Big Data 2023
Welcome to the 9th annual Big Data Conference at Linnaeus University, in Växjö, Sweden.
Even this year, the host for Big Data will be the Linnaeus University Centre for Data Intensive Sciences and Applications (DISA. https://lnu.se/disa). We invite everyone who has an interest in artificial intelligence, big data, and data intensive applications in the sciences, the humanities, in engineering and computing to take part in this event!
Our aim is that this new edition of the Big Data Conference will bring You both new inspiration from the speakers, and updates on results and ongoing research within DISA aswell as other universities and the industry.
This year we have two invited keynote speakers: Magnus Sahlgren and Christian S. Jensen. All other talks have been selected in competition and based on the responses from our call for presentations.
From this year's conference:
- A short summary can be found at: https://lnu.se/en/insights-BigData2023
- Recordings of all the presentations are available at: BigData 2023 - LnuPlay - Linnaeus University MediaSpace
From previous Big Data Conferences
- Various information, videos etc can be found via the following link: https://lnu.se/en/meet-linnaeus-university/conferences/big-data-conference/
Keynotes / Speakers
Day 1: November 30th
Keynote
Magnus Sahlgren has a PhD in computational linguistics, and his research lies at the intersection between computational linguistics, philosophy, and artificial intelligence. He is Head of Research for Natural Language Understanding at AI Sweden, and is primarily known for his work on computational models of meaning, and he is currently driving the initiative to train large language models for the Nordic languages. Sahlgren has previously held positions at the Research Institutes of Sweden (RISE), the Swedish Defense Research Agency (FOI), the Swedish Institute of Computer Science (SICS), Stockholm university, and he is the co-founder of the language technology company Gavagai AB. Sahlgren is also affiliated with Silo as a Principal AI Scientist, and with Pirr as an AI advisor.
This talk gives an overview over the process of building the first large generative language model for the Nordic languages. We cover the motivation for building the model, as well as challenges and opportunities with data and compute. We also give examples of applications of the model, and discuss future directions for building and deploying large language models for smaller languages.
Speakers
Olof Björneld is an industry PhD student at Computer Science Department, Linnaeus University. His employment is at Region of Kalmar län where he is responsible for their (health) data warehouse, residing in the Business Intelligence section.
His interests are within reuse of medical data (Knowledge discovery), Knowledge Driven Feature Engineering (KDFE) and AI in medicine. The focus of his research is about optimal knowledge discovery in clinical health care, starting with a research question applied on the relational health data stored in Electronic Health Records (EHR).
Mauro Caporuscio is a Full Professor of Computer Science at Linnaeus University (Växjö, Sweden). He received his Ph.D. in Computer Science from the University of L'Aquila, Italy. He was a Postdoctoral Researcher at INRIA (Paris, France) and an Assistant Professor at the Politecnico di Milano (Milan, Italy). He has published several papers in the most important international journals and conferences and has been serving on the program committee of international conferences. His research interests mainly focus on Software Engineering and Self-Adaptive Systems, with particular emphasis on decentralization and resiliency.
Francisco José Mora Caselles is a Master’s Degree student at Faculty of Computer Science, University of Murcia. Graduated with a Bachelor’s degree in Mathematics and a Bachelor’s degree in Computer Science at the University of Murcia in June 2023. He worked at DISA, Linnaeus University as part of a EUniWell collaboration project in 2023. His main topics of research are AI in eHealth and Pattern Mining with Subgroup Discovery.
Tora Hammar is an associate professor and senior lecturer in health informatics, at the eHealth Institute at Linnaeus University.
Tora is a pharmacist by training and has been doing research related to pharmacoinformatics, clinical decision support systems and information handling in the medication management process for almost 15 years. She is currently leading a research project about improving predictions of medication related problems using machine learning, among other things. Tora is also the research coordinator for a research groups focused on eHealth and Big data, which is one of the thematic groups in DISA (Linnaeus University Centre for data intensive sciences and applications, i.e. the organizer of the Big Data conference).
