Skip to content

Education

Formal depth built deliberately on top of practice

Built formal Computer Science and Applied AI capabilities on top of extensive professional experience in industrial digital platforms and connected systems.

Postgraduate development

Advanced AI, Innovation & Product Development

A coordinated postgraduate development period across several universities, covering advanced artificial intelligence, Innovation Management, Industrial Economics, Product Management, Product & Requirements Management, Strategy & Business Models, Agile Process & Project Management and Leadership.

Phase 2 · Product · Industrial Economics · Requirements · Delivery

Aug 2025 – Jun 2026

Blekinge Institute of Technology

Advanced-Level Specialization in Industrial Economics, Product & Requirements Management

Building on the technical AI and innovation foundation, this specialisation covers product strategy, business models, requirements, commercialisation and leadership — how customer needs and technology opportunities become viable products and sustainable value.

Aug 2025 – May 2026

Course project — Talking SCADA (product & requirements case)

I used Talking SCADA as a recurring academic case, carrying the original innovation opportunity into product definition, system requirements, value assessment and business planning — what users need, what the system should do, what to prioritise and how the offer could be delivered and sustained.

Course

Strategy and Business Models in Technology-Intensive Businesses

  • Product strategy
  • Value proposition
  • Business model development
  • Market relevance
  • Go-to-market planning
  • Developed a Talking SCADA business plan connecting customer segments, value proposition and strategic direction, positioned around cross-system diagnostics and understandable operator explanations.
  • Proposed tiered SaaS packaging, revenue logic, partner channels and a go-to-market path supported by integration, onboarding and ongoing service.
  • Treated adoption, willingness to pay and financial viability as assumptions for further validation.

Course

Product Management

  • New Product Development (NPD)
  • Product Requirements Document (PRD)
  • Product vision & strategy
  • Product discovery
  • MVP definition
  • Product Life Cycle
  • Opportunity, vision & strategy: applied New Product Development (NPD) thinking and a Product Innovation Charter (PIC) to frame market need, technical opportunity and boundaries — then shaped a product vision and strategy for Talking SCADA, positioned so its value is clear to customers and the business.
  • Concept generation & evaluation: planned lead-user involvement and cross-functional collaboration, with technical and commercial screening criteria for Go/No-Go decisions.
  • Product definition & business model: connected vision, user needs, functional and quality scope, UX and service model through a Business Model Canvas — linking product definition to how the offer creates and captures value.
  • Development planning & PRD: produced a product protocol and Product Requirements Document (PRD) covering target users, the whole offer, scenarios, MVP scope, success measures and acceptance criteria.
  • Commercialisation, launch & lifecycle: planned positioning, SaaS packaging and partner channels with pilot use tests before wider introduction, then a staged rollout with performance monitoring and customer-feedback loops across the product life cycle.

Course

Product and Requirements Management for Digital Environments

  • System Requirements Document (SRD)
  • Requirements traceability
  • Cost-Value-Risk
  • Requirements prioritisation
  • Technical feasibility
  • System requirements & traceability: produced a System Requirements Document (SRD) linking interview, observation and prototype findings to goals and requirement IDs — domain, functional, data, quality, integration and policy requirements.
  • System & workflow specification: used a context diagram, conceptual data model, interface mockup and task description to define system boundaries and the investigation workflow.
  • Value-driven prioritisation: ranked 22 requirements with a Software Value Map, and applied Cost-Value-Risk to critical requirements, considering dependencies and uncertainty.
  • Assets & sourcing: analysed reuse of technical assets and domain knowledge with Make/Buy/Share and commodity, qualifier and differentiator classifications.

Course

Agile Process and Project Management

  • Agile process
  • Scrum
  • MVP planning
  • Development planning
  • Prioritisation / delivery thinking
  • Applied agile and Scrum practices to iterative concept refinement — short cycles, scope refined through feedback, and MVP planning to test the riskiest assumptions first.
  • Used Talking SCADA to plan a limited first scope and decide what to learn next — sequencing work so evidence could change priorities and the development plan.
  • Connected development planning with project management and product-development governance — tracking progress, dependencies and delivery risk.

Course

Leadership in High-Technology and Knowledge-Intensive Organizations

  • Stakeholder alignment
  • Communication
  • Cross-functional perspective
  • Studied leadership styles in technology- and knowledge-intensive organisations, then interviewed a practising leader and analysed their style in real context — in my case the person leading and accountable for a data centre.
  • Connected the analysis to cross-functional direction: how a leader aligns engineering, operations and business stakeholders around shared priorities, communication and trade-offs.
  • Built a personal leadership development plan with structured self-reflection — mapping my strengths and growth areas against the leadership behaviours that fit technical environments.

Bridge · Aug 2025 – Jan 2026 · Innovation Management

Aug 2025 – Jan 2026

University of Skövde

Advanced-Level Studies in Innovation Management

Focused on strategic innovation, applied innovation processes, implementation and innovation leadership — studied in parallel with the advanced AI foundation as the innovation and product bridge developed further at Blekinge Institute of Technology.

  1. Domain experience & applied AI
  2. Innovation in Practice — initial concept
  3. Product & requirements development
  4. Business & commercialisation planning

Aug 2025 – Jan 2026

Talking SCADA — concept origin in Innovation in Practice

  • Framed the original Talking SCADA concept around hidden energy problems in interacting building systems, connecting a familiar user problem with energy efficiency and societal value.
  • Used PESTEL, VRIO and the Four Ps of innovation to examine external drivers, organisational capabilities and the proposed service innovation.
  • Proposed a Design Thinking approach, with cross-functional collaboration, leadership support and psychological safety as conditions for implementation.

