Soumya Basu

Dr Soumya Sankar Basu Fellow, UK Higher Education Academy, Ph.D (Engineering), Master of Computer Applications, B.Sc (Mathematics)

Senior Lecturer, Computer Science and Software Engineering


I teach Software Engineering, Software Design, Object Oriented Programming and Network Software Development



I have over 25 years of experience in academics and software services and consulting industry.  Prior to joining university, I worked for tier 1 software services and consulting organisations like IBM Global Business Services, PricewaterhouseCoopers Consulting, Wipro Technologies.

My current research interest is in Global Software Engineering, Software Engineering Methodologies, Software Architecture, Internet of Things. My doctoral research was in the area of Mobile Ad-hoc and Sensor Networks. MY specialization as an industry professional lies in Software Architecture, Application Architecture, Software Engineering Governance, Software Engineering, Process Method Tools, Software Development Methodologies (including Agile/DevOps/Garage method), Design Thinking, Requirement Engineering, Object Oriented Programming Cloud Based Application Development, Cognitive Dynamic Automation, Robotic Process Automation, RFID Application Development and Internet of Things.

I am actively involved in knowledge transfer and other industry collaboration activities  in software architecture, software engineering and cloud area.



Department of Computing

College of Business, Technology and Engineering


Computer Science and Software Engineering

Case studies in Software Design
Contemporary Software Engineering
Object Oriented Programming (Professional Solutions)
Network Software Development
Systems Modelling
Independent Study Consulting Project



Journal articles

da Silva, C.E., Gomes, E.L., & Basu, S.S. (2022). BPM2DDD: A Systematic Process for Identifying Domains from Business Processes Models. Software, 1 (4), 417-449.

Book chapters

Das, A., & Basu, S.S. (2023). An IoT-Enabled Innovative Smart Parking Recommender Approach. In Recommender Systems. (pp. 137-153). CRC Press:

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