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From Quantum Simulation to Enterprise AI: A Career Across Three Computing Paradigms

My professional career spans more than three decades and follows the fundamental evolution of large-scale computing itself: from early high-performance computing (HPC) and numerical simulation, through distributed and grid computing, to cloud computing, data-intensive science, and today enterprise-scale AI, GenAI, and agentic systems. Throughout this journey, my work has consistently focused on the intersection of mathematical modelling, scalable computing architectures, and real-world scientific and industrial applications.

Foundations in Numerical Analysis and Quantum Physics

I began my academic path in Engineering Physics at Uppsala University, with an early specialization in numerical methods and scientific computing. My master’s work focused on transport-corrected numerical models for nuclear reactor simulations at ABB Atom. This quickly evolved into advanced research in time-dependent quantum mechanics, where I pursued graduate studies both in Sweden, the United States, and Israel.

My Licentiate degree (1996) addressed quantum time evolution in time-dependent fields using Krylov subspace methods, and culminated in a PhD from Technion – Israel Institute of Technology (1999). My doctoral work focused on parallel preconditioned Krylov methods for multidimensional quantum scattering, targeting some of the most demanding computational problems in quantum chemistry and quantum physics. This work contributed new scalable solvers for large, high-dimensional, time-dependent partial differential equations.

This early phase gave me a deep and lasting foundation in:

  • Numerical linear algebra
  • Parallel algorithms
  • High-dimensional PDE solvers
  • Distributed memory architectures
  • Scientific performance optimization

Transition to Industrial Systems and Global IT Architectures

Following my PhD, I spent seven years in advanced industrial roles spanning IT security, product management, startup environments, and large-scale telecom systems. Notably, I worked in the core development of MySQL Cluster (NDB) at Ericsson, and later as Chief Architect for five global IT systems at Sony Ericsson. This period gave me hands-on experience in:

  • Mission-critical telecom databases
  • Global data warehouses
  • Enterprise security architectures
  • Large-scale distributed IT operations
  • Product management and system migration at global scale

This industry experience fundamentally shaped my later work in distributed research infrastructures by grounding it deeply in real-world operational demands.

Building Europe’s Grid Infrastructure

In 2004, I returned to academia to take on the role of Security Head for the EGEE project (Enabling Grids for eScience) at KTH, Europe’s largest distributed research infrastructure at the time, led by CERN. EGEE supported the Large Hadron Collider (LHC) and involved over 70 organizations across 40+ countries.

My responsibilities covered:

  • Leading security architecture and operations
  • Establishing the Middleware Security Group (MWSG) together with Stanford
  • Coordinating distributed security development across federated infrastructures
  • Serving as permanent member of EGEE’s executive management

This work placed me at the very core of pan-European distributed computing governance and operations, helping transition grid computing from experimental infrastructure into a production scientific backbone.

From Grid to Cloud: BalticGrid, Nordic Cloud, and SNIC

Building on EGEE, I became coordinator of BalticGrid and BalticGrid-II, extending European grid and cloud infrastructure into the Baltic region. Under my leadership, the project expanded to 6 countries, 13 partners, and 70 FTE, and achieved strong EU recognition.

During this phase, I also initiated:

  • BalticCloud – among the earliest European cloud initiatives
  • The BalticGrid Innovation Lab (BGi) – connecting early-stage startups to scalable computing
  • Early adoption of public cloud computing (AWS, OpenNebula, Eucalyptus) in research environments

From 2009 onward, I led or co-initiated major national and Nordic cloud programs:

  • SNIC Cloud (Sweden)
  • Nordic Cloud (NeIC)
  • NEON (Northern Europe Cloud)
  • Swedish participation in the EGI Federated Cloud

These efforts established production-grade national cloud infrastructure for research in Sweden and across the Nordics.

In recognition of this early and sustained engagement in cloud computing, I was appointed to the EU Cloud Expert Group in 2010, where I co-authored key strategic documents shaping European cloud policy and Horizon 2020 investments.

Entrepreneurship, Innovation, and Startup Ecosystems

Parallel to my infrastructure work, I became deeply engaged in technology entrepreneurship:

  • Startup coaching at Aalto Venture Garage and Startup Sauna
  • Co-founder and managing partner in the SICS Startup Accelerator
  • Advisor to Severalnines (database automation)
  • Co-founder of Numeri Ltd (scalable video compression)

This entrepreneurial engagement strengthened my long-term focus on translating research infrastructure into real economic value.

