Dr Dean Mohamedally

Dr. Dean Mohamedally
Principal Teaching Fellow for Applied Software Engineering and Industry Projects
Director for Apps Engineering for UCL Faculties

Software Systems Engineering Group
Technology Transfer and Apps Strategy for UCL

Email: D.Mohamedally (at) cs.ucl.ac.uk

Department of Computer Science
University College London
Gower Street
London, WC1E 6BT
United Kingdom

My office hours are Thursdays 2pm by appointment

Office: Room 4.13a, MPEB

"Hello world."

I am the Principal Teaching Fellow for Applied Software Engineering and Industry Projects and a member of the Software Systems Engineering group at the Department of Computer Science, University College London. We currently have just over 650 programming-centric students in the Department of Computer Science, 470 of which are in my course modules that involve applied and industry-oriented software engineering. I am a Fellow of the Higher Education Academy and Member of the British Computing Society.

I am also the Director for Apps Engineering for all of UCL's faculties, and together with UCL Legal and UCL Engineering we enable students to participate on cross-university and client-engaged projects as part of their respective courses. If other faculties want to contact me about apps project requirements they can get in touch with me or my colleague, Dr Yun Fu. A role I keep close attention to is on Technology Transfer (primarily to syllabus and learning domains). Companies and research groups are welcome to contact me with regards to new technology platforms and deployment.

I am an executive member of the Institute for Digital Health, Digital Humanities and a keen supporter of our VR group.

My academic speciality is in Constructionism and Problem based learning within Computer Science education. My area of interest is on software construction best practices in Software Engineering and the application of Computer Science in general education e.g. via trends in Apps development and prototyping tools. I am also interested in school-based learning mechanisms for problem based learning, constructionist reinforcement and student-learning techniques from algorithm approaches to larger solution modelling.