Faculty List

Program Directors: Ziv Bar-Joseph (CMU – zivbj@cs.cmu.edu) and James Faeder (Pitt – faeder@pitt.edu)

Program coordinators: Kelly Gentille (kmg120@pitt.edu) and Nicole Stenger (nstenger@cs.cmu.edu).

Core training faculty are those who maintain active participation in the program by advising students, teaching, and/or serving on program committees. Affiliate faculty are those who have expertise in program-related areas and have expressed an interesting in advising program students.

  • All
  • Core Faculty
  • Affiliate Faculty
  • Bioimage Informatics
  • Cellular and Systems Modeling
  • Computational Genomics
  • Computational Structural Biology
Distinguished Professor & JK Vries Chair, Computational & Systems Biology, Pitt
Biomolecular systems dynamics, multiscale modeling and simulations, computer-aided drug design, molecular and systems pharmacology, bridging sequence evolution, structure and function.
Assistant Professor, Physics CMU
Theory and computational models of living systems and processes
Program Director CPCB, FORE Systems Professor of Computer Science, CBD, MLD, CMU
Currently on leave of absence
Our group develops computational methods for understanding the interactions, dynamics and conservation of complex biological systems.
Professor, Computational and Systems Biology, Pitt
We develop new computational methods to model biological processes and mine high-dimensional, multi-modal biomedical data.
Professor; Assoc Vice Chancellor, Science Strategy & Planning (HS);Pittsburgh Foundation Professor and Director, Inst for Personalized Medicine, Pitt
Dr. Berg’s research focuses the relationships between the structures and functions of biological molecules.
Director, MBIC; Associate Professor, Chemistry and Biological Sciences, CMU
Our work is focused on developing tools that couple the best of the synthetic dyes with the advantages of genetic targeting…
Associate Professor, Computational and Systems Biology, Pitt
We develop new technologies to predict and model protein structures, their physical interactions, and substrates.
Assistant Professor, CBD, CMU
I work to quantitatively understand the evolutionary architecture of intelligent, collective systems, using the tools of dynamical systems, network theory, population genetics, machine learning and statistical inference, and widely available, yet underused, datasets.
Assistant Professor, Computational and Systems Biology, Pitt
Our research aims at understanding the molecular mechanisms of evolutionary change and innovation by examining systems biology in the light of evolution and evolution in the light of systems biology.
Professor, Pediatrics, Pitt
We develop statistical and computational methods for analyzing bulk and single-cell multi-omics data and understanding complex diseases such as childhood asthma and age-related macular degeneration.
Assistant Professor, Computational and Systems Biology, Pitt
We aim to establish comprehensive high-throughput multi-omics single-cell analysis including genome, epigenome, transcriptome, proteome, functional, and morphological methods. With large amounts of data collected from high-throughput single-cell multi-omics analysis, machine learning techniques can predict patient prognosis and suggest treatments for precision medicine.
Associate Professor, Computational Biology, Pitt
We investigate the molecular and cellular origins of human epithelial malignancies through computational approaches.
Assistant Professor, Computational Biology, Pitt
The goal of Dr. Chikina’s research is to use genome scale data to advance our understanding of how genes contribute to the function of a complex organism, in health and disease.
Associate Professor, Chemistry, Pitt
Research in the Chong lab involves the development and application of molecular simulation approaches to model a variety of biophysical processes.
Professor, Computer Science, Pitt
Database Systems, Mobile and Pervasive Data Management, Distributed Computing, Operating Systems, Real-Time Systems.
Professor, Chemistry, Pitt
Quantum Dynamics Theory, with Application to Condensed Phase Systems; Colloid Science: Structural and Dynamics of Charged Polystyrene Sphere Suspensions; Design of Dielectric Waveguides.
Professor, Biomedical Informatics, Pitt
Application of decision theory, probability theory, Bayesian statistics, and artificial intelligence to biomedical informatics research problems.
Associate Professor, Microbiology and Molecular Genetics, Pitt
We study evolution-in-action in the laboratory, in infections, and in cancers using genomics to identify and ultimately predict adaptations.
