Klaus-Robert Müller has been a professor of computer science at Technische Universität Berlin since 2006; at the same time he is directing rsp. co-directing the Berlin Machine Learning Center and the Berlin Big Data Center and most recently BIFOLD . He studied physics in Karlsruhe from 1984 to 1989 and obtained his Ph.D. degree in computer science at Technische Universität Karlsruhe in 1992. After completing a postdoctoral position at GMD FIRST in Berlin, he was a research fellow at the University of Tokyo from 1994 to 1995. In 1995, he founded the Intelligent Data Analysis group at GMD-FIRST (later Fraunhofer FIRST) and directed it until 2008. From 1999 to 2006, he was a professor at the University of Potsdam. From 2012 he has been Distinguished Professor at Korea University in Seoul. In 2020/2021 he spent his sabbatical at Google Brain as a Principal Scientist. Among others, he was awarded the Olympus Prize for Pattern Recognition (1999), the SEL Alcatel Communication Award (2006), the Science Prize of Berlin by the Governing Mayor of Berlin (2014), the Vodafone Innovations Award (2017), Pattern Recognition Best Paper award (2020). In 2012, he was elected member of the German National Academy of Sciences-Leopoldina, in 2017 of the Berlin Brandenburg Academy of Sciences and also in 2017 external scientific member of the Max Planck Society. From 2019 on he became an ISI Highly Cited researcher in the cross-disciplinary area. His research interests are intelligent data analysis and Machine Learning in the sciences (Neuroscience (specifically Brain-Computer Interfaces, Physics, Chemistry) and in industry.

Vikas Garg is currently Assistant Professor with Aalto University and FCAI. He holds a PhD in Computer Science (specialization: AI/ML/DL) from the Massachusetts Institute of Technology (MIT), USA. He has over 15 years of experience in research, teaching, engineering, product development, and supply chain management including stints at leading academic institutes, business schools, and companies such as Amazon A9, Microsoft Research, and IBM Research.

He is also Co-Founder and Chief Scientist at YaiYai Oy, a company established to provide cutting-edge AI/ML/DL based solutions to startups, governments, and leading companies across the globe in multiple sectors including Biopharma, IoT, Energy, FinTech, and Gaming.

Some of his recent innovations have led to advances in diverse domains such as protein design, multi-attribute visual search, fast inference on IoT devices such as smartphones, query recommendation and auto-completion for e-commerce platforms, drug discovery, strategic decision making in multi-agent systems, global supply chain dynamics, and design of smart grids and next generation wireless systems. He holds multiple patents and his research has been recognized at premier venues in AI, ML, NLP, Computer Vision, Automation, Energy, etc. (e.g., NeurIPS, ICML, CVPR, AISTATS, UAI, AAAI, IJCAI, TKDE, CIKM, e-Energy, and SmartGridComm).

Select honors include BP Technologies Fellowship awarded by MIT to the strongest incoming students, top ranks in competitions such as Microsoft Imagine Cup, and highest student evaluation scores for an Applied ML course that he co-designed and co-instructed at MIT. He's also been an Energy Fellow at MIT as well as active member of Machine Learning for Pharmaceutical Discovery Symposium (MLPDS), a consortium of leading pharma companies with MIT.

Sasu Tarkoma is a Professor of Computer Science at the University of Helsinki and Vice-Dean of Research at the Faculty of Science. He is also Director of the Helsinki Center for Data Science (HiDATA) and affiliated with the Helsinki Institute for Information Technology HIIT. He is Fellow of IET and EAI. He has authored 4 textbooks and has published over 200 scientific articles. He has ten granted US Patents. His research has received a number of Best Paper awards and mentions, for example at IEEE PerCom, ACM CCR, and ACM OSR. As an example flagship research project, he is leading the MegaSense project, which aims at deploying a wide array of urban air-monitoring stations and employing the data within prediction models.

