My primary research interests reflect my experience and subject matter expertise gained during my past career as an air traffic controller and concern the impact of modernization (automation) of air traffic control (ATC) and air traffic management (ATM) on the performance of individual controllers working within the system. ATC is, however, only one example of the kinds of complex and dynamic task environments I am interested in. Task demands similar to those placed on air traffic controllers can be identified in numerous other domains, including process control and health care.

My goal is to develop cognitive models of operators’ temporal awareness that will allow for prediction of their performance (influenced by subjective workload) under various operational demands (task load), providing a scientific foundation for further design and development of large-scale human-machine systems. My pursuit of this goal has been characterized by the necessity of moving back and forth between highly controllable experimental settings and high-fidelity simulations and data obtained from operational environments, This, in turn, has required development of comparable metrics in each realm.

Given the dynamic and multifaceted and time-critical nature of ATC, the explicit focus on time has served both of my immediate research goals: to (1) understand the contributions of temporal cognitive processes on human performance and (2) develop methods of objective human performance measurement that could ultimately be collected and analyzed concurrently with the performance. These closely intertwined objectives are based on the fundamental notion of the criticality of anticipatory performance in control of complex, dynamic systems.

Timing data (i.e., events unfolding in time in simulated scenarios and operational environments as well as timing of operators’ overt responses to them) can also be relatively easily obtained under both experimental and naturalistic conditions. Time is a variable that is common to the human, the task, and the environment, and offers thus a common unit of measurement of human performance in the context of the task.

Timing data can furthermore be used to infer the goodness of the temporal dimension of the operator’s mental model of the task or system being controlled. Temporal performance measures in a variety of tasks and contexts will also allow for the testing and evaluation of hypotheses and models put forward in the research literature (e.g., on prospective memory), hence making a contribution to basic psychological research.