The Shift to Data-Intensive Computing

In 2012, I founded the Data-Intensive Computing Group at KTH within the newly formed HPCViz department. This represented a strategic shift from compute-centric to data-centric computing. Drawing from my HPC background and cloud infrastructure work, I focused on:

  • Iterative large-scale data analytics
  • In-memory distributed computing
  • Advanced analytics stacks beyond classical MapReduce
  • Spark-based scalable machine learning and bioinformatics

My group became an early adopter of Apache Spark, inspired by direct interaction with the Berkeley AMPLab, Microsoft Cloud Futures, and the early Spark development team. This enabled us to run iterative statistical and machine-learning workloads with orders-of-magnitude performance gains over traditional Hadoop approaches.

Our applied research focused on:

  • Bioinformatics and life science analytics
  • Distributed virtual screening
  • Large-scale anomaly detection
  • Streaming data analytics
  • Security and intrusion detection

Teaching, Leadership, and Community Building

Across my academic career, I have consistently contributed to:

  • Undergraduate and graduate teaching
  • International summer schools in grid and cloud computing
  • National cloud training programs
  • Dozens of invited talks across Europe, Asia, and North America

I have served on program committees, expert boards, and advisory groups across cloud, grid, and data science communities. I have also supervised and co-supervised PhD students within distributed systems, cloud infrastructure, and data-intensive computing.

A Continuous Evolution of Scalable Computing

In hindsight, my academic career forms a continuous arc:

  • 1990s: Numerical analysis, quantum simulation, HPC
  • 2000s: Distributed systems, global IT, grid computing
  • 2010-2014: Cloud infrastructure, federated systems, entrepreneurship
  • 2012 onward: Data-intensive computing, streaming analytics, large-scale machine learning

From Data-Intensive Science to Enterprise AI Leadership at Telia

In 2015, I transitioned into Telia Company to help build industrial-scale analytics and AI capabilities across the Nordic and Baltic region. This move was a natural continuation of my work in data-intensive computing, cloud infrastructure, and distributed systems—now applied inside a large, data-rich, commercial environment.

Building Telia Analytics (2015–2018)

Data Scientist, Telia Company (2015.08 – 2018.11)
TV & Media Analytics Lead (2015.12 – 2017.11)
Deep Learning Coordination (2017.11 – 2018.11)

During this period, I was part of the core team that created what became Telia Analytics. I moved between roles as architect, data scientist, and technical leader, helping define both the technical foundations and the ways of working for modern analytics at Telia.

Key contributions:

  • Core member of the founding Telia Analytics initiative
  • Initially brought in as Lead Architect for Data & Analytics, designing architecture and roadmaps for the Common Data Lake (CDL)
  • Built a Spark-based TV & Media analytics platform on top of the CDL to aggregate and analyze usage, content, and service data for business insights
  • Worked closely with business owners across TV & Media and other units to identify high-value use cases and demonstrate what large-scale analytics could deliver
  • Coordinated company-wide Deep Learning (DL) initiatives within Data & Analytics:
  • Identified DL business cases, ran proofs-of-concept, and took successful ones into production
  • Led a company-wide DL course to upskill data scientists in modern deep learning techniques
  • Facilitated knowledge-sharing communities for DL best practices
  • Helped colleagues—especially data scientists—transition from traditional analytics to big data analytics and scalable ML, both technically and conceptually
  • Led work on streaming analytics within Insights & Analytics, exploring how real-time and near-real-time data could support operations and customer-facing use cases

This period established Telia’s analytics foundation: a shared data lake, a modern compute stack, and a growing community of data scientists and engineers working on large-scale use cases.

Enterprise Architecture Leadership for AI & Analytics (2019–Present)

Chief Domain Architect, Analytics & AI (2019.01 – Present)
Head of Analytics IT Architecture (2022.05 – 2024.11)
Lead Architect AI (2024.12 – Present)

From 2019 onwards, my role shifted from building solutions directly to owning and governing the overall analytics and AI architecture for Telia Group. I now lead a network of chief analytics architects across six countries (SE, FI, NO, DK, LT, EE) and am responsible for the target architecture and strategic direction of our analytics and AI capabilities.

