PeopleofSuperintelligence

Researcher

Maja Vuković

Maja Vuković is an AI researcher whose work links context-aware service planning, software modernization and agent-enabled business processes. She earned a BSc at the University of Auckland and an MSc from International University in Germany. Her 2006 Cambridge PhD dissertation applied AI planning to compose services as computing context changed. Her coauthored work covers Mono2Micro, Project Minerva and code LLM tooling; she received the IEEE TCSVC Award for Women in Services Computing in 2018 and became an IBM Fellow in 2021. In September 2026, she wrote about AI-agent-augmented business processes; as of October 2026, she is IBM's Chief Technology Officer for AI & Automation Research.

Now at
IBM
Badges

Timeline

  1. 2006

    Context-aware service composition

    She holds a BSc from the University of Auckland and an MSc from International University in Germany. In 2006, she submits her Cambridge PhD dissertation on context-aware service composition, which uses AI planning to select and assemble services as computing context changes.

  2. 2018

    A services computing award

    In 2018, she receives the IEEE TCSVC Award for Women in Services Computing.

  3. By 2019

    IBM and Mercedes research

    By 2019, she is a research manager and research staff member at IBM's T. J. Watson Research Center. Before IBM, she works as a research scientist on telematic services at the Mercedes-Benz Research and Technology Center in Palo Alto.

  4. 2021

    IBM Fellow

    She becomes an IBM Fellow in 2021, receiving an IBM distinction that recognizes sustained technical achievements and leadership.

  5. 2021–2023

    AI tools for modernization

    In 2021, she coauthors an IBM Developer article on Mono2Micro, an AI-driven tool that uses runtime traces and static analysis to recommend Java service partitions. In 2023, she coauthors an IBM Research article on Project Minerva, an open-source toolkit for refactoring legacy software; its CARGO algorithm uses code and data dependencies to recommend microservices.

  6. 2024

    Code LLM analysis tooling

    In 2024, she coauthors codellm-devkit, an open-source Python library that simplifies program analysis and provides code-specific context for code LLM use cases.

  7. September 2026

    AI agents in business processes

    In September 2026, she writes about process discovery for AI agent-augmented business processes, describing how organizations can add agent-driven tasks and use governance and observability as they deploy them.

  8. As of October 2026

    IBM AI research CTO

    She is an IBM Fellow and Chief Technology Officer for AI & Automation Research, leading IBM's global research strategy in artificial intelligence and automation. Her work focuses on large language models, AI agents and enterprise AI.

Career

  1. Since 2021IBMIBM Fellow
  2. Mercedes-BenzResearch Scientist
  3. IBM ResearchResearch Manager and Research Staff Member

Education

  1. 2006University of CambridgePhD
  2. University of AucklandBSc
  3. International University in GermanyMSc

From the biography.

  1. 23% of people shaping AI who left a university for a company later returned to a universityIncludes IBM. We estimate that 468 of the 2,011 people shaping AI who left a university for a company (23%) later returned to a university after a median of 5 years, and 163 of 829 (20%) made the reverse round trip.
  2. Google alumni have founded or led 133 other organizations, more than any other AI labIncludes IBM. We estimate that alumni of 17 major AI labs went on to found or lead 350 other organizations, including 226 they founded, and we trace 472 career moves directly between 23 labs since 2010.
  3. Universities keep AI researchers for a median of 6 years, compared with 2 years at frontier labsIncludes IBM. Across 15,811 dated work stays (6,529 people), median role tenure runs from 6 years at universities to 2 years at frontier labs. We compare all five organization types, starting decades from the 1970s to the 2020s, and the organizations that keep people longest.
  4. People shaping AI work at a median of 3 organizations over a career: 3 for university starters and institute and lab starters, versus 2 for company startersIncludes IBM. Across 6,853 people shaping AI with a dated work role, we estimate a median of 3 parent organizations over a career (mean 3.6), comparing role groups, starting sectors and starting decades from the 1950s to 2020–2026.

Colleagues

People with dated positions at the same organization in the same years.

Sources and credits

Photo: We have no published photo of Maja Vuković yet. Send us a free-licensed photo.

  1. Context aware service composition cl.cam.ac.uk. Checked 21 October 2026.
  2. Speaker: Maja Vukovic: O'Reilly Artificial Intelligence Conference: Applied AI & machine learning conferences.oreilly.com. Checked 21 October 2026.
  3. IBM Impact: Fellows ibm.com. Checked 21 October 2026.
  4. A non-disruptive approach to transform Java monoliths to microservices using IBM Mono2Micro developer.ibm.com. Checked 21 October 2026.
  5. Migrating antiquated enterprise software to the cloud with the help of AI research.ibm.com. Checked 21 October 2026.
  6. Codellm-Devkit: A Framework for Contextualizing Code LLMs with Program Analysis Insights arxiv.org. Checked 21 October 2026.
  7. Process Discovery for AI Agent-Augmented Business Processes community.ibm.com. Checked 21 October 2026.
  8. Maja Vukovic | IBM Fellow and Chief Technology Officer, AI & Automation Research at IBM | Unleashed 2026 stockholmshandelskammare.se. Checked 21 October 2026.