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Research Mentors
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Institution and Department
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Research Focus
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Ivet Bahar
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Pitt – Computational Biology
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Analytical models and computational methods for predicting the dynamics of large biomolecular systems and networks of proteins.
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Takis Benos
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Pitt – Computational Biology
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Protein-DNA interactions and the development of new tools for efficient ID of transcriptional regulatory signals.
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Carlos Camacho
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Pitt – Computational Biology
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Modeling of physical interactions responsible for molecular recognition; Developing new techniques for predicting protein complex strucures.
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Chakra Chennubhotla
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Pitt – Computational Biology
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Develop new image analysis methods for (i) Extracting spatio-temporal correlation hierarchy from neuronal activation profiles, (ii) Reconstructing neuronal struture from histological data, and (iii) Building automated segmentation algorithms for sub-cellular structures from microscopy data.
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Lillian Chong
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Pitt – Chemistry
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Protein structure and function, natively unfolded proteins, molecular sensors, MD simulations, distributed computing.
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Nathan Clark
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Pitt – Computational Biology
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Study of coevolutionary signatures between genes in order to infer novel interactions and functional changes throughout the genome.
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Rob Coalson
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Pitt – Chemistry, Physics, and the Center for Molecular and Materials Simulations
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Models kinetics and struture.function relations in biological ion channels.
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Lance Davidson
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Pitt - Bioengineering
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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.
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Markus Dittrich
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Pittsburgh Supercomputing Center
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Computer simulations of cellular systems.
The main focus is on using simulations to understand the structure and function of synapses, which are the connections between individual nerve cells. |
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G. Bard Ermentrout
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Pitt – Mathematics, CMU - Center for the Neural Basis of Cognition
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Application of nonlinear dynamics to problems from cell biology and physiology.
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Jim Faeder
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Pitt – Computational & Systems Biology
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Mathematical (rule-based) modeling of intracellular signal transduction pathways.
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Eleanor Feingold
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Pitt – Human Genetics
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Statistical methods for gene mapping; genetic epidemiology of Down syndrome; statistical approaches to bioinformatics.
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Madhavi Ganapathiraju
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Pitt – Biomedical Informatics and Intelligent Systems
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Systems Biology (Protein-protein interaction prediction) and Translational Bioinformatics by applying machine learning, signal processing and knowledge discovery.
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David Koes
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Pitt – Computational & Systems Biology
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Developing novel computational algorithms and building full-scale systems to support rapid and inexpensive drug discovery.
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Sanford Leuba
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Pitt – Cell Biology and Physiology
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Single molecule approaches to protein-DNA interactions.
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Timothy Lezon
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Pitt – Cell Biology and Physiology
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Developing coarse-grained models for studying large-scale protein dynamics.
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Yang Liu
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Pitt – Bioengineering
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Developing optical imaging instruments, signal and image processing tools to improve the early detection of cancer.
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Jeffry Madura
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Duquesne - Chemistry & Biochemistry and the Center for Computational Sciences
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Development and application of methods to study the structure, function, and dynamics of proteins and enzymes in solution and at interfaces.
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Kartik Mohanram
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Pitt - Electrical and Computer Engineering
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Models and algorithms for stochasticity in cellular processes
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Sandra Murray
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Pitt – Cell Biology and Physiology
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Role of gap junctions and cell-to-cell communication in endocrine cell proliferation, migration, differentiation, and hormone production using time-lapse video microscopy, transmission immuno-electron microscopy, and molecular biological techniques
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Mark Rebeiz
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Pitt – Biological Sciences
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Studying how morphology (size, shape, color, form) evolves in the animal world utilizing tools of classical developmental biology, as well as genetics, evolution, genomics, and bioinformatics.
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Roni Rosenfeld
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CMU – Computer Science, Machine Learning, and The Language Technology Institute
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Using growing databases of viral sequences to build descriptive and generative models of viral molecular evolution. Modeling the evolution of Influenza.
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Hanna Salman
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Pitt – Physics & Astronomy
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Understanding the factors that shape phenotypic variability in populations of bacteria and how the populations benefit from such variability. Studies utilize tools of physical biology, which combines physical techniques, both experimental and theoretical, with biological methods.
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John Shaffer
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Pitt – Human Genetics
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Applied statistical methods of gene mapping; genetic epidemiology of oral health.
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Sanjeev Shroff
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Pitt – Bioengineering
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Large-scale mathematical simulations of biological systems for research, education, and engineering design.
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Ian Sigal
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Pitt – Ophthalmology
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Computational and experimental methods to understand the biomechanics of the eye and soft tissue remodeling.
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Matt Smith
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Pitt - Ophthalmology and Bioengineering
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Computational approaches to modeling neuronal communication and interactions, combined with experimental techniques to measure the activity of populations of neurons.
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Pei Tang
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Pitt – Structural Biology
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Action of low-affinity drugs (general anesthetics and alcohols) on neurotransmitter-gated receptor channels.
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Tim Verstynen
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CMU - Psychology and CNBC
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Structure-function associations in response selection and sensorimotor skill learning.
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Art Wetzel
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Pittsburgh Supercomputing Center
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Image processing and large data handling, 10s of TBytes, for neural circuit reconstruction from optical and electron microscopy. This work involves both biological analysis and computational program development.
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Michael Widom
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CMU - Physics
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Professor Widom's research focuses on theoretical modeling of novel materials in condensed matter and biological physics settings. Methods of statistical mechanics, quantum mechanics and computer simulation are used to investigate structure, stability and properties of these materials.
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Sean Xie
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Pitt – Pharmaceutical Sciences/Drug Discovery Institute
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His research interests are: 1) GPCR CB2 membrane protein structure/function studies. 2) Methods and algorithms development for knowledgebase-target identifications and structure-based drug design for multiple myeloma, osteoporosis and hematopoietic stem cell expansion by using the integrated computational chemical genomics virtual screening, bioassay validation and medicinal chemistry synthesis approaches. (www.CBligand.org/xielab and www.CBLigand.org/CCGS)
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Leming Zhou
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Pitt – Health Information Management
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Agent-based, equation-based, and statistical modeling of cardiovascular disease; comparative genomics and its applications in personalized medicine
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Dan Zuckerman
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Pitt – Computational Biology
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Developing statistical-mechanics-based methods to study protein fluctuations and binding.
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