Leadership & Strategy

  • Chair of the Telia Analytics & AI Architecture Board, covering AI, ML, DL, MLOps, and GenAI
  • Lead of chief analytics architects across Telia’s footprint, ensuring cross-country alignment while respecting local needs
  • Define the enterprise strategy and guardrails for:
  • Big data and analytics platforms
  • Machine learning and deep learning
  • MLOps practices and tooling
  • GenAI and emerging agentic AI patterns
  • Work closely with senior business stakeholders and IT leadership to ensure analytics and AI architecture supports Telia’s overall strategy and transformation agenda

Architectural Development

  • Develop, govern, and evolve Telia’s target architecture for:
  • On-premises analytics platforms
  • Hybrid and multi-cloud environments (AWS, Google Cloud, and selected use of Azure)
  • AI and ML workloads, including GenAI
  • Lead key technical proof-of-concepts and architectural evaluations to integrate new technologies and patterns safely and effectively
  • Drive the move from monolithic or tightly-coupled platforms to modular, evolutionary architectures that can adapt over time
  • Ensure that our platforms are:
  • Scalable and performant
  • Secure and compliant
  • Suitable both for classical analytics and modern AI/GenAI workloads

Stakeholder Communication & Governance

  • Own and communicate architecture frameworks, blueprints, and roadmaps for analytics and AI across the group
  • Ensure cohesion and strategic alignment between central platforms, country initiatives, and business domains
  • Promote best practices for:
  • Data and model lifecycle management
  • Responsible AI and operational robustness
  • Platform and capability reuse across countries

Implementation Support

  • Provide ongoing hands-on guidance to:
  • Platform and data engineering teams
  • AI and ML engineers
  • Data scientists and analytics teams
  • Country and domain architects
  • Act as a trusted advisor when architecting or scaling critical AI and analytics solutions
  • Help teams adopt new capabilities (e.g., MLOps, GenAI, streaming analytics) in a way that is aligned with target architecture and long-term maintainability

Key Achievements at Telia

  • Established and chair Telia’s Architecture Board for Analytics & AI (AI–ML–DL–GenAI), driving cross-country alignment and innovation
  • Led the transformation from a purely on-prem analytics setup to a hybrid multi-cloud environment, improving scalability, flexibility, and resilience
  • Spearheaded the modernization of on-premise solutions from a legacy Hadoop-based system to a modular, in-house developed analytics stack, designed for evolution rather than one-off migrations
  • Introduced and implemented MLOps practices both in the cloud (AWS, Google Cloud) and on-prem, significantly improving the reliability and speed of ML deployment and operations
  • Directed large-scale upskilling efforts around:
  • Cloud technologies
  • Big data platforms
  • MLOps and ML engineering
  • Early GenAI experimentation and adoption
  • Currently leading the architecture for GenAI and emerging agentic AI across Telia, including:
  • Secure use of LLMs
  • RAG and knowledge-centric architectures
  • Integration of GenAI into existing analytics and customer-facing platforms

Business & Technology Impact

  • Built a hybrid multi-cloud analytics foundation, combining on-prem capabilities with AWS and Google Cloud to support diverse regulatory, latency, and cost needs
  • Enabled production-grade MLOps across environments, reducing time-to-production and improving robustness for AI and ML workloads
  • Standardized GenAI architecture patterns across countries, reducing fragmentation and enabling reuse of components and approaches
  • Delivered a clear, staged evolution path:

BI → Big Data → ML → DL → MLOps → GenAI → Agentic AI

  • Helped move analytics and AI from being isolated projects to becoming core, governed capabilities in Telia’s technology and business landscape

Closing Perspective

What began in the 1990s as parallel quantum simulation on supercomputers now continues as enterprise-scale GenAI and agentic AI across sovereign hybrid infrastructures.

The consistent through-line has always been:

Turning advanced computation into real, scalable, trusted systems for science, industry, and society.

References & Selected Writings

Data-Intensive Computing

  1. A. Gholami, A.-S. Lind, J. Reichel, J.-E. Litton, Å. Edlund, E. Laure, Platform-as-a-Service (PaaS) Privacy Threat Modeling for Emerging Biobank Clouds, submitted to DBSEC 2014, 2014.