Chemical & Biomedical Engineering, CMU
Using rheological, biophysical and optical techniques to understand the structure and organization of the cell nucleus.
Assistant Professor, Immunology, Pitt
Our research focuses on the development and use of machine-learning, high-dimensional statistical and topological network-analyses methods for biologically meaningful integration of multi-omic datasets. These analyses help us understand immune mechanisms in a wide range of contexts, encompassing both natural and vaccine-mediated immunity.
Professor, Bioengineering, Pitt
Reverse Engineering Morphogenesis – From Cell Motility & ECM to Tissue Mechanics.
Biological Sciences, CSD, CMU
Computational molecular biology and computational genomics; especially, the evolution of genomic organization and function.
Assistant Professor, Biological Sciences, Pitt
Develop broadly applicable, innovative computer-aided drug design (CADD) techniques and apply those techniques to further infectious-disease, neurological, and cancer drug discovery.
Professor, Mathematics, Pitt
Dr. Ermentrout’s main focus is in the area of mathematical neuroscience where he tries to understand the patterns of activity in networks of neurons.
Program Director CPCB, Associate Professor, Computational Biology, Pitt
Developing mathematical models of biological regulatory processes that integrate specific knowledge about protein-protein interactions.
Professor, CSD, MLD,CBD, CMU
Currently on leave of absence
Data Mining for graphs and streams. Fractals, self-similarity and power laws. Indexing and data mining for video, biological and medical databases.
Professor, Public Health, Pitt
Statistical methods for complex family-based datasets. Detecting identity-by-descent and testing relationships using dense (sequence or chip) data.
Associate Professor, Biomedical Informatics, Pitt
Pattern mining whole-genome and whole-proteome sequences, with application of suffix array data structures for preprocessing genome sequences.
Associate Professor, Biomedical Informatics, Pitt
The design and development of computational methods for solving clinically relevant biological problems.
Assistant Professor, Immunology, Pitt
Our lab uses quantitative approaches to understand how cells process stimuli to determine the appropriate functional response. Identifying the activating receptors, kinases and transcription factors that make up signaling pathways is necessary but not sufficient to predict how a cell will respond.
Distinguished Professor, Structural Biology, Pitt
The molecular and atomic details that govern specificity in a variety of cellular interactions and that result in the amazing functional diversity observed in living organisms.
Professor, Ophthalmology, Pitt
We study eye development and disease. We’re particularly interested in the genomic and epigenomic regulation of retinal development and regeneration.
Professor, Biological Sciences, Pitt
The molecular genetics of the mycobacteria and their mycobacteriophages.
Associate Professor, Computer Science, Pitt
The development of modern machine learning technologies for analysis of high dimensional time-series data in electronic health record (EHR) data and their application in clinical decision support and clinical alerting.
Assistant Professor, Biological Sciences, CMU
Understanding the role of bacteria in both health and disease.
Professor & Department Head, Biological Sciences, CMU
How genomes control cell fate decisions during embryonic development and also later regeneration.
Assistant Professor, Chemistry, CMU
Theoretical and computational chemistry, machine learning, cheminformatics, drug discovery, computer-aided molecular design, materials informatics
Associate Professor, Biomedical Informatics, Pitt
We apply artificial intelligence, machine learning, Bayesian, and other computational methods to problems in biology, medicine, and translational research.
Assistant Professor, Immunology, Pitt
Characterizing the antigenic targets of CD8+ T cells and regulatory T cells in anti-tumor and autoimmune T cell responses and probing the mechanistic basis of cross-reactivity of T cells between self- and pathogen-derived targets
Professor, Computational Chemistry, Associate Director, Center for Research Computing, Pitt
Theory and experimental studies of molecules and clusters, reaction at surfaces, electron and proton localization transfer in polyatomic molecules and waterclusters.
Program Associate Director, Associate Professor, CBD, CS, CMU
Developing statistical machine learning techniques to address significant methodological problems in computational genomics.
Program Director CPCB, Herbert A. Simon Professor of Computer Science, CBD, CMU
Designing ML, combinatorial, and optimization algorithms to extract insight from genomics data.
