AI trainer & Researcher
Dr. Rimma Dzhusupova

English speaking AI trainer Rimma Dzhusupova

AI trainer & Researcher (PhD in AI • English speaking)

Rimma: “As an AI Initiative Lead and researcher at TU Eindhoven, I combine technical expertise with practical applications. My experience in leading AI teams and involvement in developing the EU AI Code of Practice enables me to help organizations implement AI responsibly and effectively. As a mentor at Women in AI Netherlands, I’m also dedicated to guiding talent in the field of AI.”

Dr. Rimma Dzhusupova brings over 14 years of industrial experience and a deep expertise in developing practical AI solutions, backed by a Ph.D. from TU Eindhoven. She excels in devising strategies and solutions that make AI accessible and effective across various business contexts. As a recognized AI educator, Rimma adeptly demystifies complex AI concepts, transforming them into actionable strategies that businesses can implement to drive success.

An active participant in the EU Commission’s Plenary for the AI Act, she ensures that AI deployments meet the highest regulatory standards and shares her insights through workshops and presentations on the business impacts of AI developments.

Dedicated to fostering diversity within the AI field, Rimma actively supports Women in AI Netherlands, promoting responsible AI integration to spearhead innovation and sustainable growth. Her commitment is to help organizations responsibly integrate AI, driving innovation and sustainable growth in today’s rapidly evolving technological landscape.

Main Publications:

  • Dzhusupova, R., et al. Challenges in developing and deploying AI in the engineering, procurement and construction industry. 2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC), 2022, pp. 1070–1075. DOI: 10.1109/COMPSAC54236.2022.00167
  • Dzhusupova, R., et al. The Goldilocks Framework: Towards Selecting the Optimal Approach to Conducting AI Projects. 2022 IEEE/ACM 1st International Conference on AI Engineering – Software Engineering for AI (CAIN), 2022, pp. 124–135. DOI: 10.1145/3522664.3528595
  • Dzhusupova, R., et al. Choosing the right path for AI integration in engineering companies: A strategic guide. Journal of Systems and Software, vol. 210, 2024. DOI: 10.1016/j.jss.2023.111945
  • Dzhusupova, R., et al. Pattern Recognition Method for Detecting Engineering Errors on Technical Drawings. 2022 IEEE World AI IoT Congress (AI-IoT), 2022, pp. 642–648. DOI: 10.1109/AIIoT54504.2022.9817294
  • Dzhusupova, R., et al. Using artificial intelligence to find design errors in the engineering drawings. Journal of Software: Evolution and Process, e2543, 2023. DOI: 10.1002/smr.2543
  • Dzhusupova, R., et al. Practical Software Development: Leveraging AI for Precise Cost Estimation in Lump-Sum EPC Project. 2024 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER), 2024, pp. 1023–1033. DOI: 10.1109/SANER60148.2024.00110

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