  2. Å. Edlund, Data-Intensive Computing and the Future of Research, in Time to Think: Policy and Measurement in Internationalization and Competitiveness, Springer, 2014. Editor: Eskil Ullberg, George Mason University.

  3. L. Ahmed, Å. Edlund, E. Laure, O. Spjuth, Using Iterative MapReduce for Parallel Virtual Screening, CloudCom 2013, December 5, 2013.

Cloud Computing

  1. A. Gholami, Å. Edlund, E. Laure, Cloud Privacy Threat Modeling, 8th IFIP International Summer School on Privacy and Identity Management, Nijmegen, Netherlands, 2013.

  2. L. Schubert, K. Jeffery, B. Neidecker-Lutz (eds.), A Roadmap for Advanced Cloud Technologies under H2020, EU Cloud Expert Group Report, December 21, 2012. (Co-author: Å. Edlund)

  3. Å. Edlund, Cloud Computing – Challenges and Opportunities for Swedish Entrepreneurs, Swedish Entrepreneurship Forum, Publication No. 5, 2012 (52 pages).

  4. L. Schubert, K. Jeffery (eds.), Advances in Clouds, EU Cloud Expert Group Report, 2012. (Contributor: Å. Edlund)

  5. Å. Edlund, M. Koopman, Z. A. Shah, I. Livenson, F. Orellana, J. Kommeri, M. Tuisku, P. Lehtovuori, K. M. Hansen, H. Neukirchen, E. Þ. Hvannberg, Practical Cloud Evaluation from a Nordic eScience User Perspective, VTDC’11, ACM Conference, San Jose, 2011.

  6. E. Laure, Å. Edlund, The eInfrastructure Ecosystem: Providing Local Support to Global Science, in Large-Scale Computing Techniques for Complex System Simulations, Wiley Series on Parallel and Distributed Computing, 2011.

  7. Å. Edlund, I. Livenson, Cloud Computing and Startups, in Cloud Computing: Methodology, Systems, and Applications, CRC Press, 2011.

  8. Å. Edlund, Innovative Companies and Cloud Computing, BELIEF Zero-In eMagazine, Issue 4, 2010.

  9. L. Schubert, K. Jeffery (eds.), The Future of Cloud Computing – Opportunities for European Cloud Computing Beyond 2010, EU Cloud Expert Group Report, 2010. (Contributor: Å. Edlund)

  10. Contribution to: SIENA Roadmap on Distributed Computing Infrastructure for e-Science and Beyond in Europe, released February 23, 2012.

Grid Computing

  1. E. Laure et al., Programming the Grid using gLite, Computational Methods in Science and Technology, 2006. (Co-author: Å. Edlund)

  2. E. Laure et al., Middleware for the Next Generation Grid Infrastructure, Computing in High Energy and Nuclear Physics Conference, 2004. (Co-author: Å. Edlund)

Scientific Computing & Quantum Physics

  1. U. Peskin, Å. Edlund, I. Bar-On, Parallel Wave-Packet Simulations of Electron Transmission Through Water, Journal of Chemical Physics, 112, 3220–3226 (2000).

  2. I. Bar-On, Å. Edlund, U. Peskin, Parallel Solution of the Multidimensional Helmholtz/Schrödinger Equation Using High-Order Methods, Applied Numerical Mathematics, 33, 95–104 (2000).

  3. U. Peskin, Å. Edlund, I. Bar-On, M. Galperin, A. Nitzan, Transient Resonance Structures in Electron Tunneling Through Water, Journal of Chemical Physics, 111, 7558–7566 (1999).

  4. Å. Edlund, Multidimensional Quantum Scattering Calculations by a Parallel Preconditioned Krylov Subspace Method, PhD Thesis, Technion – Israel Institute of Technology, 1999.

  5. Å. Edlund, U. Peskin, A Parallel Green’s Operator for Multidimensional Quantum Scattering Calculations, International Journal of Quantum Chemistry, 69, 167–173 (1998).

  6. Å. Edlund, I. Bar-On, U. Peskin, Parallel Computation of Multidimensional Scattering Wavefunctions for Helmholtz/Schrödinger Equations, PARA98 – Applied Parallel Computing Conference, 1998.

