I am a graduate student at the Lab for Advanced Software Engineering Research (LASER) in the Department of Computer Science at the University of Massachusetts Amherst.
The goal of my research has been to study and develop techniques for improving the quality and safety of human-intensive processes. In particular, my research interests include requirements engineering, specification and validation of formal process models, process modeling languages, process guidance and exception handling patterns in processes. I have been studying the above in the context of continous process improvement and I have been modeling and analyzing medical processes as a case study.
There is evidence that important and critical processes (such as medical processes) performed in our everyday lives contain defects that could lead to a variety of negative consequences. These processes, however, are complex and non-trivial to reason about. A natural approach to understanding and reasoning about such complex processes is to create models which preserve the features of interest but leave out other irrelevant details that unnecessarily complicate the understanding and the analysis. It turns out, however, that it is hard to create accurate models and thus any meaningful process analysis greatly depends on the validation of the process model, i.e. on increasing the confidence that the model is actually an accurate representation of the real process. I am interested in the problem of validating process models.
To be able to perform rigorous reasoning and analysis of process models, these models need to be specified in a notation or a language with precisely defined semantics. I am interested in studying process modeling languages that enable such rigorous analysis. I am also investigating techniques to tackle requirements engineering issues that arise when one attempts to elicit a process from process participants (or other stakeholders) and convert the elicited information into a precise process model.
Many errors in processes occur during exceptional/non-typical scenarios. These errors may occur because people are not well-trained to deal with exceptional situations that often add time pressure, or because technology support can actually become a burden if it was not designed with exceptional situations in mind. I am interested in studying exceptional scenarios in processes and how they can be modeled to facilitate the understanding, analysis, and improvement of processes.
Once a process model has been carefully specified, validated, and rigorously analyzed, this process model can then be used to guide the execution of a process. The hope is that process guidance can improve the overall quality of human-intensive processes by ensuring that important tasks are not omitted, that tasks are not done out of order, or that the information presented to process participants is relevant to the current phase of the process.