Phase 1 · Advanced AI Foundation

These studies built the technical foundation I bring to Talking SCADA: understanding AI capabilities, limitations and the data and system conditions needed for useful decision support.

Aug 2025 – Jan 2026

Linköping University

Advanced-Level Studies in Artificial Intelligence: Natural Language Processing

  • Studied transformers, sentiment classification and domain adaptation, with PyTorch implementation and PEFT/LoRA.
  • Strengthened my understanding of language-model capabilities, limitations and adaptation to domain-specific tasks.
  • For Talking SCADA, this informs decisions about natural-language interaction and explanations grounded in building context.
  • Natural Language Processing
  • Transformer architectures
  • Domain adaptation
  • PyTorch
  • PEFT / LoRA

Jan 2026 – Jun 2026

Umeå University

Advanced-Level Studies in Artificial Intelligence: Autonomous Systems & Perception

  • Studied sensor fusion, 3D perception, prediction, planning and reinforcement learning.
  • Examined how uncertainty, data quality and sensor constraints affect decisions across an AI system.
  • This informs how I assess reliability and uncertainty in Talking SCADA's proposed decision support.
  • Multi-sensor fusion
  • 3D perception
  • Object detection
  • Path planning
  • Reinforcement learning

Completed Nov 2025

Mälardalen University

Predictive Data Analytics

  • Studied predictive analytics and machine learning for decision support.
  • Connected prediction to the decision it is intended to support.
  • For Talking SCADA, this provides a foundation for assessing how predictions could help users investigate energy deviations.
  • Predictive analytics
  • Machine learning
  • Prediction
  • Decision support

Completed Dec 2025

Mälardalen University

Deep Learning for Industrial Imaging

  • Studied deep learning and computer vision for industrial imaging.
  • Broadened the technical foundation I bring to AI product decisions, including the fit between a method, the available data and the user problem.
  • Deep learning
  • Computer vision
  • Industrial imaging
  • Industrial AI

Wider institutions involved in the postgraduate AI specialisation include Umeå University, Linköping University and Mälardalen University.

Degree

Mälardalen University

Degree of Bachelor of Science in Computer Science with Specialization in Intelligent Systems

B.Sc. in Computer Science · Applied Artificial Intelligence

Built formal Computer Science and Applied AI capabilities on top of extensive professional experience in industrial digital platforms and connected systems.

  • Built a foundation in AI methods, model evaluation and software engineering for AI systems.
  • Worked through user research, ideation, Figma prototyping and usability and accessibility evaluation in interaction-design coursework.
  • Brought this technical and human-centred foundation into the later Talking SCADA concept.
Rickard Sörlin with thesis colleagues and examiners at Mälardalen University
Degree project completed — Mälardalen University

AI & Data

  • Probability & Statistics
  • Machine Learning
  • Advanced Machine Learning
  • Deep Learning
  • Artificial Intelligence 1 & 2
  • Natural Language Processing
  • Reinforcement Learning
  • Generative AI
  • Predictive Analytics
  • Data Science

Software & Data

  • Software Engineering
  • Software Engineering for AI
  • SQL
  • Cloud Platforms

Product / Human-Centred Development

  • Interaction Design
  • Agile development
  • User stories
  • Backlog structuring
  • UML
  • Requirements prioritisation

Responsible Technology

  • AI Ethics

The degree was completed before the postgraduate development period beginning in August 2025.

Certifications

Additional programmes

  • AI Governance & Responsible AI

    University of Oxford

  • Machine Learning Specialization

    Stanford University Online

  • Deep Learning Specialization

    DeepLearning.AI

Foundation

Earlier technical foundation

  • IoT & Automation

    Sjödals Gymnasium

  • Robotic and Process Automation

    PLC · Robotics · Process Automation

Capability map

Full capability overview

Product & Strategy

  • Product Management
  • Product Strategy
  • Product & Portfolio Strategy
  • New Product Development
  • Product Discovery
  • Requirements Engineering
  • Requirements Prioritisation
  • Feature Prioritisation
  • MVP Definition
  • Roadmap Contribution
  • Product Lifecycle Thinking
  • Value Proposition
  • Business Models
  • Go-to-Market
  • Stakeholder Alignment
  • Technical-commercial trade-offs

AI & Data

  • AI-enabled products
  • GenAI / LLMs
  • RAG
  • GraphRAG
  • Agentic AI
  • Multi-Agent Systems
  • Machine Learning
  • Deep Learning
  • NLP
  • Predictive Analytics
  • Time-Series Forecasting
  • Probabilistic Forecasting
  • Computer Vision
  • Data-Driven Decision Support

Industrial / Platform

  • Industrial Digital Platforms
  • SCADA
  • BMS
  • HVAC
  • EMS
  • Building Automation
  • PLC
  • IoT
  • IIoT
  • OPC UA
  • Edge Systems
  • Connected Systems
  • Industrial Communication
  • Real-Time Monitoring
  • Energy Systems
  • Smart Buildings
  • Mission-Critical Environments

UX / Discovery

  • Customer Discovery
  • User Needs
  • Interaction Design
  • Wireframing
  • Paper Prototyping
  • Figma
  • User Testing
  • Accessibility
  • Inclusive Design
  • Heuristic Evaluation

Tools

  • Python
  • PyTorch
  • Scikit-learn
  • LangChain
  • LangGraph
  • LangSmith
  • RAGAS
  • Transformers
  • PEFT
  • LoRA
  • SQL
  • NoSQL
  • Graph Databases
  • Knowledge Graphs
  • Vector Databases
  • Time-Series Data
Depth varies across these areas — they are shown as working familiarity, not equal expert-level mastery.