  7. Å. Edlund, I. Vorobeichik, U. Peskin, High-Order Perturbation Theory for Helmholtz/Schrödinger Equations via a Separable Preconditioner, Journal of Computational Physics, 138, 788–800 (1997).

  8. U. Peskin, Å. Edlund, W. H. Miller, Quantum Time Evolution in Time-Dependent Fields and Time-Independent Reactive-Scattering Calculations via an Efficient Fourier Grid Preconditioner, Journal of Chemical Physics, 103(23), 1995.

  1. Ny Teknik (Dec 19, 2012), “Molnet ger Sverige nya jobb”, with Per Adolfsson (Microsoft Sweden).

  2. Sveriges Radio P1 – Vetandets Värld (Nov 2011), “Datahallarna växer i takt med sociala medierna”, interview.

  3. Naturvetarna (May 2011), “Datormoln med kraft att förändra IT-världen”, interview.

  4. SVT Web (Jan 2011), “Inte förvånad att datorn vann”, interview on IBM Watson.

  5. KTH Press (Feb 2011), “Vetenskapsmoln hjälper företag med hemläxan”, interview.

  6. Ny Teknik (June 2004), “Han ska göra industrin sugen på supernätet”, interview.

SELECTED ACADEMIC COMMUNITY PARTICIPATION (2009-)

2014.09.04-05, NordicCloud 2014 (program chair), Stockholm, Sweden 2014.06.23-27, ScienceCloud 2014 (program committee), Vancouver, Canada 2014.05.19-23, The EGI Community Forum 2014, Helsinki, Finland 2014.04.03-04, 4th International Conference on Cloud Computing and Services Science (program committee), Barcelona, Spain 2014.04.02-03, EASC2014, Solving Software Challenges for Exascale, Stockholm, Sweden 2014.02.24-25, CloudScape VI (panel), Brussels, Belgium

