Professor Min Chen
College Function:
Professor of Scientific Visualisation
Member of:
Governing Body
Affiliations:
Oxford e-Research Centre, MPLS
Research Interests:
Min Chen developed his academic career in Wales between 1984 and 2011, and is an internationally established scientist in the field of visualization, with significant contributions in volume graphics, video visualization and theory of visualization. His current research themes include:
- Visualizing "time" without using "time". Although animation is an intuitive way to visualizing temporal data (e.g., videos), it is not only time-consuming but also suffers from several shortcomings, such as being prone to change blindness, excessive demand on full attention, and high cognitive load due to limited short-term memory. Hence any smart visualization technique that enables users to gain insight about complex temporal data without using animation will have a profound impact in many practical applications such as medicine and sports.
- Theory of visualization. While the advantages of using visualization are well appreciated, our theoretic understanding about why and how visualization works is very limited. On one hand, it is a reasonable assumption that the science of visualization should be built upon a number of theories established in different disciplines. On the other hand, visualization provides a unique platform for us to develop a deep understanding of the theoretic models in computation, communication and cognition.
- Causality discovery technology. Causality is the fabric of our dynamic world. Is it possible to develop a new technology that can help humans to analyse and reason causality based on observation, experimentation and acquired knowledge in a systematic manner? The data deluge provides us with both the motivation and opportunity to develop such a technology.
Recent Activities
After many years of conventional academic life in Wales involving a wide range of research, teaching and administration activities, it is precious to have the opportunity to concentrate on research activities in Oxford. I have a number of ongoing research projects, including an EPSRC-funded project on video visualization, a JISC-funded function on text corpora visualization, and an industrial project funded by Laing O'Rourke. A number of my recent projects were (or are being) carried out in collaboration with Purdue, Utah, Rutgers, UNC Charlotte (USA); Stuttgart (Germany); Swansea, Cardiff, OCCAM, OCMR and ISA (UK).
The following papers exemplify some of the emerging research topics in visualization.
- M. Chen, A. Trefethen, R. Banares-Alcantara, M. Jirotka, B. Coecke, T. Ertl and A. Schmidt, From data analysis and visualization to causality discovery, IEEE Computer, 44(10):84-87, 2011.
- M. Chen and H. Jaenicke, An Information-theoretic Framework for Visualization, IEEE Transactions on Visualization and Computer Graphics, 16(6):1206-1215, 2010.
- M. Chen, D. Ebert, H. Hagen, R. S. Laramee, R. van Liere, K.-L. Ma, W. Ribarsky, G. Scheuermann and D. Silver, Data, Information and Knowledge in Visualization, IEEE Computer Graphics and Applications, 29(1):12-19, 2009.
See here for a full publication list.
Relevant Links
www.oerc.ox.ac.uk/people/min-chen
Professor Min Chen
College Function:
Professor of Scientific Visualisation
Member of:
Governing Body
Affiliations:
Oxford e-Research Centre, MPLS
Research Interests:
Min Chen developed his academic career in Wales between 1984 and 2011, and is an internationally established scientist in the field of visualization, with significant contributions in volume graphics, video visualization and theory of visualization. His current research themes include:
- Visualizing "time" without using "time". Although animation is an intuitive way to visualizing temporal data (e.g., videos), it is not only time-consuming but also suffers from several shortcomings, such as being prone to change blindness, excessive demand on full attention, and high cognitive load due to limited short-term memory. Hence any smart visualization technique that enables users to gain insight about complex temporal data without using animation will have a profound impact in many practical applications such as medicine and sports.
- Theory of visualization. While the advantages of using visualization are well appreciated, our theoretic understanding about why and how visualization works is very limited. On one hand, it is a reasonable assumption that the science of visualization should be built upon a number of theories established in different disciplines. On the other hand, visualization provides a unique platform for us to develop a deep understanding of the theoretic models in computation, communication and cognition.
- Causality discovery technology. Causality is the fabric of our dynamic world. Is it possible to develop a new technology that can help humans to analyse and reason causality based on observation, experimentation and acquired knowledge in a systematic manner? The data deluge provides us with both the motivation and opportunity to develop such a technology.
Recent Activities
After many years of conventional academic life in Wales involving a wide range of research, teaching and administration activities, it is precious to have the opportunity to concentrate on research activities in Oxford. I have a number of ongoing research projects, including an EPSRC-funded project on video visualization, a JISC-funded function on text corpora visualization, and an industrial project funded by Laing O'Rourke. A number of my recent projects were (or are being) carried out in collaboration with Purdue, Utah, Rutgers, UNC Charlotte (USA); Stuttgart (Germany); Swansea, Cardiff, OCCAM, OCMR and ISA (UK).
The following papers exemplify some of the emerging research topics in visualization.
- M. Chen, A. Trefethen, R. Banares-Alcantara, M. Jirotka, B. Coecke, T. Ertl and A. Schmidt, From data analysis and visualization to causality discovery, IEEE Computer, 44(10):84-87, 2011.
- M. Chen and H. Jaenicke, An Information-theoretic Framework for Visualization, IEEE Transactions on Visualization and Computer Graphics, 16(6):1206-1215, 2010.
- M. Chen, D. Ebert, H. Hagen, R. S. Laramee, R. van Liere, K.-L. Ma, W. Ribarsky, G. Scheuermann and D. Silver, Data, Information and Knowledge in Visualization, IEEE Computer Graphics and Applications, 29(1):12-19, 2009.
See here for a full publication list.
Relevant Links
www.oerc.ox.ac.uk/people/min-chen