ProfessorCarnegie Mellon UniversityBiological Sciences and Chemistry Departments
The Bruchez group is focused on development and use of new biosensors to characterize cellular biology in high-throughput analysis and within living organisms. Computational image analysis, quantitation and feature extraction methods are applied to obtain insights from signal-limited datasets, with a focus on protein trafficking and subcellular physiology. The group also uses single particle tracking in biophysical systems and cultured cells to study protein translation and trafficking.
ProfessorCarnegie Mellon UniversityMechanical Engineering and Biomedical Engineering Departments
The link between mechanics and biochemistry has been implicated in a myriad of scientific and medical problems, from orthopedics and cardiovascular medicine, to cell motility and division, to signal transduction and gene expression. Most of these studies have been focused on organ-level issues, yet cellular and molecular level research has become essential over the last decade in this field thanks to the revolutionary developments in genetics, computer science, molecular biology, microelectronics, and biotechnology. Developing molecular and cellular biomechanics with relation to biochemistry promises for a bright future with potential impacts on genomics, proteomics, tissue engineering, and medical diagnostics. By examining these issues in novel manners including computational biology, he explores the linkages among these disciplines. Also, through focusing on nature inspired design principles at the molecular and cellular levels, novel approaches to technology development will be enabled.
ProfessorCarnegie Mellon UniversityChemical Engineering Department
Dr. Sahinidis is interested in computational optimization and its applications in protein structural alignment, protein structure prediction, macromolecular structure determination via experimental techniques, metabolic network inference and directed improvement, drug design. He is currently very interested in protein structural (3D) alignment.
Research ProfessorCarnegie Mellon UniversityThe Robotics Institute
Dr. Schneider is interested in active learning algorithms for efficiently controlling the experimental process during the creation and fitting of biological models. He believes appropriate selection algorithms will yield an order of magnitude improvement in the model discovery process. His previous efforts in this area have focused on in vivo CNS drug discovery.
ProfessorCarnegie Mellon UniversityMachine Learning Department
Dr. Xing develops statistical models and machine learning algorithms for biological network inference and characterization, cis-regulatory module decoding, temporal/spatial gene expression analysis, regulatory evolution modeling, quantitative trait locus mapping, genome polymorphism patterning, and population genetic analysis. He is applying these quantitative approaches to investigate the mechanisms of cancer development and metazoan morphagenesis. He is also interested in developing statistical machine learning methodologies including graphical models, Bayesian approaches, inference algorithms, and learning theories for analyzing and mining high-dimensional, longitudinal, and relational data; and their applications in text/image mining, vision, and natural language processing.
Assistant ProfessorCarnegie Mellon UniversityComputer Science Department
Jean Yang is interested in designing programming models, language implementation strategies, and tools to make it easier to create software. Areas of focus include the security and privacy of medical data and developing tools for creating executable models of protein interactions.