Data-Intensive Computing, Cloud and Innovation Presentations and Events

  • 2013.12.15-18, 19th IEEE International Conference on Parallel and Distributed Systems (ICPADS 2013) (program committee, did not attend), Seoul, Korea
  • 2013.12.02-03, Spark Summit, San Francisco, USA
  • 2013.11.19, "The Big Data Revolution: Regional Growth and Business Opportunities", Aalborg University Copenhagen, Denmark
  • 2013.10.03, "Data Exploration – the 4th paradigm of Science", KTH-GMU Workshop on Internationalization and Competitiveness (presenting, panel), Stockholm, Sweden
  • 2013.09.01-03, NordiCloud 2013 (program committee), Oslo, Norway
  • 2013.06.20-21, EU-China-North America Workshop on HPC Cloud and Big Data (presenting), Stavanger, Norway
  • 2013.06.19, Digital Agenda for Europe, Dublin, Ireland (invited delegate)
  • 2013.06.17, 4th Workshop on Scientific Cloud Computing (Science Cloud 2013) (program committee), New York, USA (did not attend)
  • 2013.06.10, "Från Molnet till BigData" (presenting), VINNOVA och Entreprenörskapsforum, Stockholm, Sweden
  • 2013.05.13-16, The Nordic e-Infrastructure Conference 2013, Trondheim, Norway
  • 2013.05.08-10, 3rd International Conference on Cloud Computing and Services Science (program committee), Aachen, Germany (did not attend)
  • 2012.11.27-29, Amazon Re:Invent, Las Vegas, USA
  • 2012.11.22, Entreprenörskapsforum – (presenting report 'Cloud Computing - Challenges and Opportunities for Swedish Entrepreneurs'), Stockholm, Sweden
  • 2012.09.24-26, CloudComp - 3rd International Conference on Cloud Computing (program committee), Wienna, Austria
  • 2012.08.20-21, NordiCloud - Nordic Symposium on Cloud Computing & Emerging Internet Technologies (part of WICSA/ESCA 2012) (co-chair), Helsinki, Finland
  • 2012.06.18, 3rd Workshop on Scientific Cloud Computing (program committee - did not attend), Delft, The Netherlands
  • 2012.05.16, SNIC Cloud Computing Course at UPPMAX, Uppsala University, Sweden (Coordinator, Intro, Wrap-up)
  • 2012.05.07-08, Cloud Futures 2012, UC Berkeley, USA
  • 2012.03.28-29, EGI CF (great EGI Cloud FT demos), Munich, Germany
  • 2012.02.21, Cloud and eScience, UPPMAX, Uppsala University, Sweden (presenter)
  • 2011.12.08, e‐Science Paper Session 7B, Tools (session chair), Stockholm, Sweden
  • 2011.12.07, eScience 2011 Workshop: Cloud Interfaces and Virtualization for e-Science and Industry (organizing), Stockholm, Sweden
  • 2011.11.29, Cloud Tech Day (organizing), Stockholm, Sweden
  • 2011.09.26-27, ISC Cloud '11, Mannheim, Germany
  • 2011.09.14, Cloud Day 2011 (organizing), Stockholm, Sweden
  • 2011.06.08, VDTC11 ACM conference (speaker), San Jose, USA
  • 2011.05.05, Cloud Computing and Startups, SICS Open Day, Kista, Sweden (presenting)
  • 2011.04.13, EGI UF, 3rd Enabling Clouds for eScience Workshop, Vilnius, Lithuania (organizer, presenting)
  • 2011.03.15, CloudScape-III, Brussels: Enabling Clouds for eScience - The open collaboration spot for cloud projects in Europe
  • 2011.02.03, Seminarium om Cloudområdets möjligheter och hot, Stockholm: Innovationer i Molnet (presenter)
  • 2010.11.16, Danish Research Network, Middlefart: Cloud Computing for eScience - today and future (presenter)
  • 2010.10.22, Cloud Computing, CSC, Espoo: Cloud Innovation Platforms (presenter)
  • 2010.10.06, Mindtrek, Tampere: What are the services Cloud could offer? (presenter)
  • 2010.05.19, NOTUR 2010, Bergen: x10 Questions and Answers about Cloud Computing (presenter)
  • 2010.05.04, Nordugrid 2010, Ljubljana: NEON and VENUS-C - two new cloud projects (presenter)
  • 2010.04.13, NDGF AHM, Uppsala: Northern Europe Cloud Initiative Status Report (presenter)
  • 2010.03.28-29, Two-day Inforte seminar course on "Cloud Computing and Service Engineering", Helsinki, Finland. (presenting Cloud Security & Cloud and Innovative Companies), together with Stefan Tai.
  • 2010.03.24, PDC Seminar, Stockholm: Cloud Computing Security - an Oxymoron? (presenter)
  • 2010.03.16, OGF Europe, Munich: ECEE - Enabling Clouds for EsciencE (BOF) (Initiator)
  • 2010.03.08, Technion, Haifa & TAU, Tel Aviv, Israel: Cloud computing and Innovative Companies (presenter)
  • 2009.12.17, Industry day, Vilnius: Innovative companies and cloud computing (presenter)
  • 2009.12.14, KTH Innovation, Stockholm: Cloud computing for innovative companies and their support (presenter)
  • 2009.11.26, IST, Innovative Software Technology, Tartu: Innovative companies and cloud computing (presenter)
  • 2009.10.15, CSC/Finnogrid, Services in the Clouds Industry Seminar, Espoo: Microstartups and cloud computing (presenter)
  • 2009.10.13, SUMMIT09, Cloud and HPC workshop, Banff: NEON - the Northern Europe Cloud Initiative (presenter)
  • 2009.09.21, EGEE09, Cloud and Grid workshop (co-chair), Barcelona: BGi and Northern Europe Cloud (NECloud)
  • 2009.09.15, Terena 4th TF-Storage Meeting, Copenhagen: Baltic Cloud, and the new Northern Europe Cloud (presenter)
  • 2009.07.17, ISSGC09, Sophia Antipolis: Cloud computing, Virtualisation and the Future (presenter)
  • 2009.06.12, Cloud Computing Day, Oslo: Grid, Cloud and Innovation (presenter)
  • 2009.05.27, LitGrid, Vilnius: Cloud computing (presenter)
  • 2009.05.25, UT, Tartu: Startup School (Initiator, presenter)
  • 2009.04.24, LSE, London: Extending the iED Ecosystem with Cloud Computing
  • 2009.04.21, KTH, Stockholm: Cloud computing - pay-as-you-go computing explained (presenter)

2004-2009: Many grid computing events, especially from the Enabling Grids for eScience (EGEE) project

1993-1999: Numerous distributed computing and scientific computing presentations