Assistant Professor, Computational Biology, Pitt
We develop computational algorithms and full-scale systems to support rapid and inexpensive drug discovery and apply these methods to develop novel therapeutics.
Assistant Professor, Developmental Biology, Pitt
We model epigenomic marks during differentiation and development, and build methods to elucidate the role of transcriptional enhancer sequences in vertebrate left-right patterning.
Associate Professor, Chemistry, CMU
Understanding the work of membrane proteins, such as receptors, signal transduction proteins, toxins and ion channels.
Associate Professor, CS, CBD, CMU
Personalized Medicine and Computational Structural Biology using Machine Learning and Mechanistic Modeling. Modeling the evolution of drug resistance.
Professor, Biological Sciences, Pitt
Elucidating the evolution of bacterial genomes, including their size, composition, variability and organization.
Professor Biomedical Engineering, CMU
To investigate biological systems with mechanical engineering approaches, which we enable by synthesizing novel technologies.
Assistant Professor, Biological Sciences, Pitt
My research addresses how gene expression programs change, leading to changes to cellular identity.
Associate Professor, Computational Biology, Pitt
We use single cell experiments and mathematical models to understand how single cells process information to make cell fate decisions in inflammatory disease and cancer.
Assistant Professor, Computational Biology, Pitt
Using coarse-grained models and statistical physics techniques to elucidate the underlying physical rules that are applied to the elements of living systems.
Professor, Computer Science, Pitt
Big data, user-centric data management, scientific data management, data stream management systems and data-intensive computing.
Assistant Professor, Pathology, Pitt
Our lab is interested in bioinformatics and biostatistics analysis on high-throughput genomic data, such as multi-omics Microarray and sequencing data.
Assistant Professor, Computational & Systems Biology, Pitt
Developing embryos must orchestrate the fates and movements of their cells with precision. However, precise control is no easy feat; genetic mutations, unexpected environmental perturbations and noisy signaling all threaten to scramble communication. Despite these challenges, development is remarkably robust. How do developing systems ensure precise pattern formation? How are mistakes corrected when they occur? Can we learn to engineer synthetic systems to have the reliability of developing embryos? Answers to these questions must span multiple scales, from signaling responses in individual cells to collective cell movement and morphogenesis. Our lab will tackle these questions with a combination of optogenetic manipulation, quantitative microscopy, computational modeling and classical embryology. Over the long run, we hope to learn the mechanistic principles that enable embryos to avoid and correct errors in development.
Professor, Biomedical Informatics, Pitt
Computational methods to identify signaling pathways underlying biological processes and diseases as well as statistical methods for acquiring knowledge from biomedical literature.
Assistant Professor, Computational Biology, CMU
Starting June 1, 2022
Jose's group develops the next generation of computational approaches to accelerate biomedical knowledge discovery through automated and autonomous science.
Professor of Medicine, Immunology and Dermatology Co-Leader, Melanoma Program, University of Pittsburgh Cancer Institute
Research Interests Mechanisms of tumor-induced T cell dysfunction Targeting Inhibitory pathways to reverse tumor-induced T cell dysfunction in cancer patients Cancer vaccines and immunotherapy of cancer
Ray and Stephanie Lane Professor of Computational Biology, CBD, CMU
Developing novel algorithms to study genome structure and function, chromatin and nuclear genome organization, and gene regulation in mammalian genomes as well as in cancer.
My research is focused on algorithm development and improvement in Bioinformatics such as genome assembly, RNA transcript assembly, sequence alignment, biological data storage, search and retrieval.
Assistant Professor, Biological Sciences, CBD, CMU
Understanding the genetic causes of variation in gene expression.
Associate Professor
Synthetic Biology and genetic circuit engineering, Programming multicellular systems and organoids via integration of systems and synthetic biology, Synthetic living machines, Morphogenetic engineering using human stem cells, Study and recreate multicellular evolution, computation, recording and their emergent behaviors.
Assistant Professor, Electrical and Computer Engineering, Bioengineering, Pitt
Biological design automation and systems and synthetic biology.
