Rate My Professor David Chen

Dr. David Chen is a Senior Lecturer in the School of Information and Communication Technology within Griffith Sciences at Griffith University. He obtained his PhD in the area of distributed collaborative systems from Griffith University in 2001, following a Bachelor with first class Honours in Information Technology in 1995 from the same institution. Throughout his academic career at Griffith University, Dr. Chen has focused his research on distributed collaborative systems, real-time communication protocols, multi-agent systems, and innovative pedagogical approaches in information technology education. His work addresses challenges in collaborative editing, constraint propagation in design environments, and improving student engagement through flipped classroom methodologies. Dr. Chen is a Member of IEEE and contributes to the academic discourse on teaching and learning in ICT.

Dr. Chen has published several key papers in his field, including 'Leveraging single-user applications for multi-user collaborative editing' (2004), which explores adaptations for collaborative use; 'Optional and responsive locking in distributed collaborative object editing systems' (2004); 'Multi-way Dataflow Constraint Propagation in Real-time Collaborative Design Environments' (2005) with Kai Lin and Geoff Dromey; 'Engineering Real-Time Communication Through Predictable Time-Triggered Execution' (2016) with René Hexel and Fawad Riasat Raja; 'Flipping a Programming Class to Improve Student Engagement and Learning' (2019) with Jolon Faichney; and 'A Flexible Communication Protocol with Guaranteed Message Delivery for Multi-Agent Systems' (2022). He teaches undergraduate and postgraduate courses in software development and web development. Additionally, Dr. Chen has featured in the School of ICT Conversation Bytes podcast, discussing solutions to problems in teaching and learning programming. His ongoing research includes advanced models for traffic flow prediction, such as PIMPC-GNN: Physics-Informed Multi-Phase Consensus Graph Neural Network (2026).