Fredrik Hanell holds a PhD in Library and Information Studies from Lund University (2019) and is a Senior Lecturer in Library and Information Science and Head of Department at the Department of Cultural Sciences, Linnaeus University, Sweden. In his PhD project, Fredrik explored the digital daily lives of teacher students and used netnography to investigate the meeting between practices of learning in teacher training and new digital tools. His current research focuses on critical library studies, digital methods, and media- and information literacy. Between 2021-2023 Fredrik is participating in the research project "Public libraries in a changed political landscape – a democratic mission for a new era?". Fredrik teaches digital methods and netnography on the master program in Digital Humanities and has participated in developing new Open Educational Resources on digital methods.
Cecilia Hjertzell is the Chief Marketing Officer and board member at Capacio. She boasts a rich history as an entrepreneur, CMO, and digital business developer with a primary focus on analytics. In her work, she holds extensive experience in assembling efficient, cross-functional teams tailored to the developmental phases of companies.
Daniel Ihrmark is a substitute lecturer at Linnaeus University in Växjö, Sweden. His Ph.D. project has dealt with the implementation of digital tools within language teaching, especially within the realm of second language learner diagnostics in English as an additional language. His work on the American authors of the 1920s has resulted in the creation of the Linnaeus University Lost Generation Corpus, which is a structured, computer-readable collection of fiction and non-fiction texts by authors such as F. Scott Fitzgerald, Ernest Hemingway, and Gertrude Stein. The intent of the Lost Generation Corpus is to make digital methods of engaging with the authors’ texts more accessible. Daniel is also active within the Educational Linguistics environment at Linnaeus University, which explores the role and use of language in educational contexts through transdisciplinary efforts.
Alisa Lincke is a Senior Lecturer at Computer Science Department, Linnaeus University. Her research interests are decision support systems (DSS), data-drive applications, and AI in eHealth. She works with different type of data, such as structured (sensors data) and unstructured (images, text) and uses interactive visualisations for visual data exploration.
Neda Maleki has a Ph.D. in Computer Engineering and is a postdoctoral fellow at the Department of Computer Science and Media Technology at Linnaeus University in Kalmar, Sweden. Her focus lies within the Internet of Things (IoT). Currently, she is involved in the “IoT Lab for SME” project, where the primary objective is establishing a robust network of companies in the Linnaeus region. This network fosters collaboration and mutual growth, enabling companies to leverage each other’s expertise and products within IoT. The mission is to empower small and medium-sized enterprises (SMEs) with the knowledge and practical resources to embark on their digital transformation journey.
Dr. Mohammed Ahmed Taiye holds a PostDoc fellowship at Linnaeus University in Sweden. He completed his Master's and was awarded a scholarship for his PhD degrees at the Northern University of Malaysia (UUM), with a focus on improving text analysis techniques, specifically in the areas of Artificial Intelligence (AI) and text mining. During his PhD program, he was also selected by the UUM School of Computing (SOC) to participate in the Group Based Learning program (GBPL) at Shibaura Institute of Technology in Tokyo, Japan.
His research interests are centered on the practical application of AI in the fields of Education (AIEd), Digital Humanities. and Health Care. Dr. Taiye is highly engaged in teaching master students about fundamental AI concepts and techniques, ensuring accessibility for students from various academic backgrounds. His work represents the fresh perspective of a budding academic in the field of AI research and its intersection with several scientific disciplines. Currently, Dr Mohammed Ahmed Taiye is involved in a couple of research projects supported by the EU and the Kamprad foundation in which he is exploring novel ways of using text mining and AI techniques for supporting human decision-making.
Jonas Tillström is business area manager for analytics, AI and machine learning at Sigma Technology Insight Solutions in Gothenburg. He has worked in the analytics and business intelligence area since 1994 and been part of a large number of projects for customers in automotive, manufacturing, retail, healthcare, and many other areas.