Professor, Machine Learning, CS, CMU
Machine learning to understand how the human brain uses neural activity to represent information, and statistical learning algorithms for natural language processing.
Assistant Professor, Computational Biology, CMU
Dr. Mohimani’s research focuses on the development of computational metabolomics and metagenomics methods for antibiotic discovery and microbiome analysis.
Professor of Computational Biology Emeritus, CMU
Cell and computational biology. Experimental and computational methods to learn and represent how proteins are organized within eukaryotic cells.
Assistant Professor
Our research focuses on how cells control protein localization in response to nutritional and environmental stressors. We are interested in gaining a deep mechanistic understanding of how the ‘decisions’ are made to selectively relocalize membrane proteins via vesicle-mediated trafficking in response to cellular signaling cues. We use a wealth of biochemical, genetic and cell biological approaches, including high content and systems level studies, in our work. Our research focuses on how cells control protein localization in response to nutritional and environmental stressors. We are interested in gaining a deep mechanistic understanding of how the ‘decisions’ are made to selectively relocalize membrane proteins via vesicle-mediated trafficking in response to cellular signaling cues. We use a wealth of biochemical, genetic and cell biological approaches, including high content and systems level studies, in our work.
Assistant Professor, Department of Biomedical Informatics, Pitt
My research focuses on developing data-driven computational approaches to understand disease mechanisms in order to assist in the development of personalizing anticancer treatments.
Assistant Professor, Human Genetics, Pitt
Investigates large-scale behavior of molecular dynamics in human diseases using bioinformatics, identifying molecular mechanisms of human diseases across diverse types of genetic and epigenetic data through big data analysis and machine learning algorithms.
Assistant Professor, Computational Biology, CMU
The neurogenomics laboratory studies how genome sequence differences influence behavior and neurological disorder predisposition.
Assistant Professor Director, High-Definition Fiber Tractography Lab
Diffusion MRI, tractography, network analysis, medical image analysis, pathology informatics.
Professor, Business, CS, CMU
Models, methods and applications of discrete optimization.
Assistant Professor, Biological Sciences, Pitt
We study the evolution of gene regulatory networks that control differences in morphology.
Professor, Statistics, Computational Biology, CMU
The use of statistical tools to understand the workings of the human genome and the nature of inherited diseases.
Professor & Head Machine Learning, Professor LTI, CS, CBD, CMU
The long term vision of our DELPHI research group is to make epidemiological forecasting as universally accepted and useful as weather forecasting is today.
Professor, Mathematics, Pitt
Modeling and analysis of neuronal network dynamics, especially respiratory, locomotor and pathological rhythms; modeling acute inflammation, including in traumatic brain injury; multiple time scale dynamics and parameter estimation for biological models.
Professor, Biological Sciences, CMU
My research is directed at understanding inter-molecular interactions in biological systems.
Professor, Disruptive Health Tech Inst., CMU
For the last 20 years, the Russell laboratory has been discovering what can be achieved by exploiting the rich interface of chemistry, biology and materials.
Associate Professor, Physics & Astronomy, Pitt
Our research aims to understand mechanisms of collective behavior and variability in bacterial cultures and their effect on responses to changing environments.
Professor, Computer Science, ML, CBD, CMU
Steering evolution and biological adaptation using computational game theory and opponent exploitation techniques; generating multi-step treatment plans; optimization, game theory, artificial intelligence, and market design.
Professor of Obstetrics, Gynecology, Reproductive Sciences & Cell Biology & of Bioengineering, Pitt
The molecular biology of cell function in gametes, embryos, stem cells, maternal/fetal efficacy of assisted reproduction technologies, the origins of developmental diseases, and…
Professor & Department Head Computational Biology, Professor Biological Sciences, CMU
Computational genomics, population genetics and phylogenetics, cancer heterogeneity and progression, computational biophysics, simulation and model inference of complex reaction networks.
Assistant Professor, Chemical/Petroleum Engineering, Pitt
COMPUTATIONALLY DRIVEN DISCOVERY IN HEALTH Biological information – from molecular events to personal genomics – has exploded. Our group aims to develop computational approaches to exploit large-scale data to promote disease treatment discovery and optimization.
