Systems Biology – TECBio REU

Research Mentors	Institution and Department	Research Focus
Anne-Ruxandra Carvunis	Pitt – Computational Biology	My research aims at understanding the molecular mechanisms of change and innovation by examining systems biology in the light of evolution and evolution in the light of systems biology.
Rob Coalson	Pitt – Chemistry, Physics, and the Center for Molecular and Materials Simulations	Computational approaches to study ion channel gating and transport.
Vaughn Cooper	Pitt – Microbiology and Molecular Genetics	Studying the evolution, ecology, and genome dynamics of experimental and clinical microbial populations.
Lance Davidson	Pitt – Bioengineering	Multidisciplinary (mathematics, developmental biology, biophysics, and bioengineering) approach to understanding how molecular and genetic programs drive the formative tissue mechanics and self-assembly processes that generate living structures in developing embryos.
G. Bard Ermentrout	Pitt – Mathematics and the CMU-Center for the Neural Basis of Cognition	Application of nonlinear dynamics to problems from cell biology and physiology.
Jim Faeder	Pitt – Computational & Systems Biology	Mathematical (rule-based) modeling of intracellular signal transduction pathways.
Robin E.C. Lee	Pitt – Computational Biology	Quantitative imaging, microfluidics, and mathematical models to study how dynamic molecular signals transmit information in single cells.
Timothy Lezon	Pitt – Cell Biology and Physiology	Computational systems biology of signaling pathways.
Bing Liu	Pitt – Computational Biology	Development of mathematical models to study the dynamics of signaling networks; development of formal verification and machine learning based techniques for computational modeling and analysis of biological systems.
Natasa Miskov-Zivanov	Pitt – Bioengineering	Automation of learning big mechanisms in biology. Systems and synthetic biology. Emerging technologies and Internet of Things in medicine
Robert S. Parker	Pitt – Chemical and Petroleum Engineering	Systems medicine – mathematical modeling of disease (cancer, critical care/inflammation/sepsis, diabetes, cystic fibrosis) to support patient-tailored treatment decision-making.
Roni Rosenfeld	CMU – Computer Science, Machine Learning, and The Language Technology Institute	Using growing databases of viral sequences to build descriptive and generative models of viral molecular evolution. Modeling the evolution of Influenza.
Jonathan Rubin	Pitt – Mathematics	Application of dynamical systems to modeling of inflammation and other aspects of physiology.
Hanna Salman	Pitt – Physics & Astronomy	Understanding the factors that shape phenotypic variability in populations of bacteria and how the populations benefit from such variability.
Jason Shoemaker	Pitt – Chemical and Petroleum Engineering	The Shoemaker Lab focuses on systems immunology. We model our body’s natural, dynamic responses to disease and develop mathematical tools to support these modeling challenges. Our model systems are multiscale with applications in pathogen detection and clearance, cancer immune evasion, and more. We are very interdisciplinary – most projects involve collaborations with UPMC or our international collaborators in Japan and Switzerland.
Matt Smith	Pitt – Ophthalmology and Bioengineering	Computational approaches to modeling neuronal communication and interactions, combined with experimental techniques to measure the activity of populations of neurons.
Ben Van Houten	Pitt – Pharmacology and Chemical Biology	The formation and repair of DNA damage in nuclear and mitochondrial genomes, with particular interest in the structure and function of proteins that mediate nucleotide excision repair and the role of oxidative stress in human disease.
Jianhua Xing	Pitt – Computational Biology	Computational and experimental quantitative biology approaches to study the dynamics and (genetic and epigenetic) regulatory mechanism of cell phenotype changes.
Leming Zhou	Pitt – Health Information Management	Agent-based, equation-based, and statistical modeling of cardiovascular disease; comparative genomics and its applications in personalized medicine.