Research Mentors

Institution and Department

Research Focus

Ivet Bahar

Pitt - Computational & Systems Biology

Analytical models and computational methods for predicting the dynamics of large biomolecular systems and networks of proteins.

Takis Benos

Pitt - Computational & Systems Biology

Protein-DNA interactions and the development of new tools for efficient ID of transcriptional regulatory signals.

Carlos Camacho

Pitt - Computational & Systems Biology

Modeling of physical interactions responsible for molecular recognition; Developing new techniques for predicting protein complex strucures.

Anne-Ruxandra Carvunis

Pitt - Computational & Systems Biology

How do new genes emerge and acquire new functions during evolution? (sample project)

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

Chakra Chennubhotla

Pitt - Computational & Systems Biology

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)

Lillian Chong

Pitt – Chemistry

Protein structure and function, natively unfolded proteins, molecular sensors, MD simulations, distributed computing.

Nathan Clark

Pitt - Computational & Systems Biology

Study of coevolutionary signatures between genes in order to infer novel interactions and functional changes throughout the genome. (sample project)

Rob Coalson

Pitt – Chemistry, Physics, and the Center for Molecular and Materials Simulations

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)

Vaughn Cooper

Pitt – Microbiology & Molecular Genetics

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)

Lance Davidson

Pitt - Bioengineering

Modeling 3D multicellular arrays for investigating emergent properties of tissue self-assembly. (sample project)

Jacob D. Durrant

Pitt - Biology

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)

G. Bard Ermentrout

Pitt – Mathematics, CMU - Center for the Neural Basis of Cognition

Application of nonlinear dynamics to problems from cell biology and physiology. (sample project)

Jim Faeder

Pitt – Computational & Systems Biology

Mathematical (rule-based) modeling of intracellular signal transduction pathways. (sample project)

David Koes

Pitt – Computational & Systems Biology

Development of algorithms and systems for computational drug discovery (sample project)

Dennis Kostka Pitt - Developmental Biology Computational genomics with a focus on development and cellular differentiation, and single cell RNA sequencing. (sample project)

Miler Lee

Pitt – Biological Sciences

Gene regulation during early development and cellular reprogramming; comparative genomics

Robin Lee

Pitt – Computational & Systems Biology

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)

Timothy Lezon

Pitt – Computational & Systems Biology / Drug Discovery Institute

Computational systems biology of signaling pathways.

Bing Liu Pitt - Computational & Systems Biology Mathematical modeling of signaling network dynamics with formal verification and machine learning techniques. (sample project)

Jeffry Madura

Duquesne - Chemistry & Biochemistry and the Center for Computational Sciences

Development or systems engineering tools; modeling, analysis, and control of biomedical systems (sample project)

Natasa Miskov-Zivanov Pitt - Electrical and Computer Engineering Automation of learning big mechanisms in biology. Systems and synthetic biology. (sample project)

Sandra Murray

Pitt – Cell Biology and Physiology

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

Robert Parker Pitt - Chem/Petroleum Engineering Development or systems engineering tools; modeling, analysis, and control of biomedical systems (sample project)

Mark Rebeiz

Pitt – Biological Sciences

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.

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. Studies utilize tools of physical biology, which combines physical techniques, both experimental and theoretical, with biological methods.

John Shaffer

Pitt – Human Genetics

Applied statistical methods of gene mapping;  genetic epidemiology of oral health. (sample project)

Sanjeev Shroff

Pitt – Bioengineering

Large-scale mathematical simulations of biological systems for research, education, and engineering design.

Ian Sigal

Pitt – Ophthalmology

Computational and experimental methods to understand the biomechanics of the eye and soft tissue remodeling.

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.

Pei Tang

Pitt – Structural Biology

Action of low-affinity drugs (general anesthetics and alcohols) on neurotransmitter-gated receptor channels.

Shikhar Uttam Pitt - Pitt - Computational & Systems Biology Learning intra-tumor heterogeneity in compressed domains: an information theoretic perspective. (sample project)

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.

Tim Verstynen

CMU - Psychology and CNBC

Structure-function associations in response selection and sensorimotor skill learning.

Art Wetzel

Pittsburgh Supercomputing Center

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.

Sean Xie

Pitt – Pharmaceutical Sciences/Drug Discovery Institute

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. ( and

Jianhua Xing

Pitt - Computational & Systems Biology

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)

Leming Zhou

Pitt – Health Information Management

Agent-based, equation-based, and statistical modeling of cardiovascular disease; comparative genomics and its applications in personalized medicine (sample project)