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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 & Systems 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 & Systems 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 & Systems 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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Anne-Ruxandra Carvunis
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Pitt - Computational & Systems Biology
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How do new genes emerge and acquire new functions during evolution? (sample project)
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| Mary Cheng |
Pitt - Computational & Systems Biology |
Molecular mechanisms of ion channels and transporters, and regulation of protein functions by drugs, membrane lipids and regulatory proteins |
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Chakra Chennubhotla
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Pitt - Computational & Systems 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. (sample project)
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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 & Systems Biology
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Study of coevolutionary signatures between genes in order to infer novel interactions and functional changes throughout the genome. (sample project)
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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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Computational approaches to modeling biological nanopores, including ion permeation and gating in membrane spanning ion channel proteins, and transport of large biomolecules through the Nuclear Pore Complex. (sample project)
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Vaughn Cooper
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Pitt – Microbiology & Molecular Genetics
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Understanding how bacterial populations evolve and adapt to colonize hosts and cause disease. By studying evolution-in-action, both in experimental populations and in ongoing infections, and using the latest methods in genomic sequencing, we seek to identify mechanisms of bacterial adaptation in vitro and in vivo. (sample project)
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Lance Davidson
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Pitt - Bioengineering
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Modeling 3D multicellular arrays for investigating emergent properties of tissue self-assembly. (sample project)
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Jacob D. Durrant
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Pitt - Biology
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Computer-aided drug design to intelligently identify small-molecule ligands that disrupt or enhance the critical interactions between these “drug targets” and other microscopic partners. (sample project)
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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. (sample project)
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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. (sample project)
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David Koes
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Pitt – Computational & Systems Biology
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Development of algorithms and systems for computational drug discovery (sample project)
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| Dennis Kostka |
Pitt - Developmental Biology |
Computational genomics with a focus on development and cellular differentiation, and single cell RNA sequencing. (sample project) |
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Miler Lee
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Pitt – Biological Sciences
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Gene regulation during early development and cellular reprogramming; comparative genomics
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Robin Lee
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Pitt – Computational & Systems Biology
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Our research combines principles of systems and synthetic biology to understand how information flows through signal transduction circuits to regulate fate decisions in single cells. (sample project)
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Timothy Lezon
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Pitt – Computational & Systems Biology / Drug Discovery Institute
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Computational systems biology of signaling pathways.
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| Bing Liu |
Pitt - Computational & Systems Biology |
Mathematical modeling of signaling network dynamics with formal verification and machine learning techniques. (sample project) |
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Jeffry Madura
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Duquesne - Chemistry & Biochemistry and the Center for Computational Sciences
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Development or systems engineering tools; modeling, analysis, and control of biomedical systems (sample project)
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| Natasa Miskov-Zivanov |
Pitt - Electrical and Computer Engineering |
Automation of learning big mechanisms in biology. Systems and synthetic biology. (sample project) |
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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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| Robert Parker |
Pitt - Chem/Petroleum Engineering |
Development or systems engineering tools; modeling, analysis, and control of biomedical systems (sample project) |
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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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Jonathan Rubin
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Pitt - Mathematics
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Application of dynamical systems to modeling of inflammation and other aspects of physiology.
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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. (sample project)
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Jason Shoemaker
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Pitt – Chemical Engineering and Systems Immunology
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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.
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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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| Shikhar Uttam |
Pitt - Pitt - Computational & Systems Biology |
Learning intra-tumor heterogeneity in compressed domains: an information theoretic perspective. (sample project) |
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Ben Van Houten
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Pitt – Pharmacology and Chemical Biology
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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.
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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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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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Jianhua Xing
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Pitt - Computational & Systems Biology
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Computational and experimental quantitative biology approaches to study the dynamics and (genetic and epigenetic) regulatory mechanism of cell phenotype changes. The lab is highly interdisciplinary including physics, mathematical and computational modeling, and cell biology studies. (sample project)
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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 (sample project)
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