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Sanders, Palecek, Shusta and Ceglarek win NSF CAREER awards

Mechanical Engineering Assistant Professor Scott Sanders, Chemical and Biological Engineering Assistant Professors Sean Palecek and Eric Shusta and Industrial and Systems Engineering Assistant Professor Darek Ceglarek are 2003 recipients of the National Science Foundation's prestigious Faculty Early Career Development Award (CAREER). The awards are granted on the basis of creative career-development plans that effectively integrate research and education.

Scott T. Sanders

Scott T. Sanders (large image)

Scott Sanders

Sanders' project aims to develop laser-based sensors for monitoring gas and liquid properties with sub-millisecond time responses. The sensors will be applied to fundamental test beds, such as Bunsen flames, as well as practical systems such as internal combustion engines. Sanders is affiliated with the Engine Research Center.

According to Sanders, the project will enhance the use of laser sensors as a diagnostic tool. Most existing sensors measure either continuous data (such as a time history of temperature at a certain point) or spatially resolved data (such as a single image of gas temperature). Sanders says that this project will combine these two approaches, offering data that are both continuous and spatially resolved (such as a movie of gas temperature).

The project integrates research and education by incorporating active learning techniques and creative problem solving into the undergraduate thermal-fluid sequence. In addition, the project will be coupled with a graduate-level course in optical techniques and provide research opportunities for undergraduate students.

Sean P. Palecek

Sean P. Palecek (large image)

Sean Palecek

Chemical and Biological Engineering Assistant Professor Sean Palecek will apply his grant to the creation of a cell-based biosensor for detecting DNA damaging agents. His goal is to take advantage of eukaryotic cells which have evolved extremely sensitive and rapid mechanisms to sense and respond to DNA damage.

The first stage of his project will quantitatively determine the dose and time-dependence of DNA damage-sensitive gene transcription in the budding yeast Saccharomyces cerevisiae in response to a panel of selected damaging agents. Clusters of genes sensitive and selective for DNA-damaging agents will serve as the basis for biosensor design. Next, the damage-regulated genes will be replaced with reporter genes to facilitate measurement of gene transcription. The third stage of the project will enhance the sensitivity of the cells to DNA damage by disabling endogenous DNA damage pathways.

Palecek's project will create new laboratory materials in molecular and cellular bioengineering for undergraduate engineering and high school students. The labs will illustrate the ability to quantitatively control how cells respond to environmental stimuli by altering the genetic makeup of the cells.

Eric V. Shusta

Eric V. Shusta (large image)

Eric Shusta

Chemical and Biological Engineering Assistant Professor Eric Shusta will use his award to develop a novel technological platform for protein production optimization.

The use of protein therapeutics for the treatment of a variety of diseases is a rapidly expanding industry. Over 370 protein medicines are currently in clinical trials or awaiting approval by the Food and Drug Administration. This number has increased dramatically since 1995 when only 234 biopharmaceuticals were in development. These medicines target more than 200 diseases including cancer, heart disease, arthritis, Alzheimer's, AIDS and cystic fibrosis and represent more than $26 billion in research expenditures annually. However, one of the major hurdles in the development of a protein therapeutic is production of the recombinant protein at a level that can meet demand in an economically feasible manner. Present methods for the optimization of protein expression hosts involve either random mutagenesis of a host strain followed by laborious screening or ad hoc cellular manipulation.

Shusta's approach will combine yeast genetics with yeast surface display technology to engineer cells for increased production of a model therapeutic protein. Yeast surface display will provide a quantitative assessment of protein expression level on a single cell basis and make the rapid screening of combinatorial libraries of yeast variants possible. Due to facile yeast genetics, the cellular constituents that mediate high protein producing strains can be readily identified and will help develop a global network of protein interactions critical to high yield protein production.

In coordination with the research objectives, Shusta will develop and implement a composite classroom and laboratory course that introduces molecular and cellular level design strategies. This course sequence will train undergraduate and graduate students in modern combinatorial methods for the engineering design of RNA, DNA, proteins and cells.

Dariusz (Darek) Ceglarek

Dariusz (Darek) Ceglarek (large image)

Darek Ceglarek

Dimensional variation is a major issue with many U.S. manufacturing industries. High levels of variation can cause expensive product and process design changes after the design stage. It also can lead to long ramp-up time during new product launch, especially for automotive and aerospace assembly lines, and low production yield below design intent expectations. Since some manufacturing- and design-induced variation is inevitable, it is important to have methods for identifying root causes of dimensional variation, as well as a thorough understanding of the sources of variation during a new product launch.

Industrial and Systems Engineering Assistant Professor Darek Ceglarek hopes to develop a generic multistage assembly process model, stream of variation (SOVA) system which potentially can be applied widely across discrete manufacturing industries, such as automotive, aerospace, shipbuilding and appliance manufacturing, where product dimensional integrity is of crucial importance. SOVA will take into account key product- and process-control characteristics with varying resolution that can be used during design, launch and full production phases in complex assembly processes. Based on a generic computer-aided design and manufacturing system integrated with statistical analysis to predict early-design-phase process performance, companies can apply the model during a manufacturing system's design, launch and full production phases. The project aims to integrate CAD and CAM models with statistical analysis to predict manufacturing-process dimensional variability during design as it relates to compliant parts. In addition, it will facilitate math-based design and manufacturing by synthesizing product and process variables to expand the classic "part interchangeability" concept into "process interchangeability," and train industrial engineers in statistical methods and their application in CAD and CAM systems.

By integrating research with education, Ceglarek will develop the graduate courses, "Information-Based Design and Manufacturing," and "Reconfigurable/Reusable Manufacturing Systems," and one undergraduate course, "Product and Process Variability Reduction." He also will partner with students and science faculty in Madison-area high schools to develop grade-specific projects and problems by visualizing various geometric phenomena that occur in industrial settings. Among other efforts, he will organize exchange programs and long-distance courses with Berlin University of Technology, Hong Kong University of Science and Technology and Chalmers University of Technology in Sweden.