Organization Developer || Technology Enthusiast || System Administrator || Open Source Advocate
Bergen, Norway
Technology enthusiast with experience in organizational leadership, software development and system administration. Passionate about creating engagement and growth through strategic communication and relationship building, with a focus on IT projects and open source. Loves shaping, maintaining and streamlining organizational structures and procedures.
Believes in open source, knowledge sharing and transparent communication.
Motivated by creating engagement and growth in teams and organizations.
Builds trust and networks across professional communities and organizations.
Shapes and maintains organizational structures and procedures that scale.
Norwegian Armed Forces
AI Safety Bergen
AI Safety Bergen
AI Safety Bergen
AI Safety Bergen
Phonofestivalen
Studentersamfunnet i Bergen
Studentersamfunnet i Bergen
Specialization in information architecture, user behaviour and digital communication.
Consciousness, cognitive abilities and philosophy of AI. Specialization in computer science, philosophy and information science.
Artificial agents, machine learning and development of AI solutions. Combines computer science and information science.
The biological foundations of the nervous system, emotions, and learning, combined with cognitive theories of perception, memory, and reasoning.
Natural deduction for propositional and first-order predicate logic with identity, model theory, and set theory. Includes metalogic and proofs of properties of formal proof systems.
Introduction to phonetics, phonology, morphology, syntax, and semantics. Provides a theoretical and practical foundation for language-related studies.
Philosophy of science, ethics, and fundamentals of logic and argumentation theory. Develops critical and analytical competence relevant to one's own field of study.
The functional paradigm with recursion, higher-order functions, and immutable data structures. Programming in a functional language such as Haskell.
Interdisciplinary overview of cognition from computer science, linguistics, psychology, and philosophy. Covers knowledge representation, reasoning, learning, language, perception, and consciousness.
Modern philosophy of mind and the relationship between mental and physical properties. Covers behaviorism, identity theory, functionalism, and the problem of consciousness.
Introduction to propositional logic and first-order predicate logic. Emphasis on translating natural language into formal logic, truth tables as a proof system in propositional logic, and the tree method in propositional and predicate logic. Provides a foundation for further study in cognitive science.
Practical introduction to programming using a modern language. Covers variables, expressions, control flow, arrays, and file handling.
Logic-based knowledge representation and various forms of reasoning including deductive, default, and abductive reasoning. Also covers reasoning about knowledge, action, and change in multi-agent systems.
Continuation of programming with focus on code quality. Covers abstractions, object-oriented design, inheritance, polymorphism, generics, and testing.
Cognitive science related to linguistic knowledge, language acquisition, and language use. Explores the psychological and cognitive aspects of language.
Statistical methods and analysis for cognitive science. Covers descriptive statistics, hypothesis testing, and data analysis for cognitive experiments.
Data structures, algorithms, object-orientation, thread programming, and efficiency analysis. Also covers standards for structured data such as JSON, RDF, and XML.
Theory and practice of relational and NoSQL databases. Covers data modeling, normalization, query languages, and indexing principles.
Elementary logic and set theory, relations, functions, graphs, and trees. Covers combinatorics, probability, information theory, and computability.
Theoretical and practical foundations of AI including state-space search, knowledge representation, inference, and machine learning.
Supervised learning with deep learning, unsupervised learning including clustering, and reinforcement learning. Practical applications in data analysis.
Also counts towards this degree:
Explainable AI (XAI), fairness, algorithmic accountability and trust, artificial morality, and responsible use of AI. Includes practice in popular dissemination of AI.
Broad introduction to artificial intelligence as a discipline, including historical development, ethical implications, and key subfields such as machine learning, robotics, and natural language understanding.
Introduction to artificial agents and multi-agent systems, including agent modeling, autonomous agent architecture, control systems, and basic robotics.
Independent research project under supervision on a relevant topic in information science. Demonstrates advanced knowledge and scientific methodology, including problem formulation, literature review, data collection, analysis and critical evaluation.
Advanced topics in AI including artificial life, multi-agent systems, machine learning, neural networks, genetic algorithms, and natural language processing.
Methods for analyzing text and network data, including language models, document clustering, supervised machine learning, and network models.
Introduction to the HCI research field. Covers advanced concepts and approaches for analyzing and designing interactive systems.
Formal logics for reasoning about multi-agent interaction, including epistemic logic, temporal logic, coalition logic, and alternating-time temporal logic.
Self-chosen project work in informatics carried out with a supervisor. Project: analyzing programming language standardization and evolution processes. Includes programming, documentation in the form of a technical report, and an oral presentation.
Norwegian Armed Forces
2017-10
Norwegian Public Roads Administration
2017-01
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