Day 2: December 1st
Keynote:
Christian S. Jensen is Professor of Computer Science at Aalborg University, Denmark. His research concerns analytics, including machine learning, data mining, and query processing, and data management, with a focus on temporal and spatio-temporal data. Christian is an ACM and IEEE Fellow, and he is a member of Academia Europaea, the Royal Danish Academy of Sciences and Letters, and the Danish Academy of Technical Sciences. He has received several awards, most recently the 2022 ACM SIGMOD Contributions Award and the 2019 IEEE TCDE Impact Award. He is on the board of Villum Fonden, a major funder of research in Denmark and is vice-chair of the Danish National Research Foundation. He is president of the steering committee of the Swiss National Research Program on Big Data. In Germany, he is on the scientific advisory board (SAB) of the Max Planck Institute for Informatics; and in Norway, he chairs the SAB of the Norwegian Research Center for AI Innovation.
Speakers
Tibo Bruneel is an industrial PhD Student at Softwerk AB and DISA, Linnaeus University. Graduated with a Master’s Degree in Software Technology at the Linnaeus University June 2023. Started as an industrial PhD student at Softwerk AB and the Linnaeus University, as part of the DIA graduate school, in September 2023. I am interested in topics in software development, machine learning and the combination through MLOps. My research focusses on combining software and AI components in industrial settings.
Farid Edrisi is currently pursuing a Ph.D. degree in computer science at the Department of Computer Science, Linnaeus University, Växjö, Sweden. His research interests include software architecture, self-adaptive systems, and developing digital twins at the machinery and organizational levels. He participated in several research project including Aligning Architectures for Digital Twin of the Organization (Aladino) which its aim was establishing a set of sound engineering methodologies, methods and tools for modeling, evaluating, and evolving a digital twin of an organization.
Manoranjan Kumar is employed as a Specialist in Data Analytics within Volvo CE, Braås, Sweden. He´s also pursuing an industrial Ph.D. from Linnaeus University, Växjö since 2020.
Manoranjan has 17 years of automotive development experience in the areas of Trucks, Buses, and Construction equipment working in the domain of FE Analysis, complete vehicle simulations (Articulated Hauler and Wheel loaders), Artificial intelligence, Machine learning, data analytics and log developments for the machines. He graduated in Mechanical Engineering from SASTRA, Thanjavur, India in the year 2006 and has a Master’s in Machine Design from UVCE, Bangalore, India in the year 2011.
Felix Viberg is a Computer Science PhD candidate at SKF Sverige AB and the Linnaeus University. Felix' work focuses on introducing new and robust methods for autonomous manufacturing. He is especially focused on operational problems related to visual inspection, anomaly detection and communication. Felix' has been part of developing several systems that are actively used at the production site in Gothenburg.
Oxana Lundström is a final year PhD candidate in Computational Biology at Stockholm University and a part-time research engineer at the IoT Lab, Linnaeus University, Kalmar. During her PhD Oxana worked with genetic sequencing data and implemented an interactive tool that lets medical researchers explore genetic variations in colorectal cancer.
Parallel to her research, she has been building on her industry experience as a data science consultant for companies like IBM, Plotly, and Mentimeter.
Her current passion lies in exploring the intersection of wearable technology, biosensors, and healthcare. She is actively investigating how these technologies can be leveraged to improve the daily lives of patients with chronic diseases by making practical use of the plethora of data these devices generate.
Thor Wikfeldt has an academic background in computational chemistry and materials science. After obtaining his Ph.D. from Stockholm University in 2011 he worked as a postdoc first at University College London and then the University of Iceland, before returning to a researcher position at Stockholm University. In 2016 Thor jumped over to high performance computing (HPC) and worked as an application expert in molecular dynamics at the PDC HPC center at KTH until 2020. In September 2020, Thor joined the newly established EuroCC National Competence Centre in Sweden (ENCCS) as a training coordinator where he developed the ENCCS training portfolio on topics in HPC and related areas. Since 2023, Thor serves as the director of ENCCS at the RISE Research Institutes of Sweden.
A Sustainable Event
Big Data 2023 is - of course! - a sustainability-assured meeting in accordance with Linnaeus University’s guidelines for sustainable events. These guidelines are linked to the 17 global goals in Agenda 2030 and comprise the three dimensions of sustainable development: the economic, the social, and the environmental.
Learn more about Linnaeus University´s sustainable events here.