association for Data Science."
Agnieszka Słowik is a Postdoctoral Researcher working on human-centric, inclusive and responsible AI at Microsoft Research Cambridge. Prior to joining Microsoft, she did her PhD in out-of-distribution generalisation in machine learning at University of Cambridge, with particular focus on learning from multiple training distributions and compositional generalisation. During her PhD, she did several research internships at Mila, Meta AI and Microsoft Research. She published at top machine learning venues, such as AISTATS and AAAI, and co-organised various scientific events -- most recently, ML in PL 2022, The 5th Workshop on Emergent Communication @ ICLR 2022, and Oxbridge Women in Computer Science Conference 2022. She received multiple awards for her work and volunteering, including the Wiseman Prize from the University of Cambridge Department of Computer Science and Technology, Young AI Researcher 2022 Award at Perspektywy Women in Tech Summit, and Myson College Exhibition for Personal Achievement from Lucy Cavendish College, University of Cambridge. Apart from research and engineering, she enjoys teaching, science communication, outreach activities, hiking, cross-country skiing, reading, cerebral films, travelling (36 countries and counting) and learning foreign languages.
Sebastian is an ELLIS/IMPRS-IS PhD student at the University of Tübingen. Prior to returning to academia, he conducted research in industry, where he worked as a scientist in Microsoft's Mixed Reality and AI Lab, and an AI Resident at Microsoft Research Cambridge. In a previous life, he spent several years working as a software engineer. His primary research interest lies in efficiently learning compositional representations in computer vision.
Dr. Diego Galar is a Professor in the Division of Operation and Maintenance at Luleå University of Technology (Sweden), where he coordinates several projects related to industrial AI. He was also a principal researcher at Tecnalia managing the Reliability research group and professor at Skovde holding the Volvo Maintenance chair. He is the author of more than five hundred publications in the field of maintenance and a visiting professor at several international universities.
Award-winning computer scientist and data analyst. One of the founding members of deepsense.ai. He specializes in applying data structures and algorithms in artificial intelligence.
Sebastian is a postdoctoral researcher at IDEAS NCBR and also an assistant professor at the Gdańsk University of Technology, where he earned his PhD. Previously, he was employed as an Applied Scientist at Amazon and contributed to projects such as the visual perception system for the autonomous robot Amazon Scout. He has extensive experience in a variety of computer science topics and has worked for Moody's Analytics on mathematical modeling. His research focuses on the real-world generalization and efficient computation of machine learning algorithms. In addition, he is collaborating with the Medical University of Gdańsk on a project aimed at early cancer diagnosis through the use of liquid biopsies.
Pola got her PhD in 2022 from the Technical University of Denmark doing research on probabilistic machine learning, invariance learning and AI ethics. She has recently joined AWS in Berlin as an Applied Scientist where she works on responsible AI.
Senior Research Engineer in the Machine Learning Research team at Allegro, where he works on applying and advancing NLP methods in the e-commerce domain. He obtained his PhD from the University of Warsaw, in which he focused on machine learning methods for histopathology.