Bruce Ferwerda is an Assistant Professor in the Computer Science and Informatics department of the School of Engineering at Jönköping University, Sweden. Currently, he also is a researcher in the Department of Computational Perception at the Johannes Kepler University in Linz, Austria. He received his master’s degree in Human-Technology Interaction from Eindhoven University of Technology in the Netherlands and received his PhD degree in Technical Sciences from the Johannes Kepler University in Austria. In between his master’s and PhD studies, Bruce studied at Yonsei University in Seoul, South-Korea, and worked as a researcher at the Human-Computer Interaction, and the Cognitive Science departments. He was also visiting researcher at the Ubiquitous and Distributed Computer Department of Waseda University, Tokyo, Japan, and at the Donald Bren School of Information and Computer Sciences of the University of California, Irvine, USA. His current research interest is in revealing and improving user experiences. By conducting user studies as well as analyzing (online) behavioral patterns (e.g., social media) an understanding is created about the user’s behavior, preferences, and needs. These understandings are used to create user models for personalization in systems.

Markus Schedl is an Associate Professor at the Johannes Kepler University Linz / Department of Computational Perception. He graduated in Computer Science from the Vienna University of Technology and earned his Ph.D. in Computer Science from the Johannes Kepler University Linz. Markus (co-)authored more than 150 refereed conference papers and journal articles on topics of information retrieval, web mining, multimedia, music information research, and recommender systems. Since 2007, Markus has been giving several lectures, among others, "Music Information Retrieval", "Exploratory Data Analysis", "Multimedia Search and Retrieval", "Learning from User-generated Data", "Multimedia Data Mining", and "Intelligent Systems". He further spent several guest lecturing stays, among others at the Universitat Pompeu Fabra, Barcelona, Spain, the Queen Mary, University of London, UK, and the Kungliga Tekniska Högskolan, Stockholm, Sweden.

Mirna Adriani received her PhD in Computer Science from Glasgow University in Scotland UK. She has interest in text (cross-language information retrieval, summarization, question answering etc.) and multimedia Information Retrieval (such as music and speech processing). She also works on local language and traditional music processing (such as Javanese and Balinese language and music processing). Currently she is the head of the Information Retrieval Lab in the Faculty of Computer Science, Universitas Indonesia.

Peter Knees is an Assistant Professor of the Faculty of Informatics, Institute of Software Technology and Interactive Systems of the TU Wien, Austria. He holds a Master's degree in Computer Science from the TU Wien and a Ph.D. degree from the Johannes Kepler University Linz. He (co-)authored over 90 publications including the book "Music Similarity and Retrieval" and serves as program committee member and reviewer for several conferences and journals relevant to the fields of music, multimedia, and text IR, including ISMIR, ACM Multimedia, ICMR, and IUI, and has organized workshops at ICME, ISM, WWW, SIGIR, ICDM, CHI, and UMAP. He is an experienced teacher of graduate-level courses on multimedia retrieval, recommender systems, and AI in popular culture and has given tutorials and lectures on music IR at ECIR, SIGIR, and RuSSIR.. In addition to music and web information retrieval, his research interests include multimedia, user interfaces, recommender systems, and digital media arts. From 2013 to 2016, he was PI for Johannes Kepler University in the EU-FP7 project GiantSteps, which investigated new music production tools combining music information retrieval with interface and human-computer interaction research. Currently, he is leading the project SmarterJam, dealing with recommendation in online music jam communities.

Thomas Lidy has a long-standing experience in audio analysis and Music Information Retrieval, which he has gathered in more than 12 years of working in this domain as a researcher at the Vienna University of Technology in an international context. His research expertise is on extracting features and semantic parameters such as rhythm, genre, and mood from audio content as well as Machine Learning for automatic classification of music and clustering and visualization of large music collections. He is the author of 40 articles, book chapters and papers at refereed international workshops and conferences. Thomas participated actively in the annual MIREX music retrieval benchmarking initiative, achieving top positions multiple times. Most recently, Thomas has a strong focus on Deep Learning for audio, winning 3 benchmark contests in the last 2 years (MIREX, DCASE) with novel neural network based approaches. Thomas was also a co-organiser of the ECDL 2005, ISMIR 2007 and iPres 2010 conferences as well as Waves Vienna Music Hackday 2015 to 2017 and is the co-host of the Vienna Music Technology and Vienna Deep Learning Meetup groups. In 2008, Thomas had founded Spectralmind, an innovative music technology company that created both professional music search products and mobile apps for visual music discovery. Currently he is the Head of Machine Learning at Musimap, a startup providing a large-scale human+AI based music recommender and search engine.

Yohanes Stefanus is a Lektor Kepala (Associate Professor) at the Faculty of Computer Science, University of Indonesia. His research expertise is in Computer-Aided Geometric Design, Wavelet-Transform-based Techniques, and Computational Logic. He also works on Machine Learning and Symbolic Computation. He holds a M.Math. degree and a Ph.D. degree in Computer Science from the University of Waterloo, Canada.