Rosa Maria Ballardini is Professor of IP law and Vice Dean (research) at the University of Lapland, Faculty of Law. She holds a PhD from Hanken School of Economics, Finland (2012), an LLM in IT and IP law from the University of Edinburgh, Scotland (2005) and a law degree from the University of Brescia, Italy (2003). In 2017 Rosa was granted the title of Docent (Docentti) in Intellectual Property Law from the University of Helsinki. Previously - 2008 to 2009 - she was a Visiting Scholar at UC Berkeley/Boalt Hall.

Since 2005, she has researched and taught in the field of IP law at various universities. Prof. Rosa's research interests focus on the interface between law (with focus on IP law), technology and sustainability. Currently, she also investigates issues related to the role of empathy in law and decision making. She has written extensively especially in the fields of patent and copyright law, open innovation and open source, as well as IP strategies and IP management in various technological contexts such as software, 3D printing, artificial intelligence and industrial internet. Her research approach is multidisciplinary, combining law, technology, business and policy via using different types of methodologies (e.g. traditional legal research methods, empirical methods and design thinking in legal studies).

Rosa is a Board member of the IPR University Center, a member of the Finnish Copyright council and is part of several international associations on IPR.

Professor Ola Engkvist is head of Molecular AI in Discovery Sciences, AstraZeneca R&D. He did his PhD in computational chemistry at Lund University followed by a postdoc at Cambridge University. After working for two biotech companies he joined AstraZeneca in 2004. He currently leads the Molecular AI department, where the focus is to develop novel methods for ML/AI in drug design, productionalize the methods and apply the methods to AstraZeneca's small molecules drug discovery portfolio. His main research interests are deep learning based molecular de novo design, synthetic route prediction and large scale molecular property predictions. He has published over 100 peer-reviewed scientific publications. He is adjunct professor in machine learning and AI for drug design at Chalmers University of Technology and a trustee of Cambridge Crystallographic Data Center.

Danish Pruthi recently received his Ph.D. from the School of Computer Science at Carnegie Mellon University, where he was advised by Graham Neubig and Zachary Lipton. He is broadly interested in the areas of natural language processing and deep learning, with a focus on model interpretability. He has spent time doing research at Google AI, Facebook AI Research, Microsoft Research and Indian Institute of Science (IISc). He is also a recipient of the Siebel Scholarship and the CMU Presidential Fellowship.

Dr. Chandra Shekar Lakshminarayanan is an Assistant Professor at Department of Computer Science & Engineering, IIT Madras. He obtained his PhD from the Department of Computer Science and Automation, Indian Institute of Science (2016), and was a post-doctoral research fellow at the Department of Computing Science (July 2016- June 2017), University of Alberta, and a research scientist at DeepMind, London (August 2017-July 2018).

Juho Rousu is a Professor of Computer Science at Aalto University, Finland. Rousu obtained his PhD in 2001 from University of Helsinki, while working at VTT Technical Centre of Finland. In 2003-2005 he was a Marie Curie Fellow at Royal Holloway University of London. In 2005-2011 he held Lecturer and Professor positions at University of Helsinki, before moving to Aalto University in 2012. Rousu's main research interest is in developing principled machine learning methods, models and tools for computational and data science. Rousu's favourite topics include learning with multiple and structured targets, multiple views and ensembles. His applications of interest include metabolomics, biomedicine, pharmacology and synthetic biology.

Julius Sipilä, Head of Medicinal Chemistry at Orion Pharma R&D got his Ph.D. in Pharmaceutical Chemistry from the Faculty of Pharmacy, University of Helsinki, where he studied enzymes involved in the biotransformation of drugs and neurotransmitters. At Orion Pharma he has gained more than 15 years of experience working as research scientist in various drug discovery projects in the fields of CNS disorders and Oncology. Before taking responsibility of the Medicinal Chemistry unit, he has been leading Computational Medicine Design for several years, bringing it to the age of cloud computing and artificial intelligence. Solving medicine design challenges combining chemistry, molecular modelling and machine learning methods is his passion.

