Our research is motivated by the need for efficient, economically viable, and environmentally benign chemical products and processes. In response to this need, our projects range in focus from the process scale to the global scale. Most projects are multidisciplinary in nature and overlap with other fields such as statistics, signal processing, bioinformatics, systems ecology, and industrial ecology. Current research is focused on two broad areas. Efficient Process Engineering via Bayesian and Multiscale Methods Efficient engineering of chemical and manufacturing processes requires efficient methods for solving individual tasks and integration between related tasks. Examples of such tasks include feedback control, process monitoring, state and parameter estimation, process design, and equipment scale-up. Ideally, solution techniques for all tasks should be able to make maximum use of all the available information. Such information is usually in the form of measured data, fundamental or empirical process models, heuristic knowledge, and experience.  We are developing new methods for process engineering tasks that can maximize the use of available process knowledge and data. These methods rely on the rigorous foundation of Bayesian statistics for combining different types of information, and wavelet analysis for capturing the multiscale character inherent in all systems. Bayesian statistics provides a statistically sound way of combining prior knowledge with measurements to estimate the probability distribution of unknown variables. Wavelet analysis is an approach for capturing information about events occurring with different localization in time, space, or frequency.

Current research is developing multiscale and Bayesian approaches for fault detection and diagnosis, linear and nonlinear modeling, and state and parameter estimation in nonlinear dynamic systems. The resulting methods are usually more accurate than existing approaches, and can improve the performance and profitability of processing systems. We are also using our methods to extract knowledge from data obtained from complex chemical and biological systems. Current research is directed towards discovering new cancer drugs from genomic, pharmaceutical, and chemical databases Ecologically and Economically Conscious Process Engineering As chemical engineers, we have been tremendously successful in developing new products and technologies for enhancing our quality of life. Unfortunately, we have been much less successful in ensuring the environmental viability of our products and processes. With increasing realization that the current practice of many industrial activities cannot be sustained for long, there is a critical need for incorporating ecological and economic factors in engineering decisions.  We are developing novel methods for ecologically and economically conscious process engineering based on treating industrial and ecological systems as networks of energy flow. Ecological systems convert global inputs into ecological resources and services, while economic systems convert natural resources and services into economic goods and services and waste. Our work combines methods from systems engineering, systems ecology, and life cycle assessment to analyze products and processes at multiple scales. The thermodynamic concept of exergy or available energy provides the link between various methods and disciplines.