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LEARNING AT NORTHEASTERN UNIVERSITY LONDON

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Biography


Dr. Muhammad Khan is a dynamic academic, consultant, and entrepreneur who combines cutting-edge research with practical industry application in the fields of Lean Innovation, project management, and AI-driven engineering solutions. His pioneering research in Lean Product Development and set-based concurrent engineering has been instrumental in transforming design and innovation processes across many of the world’s largest engineering organisations, several of which he has directly led and supported.

Dr. Khan’s academic journey began at King’s College London, where he completed both his Bachelor’s and Master’s degrees in Computer-Aided Mechanical Engineering, graduating with First-Class Honours. After gaining valuable experience through multiple roles in aerospace engineering, he pursued his Ph.D. at Cranfield University. During his doctoral studies, he served as technical integrator and project manager on the €7.6M LeanPPD project, where he developed the first comprehensive model for Lean Product Development. This foundational work led to his role as research fellow on the £8M+ CONGA project “Configuration Optimisation of Next Generation Aircraft.”

His academic career has spanned multiple institutions, including positions as Senior Lecturer in Engineering Management at the University of Wolverhampton and Lecturer in Engineering Management at Aston University. Beyond academia, Dr. Khan has held multiple director and CEO positions and has extensive consultancy experience, leading transformation projects across the globe from San Francisco to Melbourne.

Dr. Khan is committed to excellence in research, teaching, innovation, and enterprise, dedicating himself to raising the standards of his teams, establishing new projects, acquiring funding, and mentoring the next generation of technology leaders. His work has had a lasting impact on organisations, businesses, and the engineering design community both in the UK and internationally.

Research


Dr. Khan’s research focuses on the intersection of Lean methodologies, innovation management, and artificial intelligence applications in engineering and project management. His work in Lean Product Development, particularly in set-based concurrent engineering, has been widely implemented across industry and has established him as a leading authority in the field.

His research portfolio demonstrates significant impact through major European projects, including his foundational work on the €7.6M LeanPPD project where he developed the first comprehensive model for Lean Product Development, and his subsequent leadership role on the £8M+ CONGA project focusing on next-generation aircraft configuration optimisation. These projects have not only advanced theoretical understanding but have also resulted in practical tools and methodologies that have been adopted by leading engineering organisations worldwide.

Dr. Khan’s current research interests extend into the application of AI technologies, including generative AI, in project management and engineering design processes. He has been at the forefront of exploring how artificial intelligence can enhance traditional Lean principles, creating powerful synergies between established methodologies and cutting-edge technology. His work aims to make a lasting impact on the engineering and management community by developing innovative approaches that combine AI capabilities with proven Lean principles, processes, tools, and methods. His collaborative approach with industry partners ensures that his research maintains strong real-world relevance whilst advancing academic knowledge.


Journal Articles


2025 Fargher, G., Al-Ashaab, A., and Khan, M.S. (2025). LAMPD: A Combined Lean and Agile Model for Product Development. International Journal of Agile Systems and Management, (Acceptable for publication).
Impact Factor: 1.36 (2023).


2016 Suwanda, S., Sobun, N. S., Al-Ashaab, A., Khan, M. S., Rehman, A., Beg, N. (2016). The development of Knowledge-Shelf to support the generation of a set-based design of Surface Jet Pump. WSEAS Transactions on Fluid Mechanics, 11, Article No. 20, 159-165.
Impact Factor: 0.82 (2022).


2015 Khan, M.S., Al-Ashaab, A., Shehab, E., Kerga, E., Martin, C., Ewers, P. (2015). Define value: applying the first lean principle to product development. International Journal of Industrial and Systems Engineering, 21(1), 1-30.
Impact Factor: 1.09 (2022).


2013 Al-Ashaab, A., Golob, M., Attia, U.M., Khan, M.S., Parsons, J., Andino, A., Perez, A., Guzman, P., Onecha, A., Kesavamoorthy, S., Martinez, G. (2013). The transformation of product development process into lean environment using set-based concurrent engineering: A case study from an aerospace industry. Concurrent Engineering, 21(4), 268-285.
Impact Factor: 3.69 (2022)


2011 Khan, M.S., Al-Ashaab, A., Shehab, E., Haque, B., Ewers, P., Sorli, M., Sopelana, A. (2011). Towards lean product and process development. International Journal of Computer Integrated Manufacturing, 26(12), 1105-1116.
Impact Factor: 5.00 (2022)

Conference Articles


2019 Bolaji, A., and Khan, M. S., 2019, Improving knowledge management in the African oil and gas sector: A case study from Nigeria, 15th International Conference on Knowledge, Economy and Management, 21 – 24 April 2019, Rabat (pp. 1-17).


2012 Cabello, A., Flores, K., Flores, M., Khan, M. S. and Al-Ashaab, A., 2012, An analysis of methods to achieve conceptual robustness for lean product development, 18th International ICE Conference on Engineering, Technology and Innovation, 18 – 20 June 2012, Munich (pp. 1-10). IEEE.


2012 Kerga, E. T., Blázquez, A. and Khan, M. S., 2012, “Advanced process planning in lean product and process development”, 18th International ICE Conference on Engineering, Technology and Innovation, 18-20 June, Munich (pp. 1-13), IEEE.


2011 Khan, M., Al-Ashaab, A., Doultsinou, A., Shehab, E., Ewers, P. and Sulowski, R., 2011, Set-Based Concurrent Engineering process within the LeanPPD environment, 18th ISPE Conference on Concurrent Engineering, 04 – 08 July 2011, Massachusetts, Springer.


2010 Al-Ashaab, A., Flores, M., Khan, M. S., Maksimovic, M., Alam, R., Shehab, E., Doultsinou, A. and Sopelana, A., 2010, The Industrial requirements of KBE for the LeanPPD model, International Conference of Advances in Production Management Systems, 11 – 13 October 2010, (APMS 2010) Como, Italy.


2014 Al-Ashaab, A., Golob, M., Oyekan, J., Araci, Z.C., Khan, M.S., Deli, D., and Al-Ali, E., (2014). Flying into aerospace’s next generation. Industrial Engineering, 46(10), pp.38-43.

Teaching


Dr. Khan is a passionate educator who believes firmly in interactive and experiential learning approaches. His teaching philosophy centres on creating engaging, hands-on experiences that bridge theoretical knowledge with practical application. Most courses he has designed and delivered incorporate peer-to-peer discussion, workshop activities, physical instruments, and innovative tools including Lego bricks to facilitate learning.

His teaching experience spans a range of audiences, from undergraduate students to company vice presidents, demonstrating his ability to adapt complex concepts for diverse learning contexts. He has successfully taught across Levels 4-7 at various universities, consistently receiving positive feedback for his dynamic and engaging approach.

Current Teaching Portfolio at Northeastern University London (2025):


• Project Management & Communication (MSc L7)
• Fintech Innovation and Change (BSc L5)
• Fintech & Financial Innovation (BSc L6)

Dr. Khan has pioneered the integration of AI tools in project management education, facilitating numerous workshops that empower students to leverage artificial intelligence for rapid project planning and management. These innovative sessions have equipped students with cutting-edge skills whilst maintaining the rigorous academic standards expected at the university level.


Lecturer Areas/Areas of Expertise:

• Project Management
• Innovation Management
• Lean Product Development, Lean Manufacturing & Process Improvement
• Artificial Intelligence Applications in Engineering and Project Management, Including Generative AI
• Set-Based Concurrent Engineering