Suzan Bayhan is an assistant professor at the University of Twente (UT) in the Netherlands. Before joining the UT, she worked as a researcher at TU Berlin, University of Helsinki, and Bogazici University. She co-received the best paper award at ACM ICN 2015 and IEEE WoWMoM 2020 as well as the best demo award at IEEE INFOCOM 2020. She acted as a mentoring co-chair in N2Women board. Her current research interests include coexistence in unlicensed spectrum, edge computing, and energy efficient communications.

Martin Andraud is an assistant professor in the Department of Electronics and Nanoengineering in Aalto University, Helsinki, Finland. He received the Diploma degree in engineering, with a focus on microelectronics, from Telecom Physics Strasbourg, France, in 2012, the M.S. degree in micro- and nano-electronics from Strasbourg University, France, in 2012, and the Ph.D. degree in micro- and nano electronics from TIMA Laboratory, University of Grenoble Alpes, France, in 2016. Between 2016 and 2019, he was a Post-Doctoral Researcher, successively with TU Eindhoven, The Netherlands and KU Leuven, Belgium. His current research interests are the design of low-power integrated circuits and mixed-signal edge AI hardware accelerators for self-adaptive and self-learning applications.

Kimmo Hätönen completed his Ph.D. in Computer Science at the University of Helsinki, Finland in 2009. He is a Principal Scientist at Nokia Bell Labs in Espoo, Finland, where his responsibility areas include all sorts of data science applied to network and IoT data; currently especially exchange and analytics of streaming data. He has studied data, information and knowledge related issues for over 30 years in Research organizations at Nokia and at the University of Helsinki. He has authored and co-authored several tens of publications and been involved in introducing several methods, tools and products for communication network data analysis.

Terhi Kajaste is currently the Corporate Relations Manager at Aalto University. Ms. Kajaste is also the Manager of Industry and Society collaboration at Finnish Center of Artificial Intelligence (FCAI). She is an experienced professional and leader with long experience and wide understanding of public and private sectors as well as of academic, business, societal and political aspects. She was the Managing Director of Finnish Health Technology Association from 2007 to 2015. She has worked as an intermediator between healthcare and health tech industry for many years. Currently, she is applying her experience and knowledge in academic and ecosystem collaborations. Terhi holds a Master's in Science from Helsinki University of Technology.

Kit is a Senior Manager in the Global Engagement team of Aalto University in Finland. Kit has an interesting mix of work experience spanning over 19 years from two different fields and in two different countries; International Affairs (Finland) and Food science and Nutrition (India). Kit has travelled through core functions in teaching and research and in international project management in various academic institutions in India and in Finland. Currently, Kit is responsible for developing and managing selected key international university partnerships for Aalto University. Kit is also coordinating the FICORE (Finnish Indian Consortia for Research and Education) network which involves 23 IITs and 15 Finnish higher educational institutions. FICORE is part of the Global Programme Pilot initiative from the Finnish Ministry of Education and Culture.

Siddharth Naithani, as Senior Advisor for ICT at Business Finland, assists companies across Finland discover relevant commercial opportunities through identification of new potential end customers and market-entry partners. He oversees the domains of Data & Software, Games & Media and finally Mobility & Communications. Continually in touch with the Indian private sector to source problem statements and upcoming focus areas, he primarily engages with Banks, Systems Integrators, Logistics Giants, Gaming Studios and a variety of Tech Unicorns. Previous to Business Finland, Siddharth was heading the Australian Governments Fintech initiative in Mumbai, and has experience working with the Irish & British governments, a National Chamber of Commerce in India as well as KPMG. Holding an MSc in International Business Management from the University of Aberdeen and a Bachelor of Business Studies from Trinity College Dublin, Siddharth has earlier studied in five different educational systems across eight countries.