Associate Professor
We study soft tissue architecture and biomechanics. We use computational and experimental tools to figure out natural strategies to make tissues robust and last a lifetime. We do this primarily by studying the eye.
Director, Center for Systems Immunology, Professor, Immunology, Pitt
The analysis of transcription factors and gene regulatory networks that regulate the development and functioning of innate and adaptive cells of the immune system.
Associate Professor, Mathematics, Pitt
My research is in the area of mathematical biology. We construct mathematical models of biological systems within the framework of continuum mechanics and stochastic dynamic systems.
Professor, Anesthesiology, Pitt
We are interested in the action of low-affinity drugs, such as general anesthetics and alcohols, on the neurotransmitter-gated receptor channels.
Director, Drug Discovery Inst., Professor, Computational & Systems Biology, Pitt
I am focusing my efforts in Quantitative Systems Pharmacology in order to change the paradigm in drug discovery and development.
Assistant Professor, Department of Biomedical Informatics, Pitt
Developing causal discovery methods in the presence of latent variables, methods for integrative analysis of multiple experiments, modelling and application of causal discovery on neural and biological data.
Professor, Department of Biostatistics, Pitt
We develop rigorous, timely and useful statistical and computational methodologies to understand disease mechanisms and improve disease diagnosis and treatment.
Assistant Professor, Department of Computational and Systems Biology Pitt
We study cancer systems biology of tumor microenvironments at multiple scales by integrating high-dimensional microscopy, imaging and data science, and systems and bioinformatics approaches.
Associate Professor, Biomedical Informatics, Pitt
Application of AI, machine learning, data mining of biomedical data, and Bayesian methods to problems in clinical medicine and bioinformatics with focus on patient-specific predictive modeling.
Professor, Surgery, Immunology, Bioengineering, Computational Biology, Clinical & Translational Science, and Communication Science & Disorders, Pitt
Our group’s research focuses on studying mechanisms of inflammation and gaining a systems-level perspective into this central physiological and pathological process.
Associate Professor, Pathology & Biomedical Informatics, Pitt
Apply integrative bioinformatics, cancer genetics, molecular cancer biology, and translational studies to identify driving genetic aberrations and appropriate cancer targets on the basis of deep sequencing and genomic profiling datasets.
Professor, Biomedical Engineering, CMU
Mechanics represent a key aspect of live cells. Our lab seeks a cellular-level understanding of the mechanisms of actuating and sensing mechanical events.
Professor, Statistics, ML, CMU
We are group of faculty and students in Statistics and Machine Learning broadly interested in theoretical work at the intersection of these two disciplines.
Assistant Professor, Machine Learning Dept & Neuroscience Institute, CMU
Her research is focused on computational modeling of the brain representation of language and other high-level tasks. She uses machine learning and neuroimaging -- fMRI and MEG -- to study how the brain represents information during complex naturalistic tasks. Her research is at the interface between natural language processing, machine learning and cognitive neuroscience.
Assistant Professor, Biomedical Informatics, Pitt
Developing new strategies for treating pathogens in the clinic, ultimately turning the tide against increasing antibiotic resistance.
Senior Systems Scientist, Computational Biology, CMU
My research uses integrative approaches to study complex human diseases by combining biology, computational and statistical learning, bioinformatics, and genomics.
Assistant Professor, Radiology, Biomedical Informatics, and Bioengineering, Pitt
Current research interests center on computational breast imaging and clinical studies for investigating quantitative imaging-derived biomarkers, models, and systems for breast cancer screening, risk assessment, diagnosis, prognosis, and treatment, towards improving individualized clinical decision-making and precision medicine.
Associate Dean for Research Innovation at The School of Pharmacy, Professor, Pharmaceutical Sciences/Drug Discovery Institute, Pitt
Dr. Xie’s research group designs and discovers GPCRs chemical genomics-based drugs for osteoporosis, multiple myeloma and breast cancer research.
Professor, Machine Learning, LTI, CS, CMU
Currently on leave of absence
We develop machine learning, statistical methodology, and computational systems for solving problems of learning, reasoning, and decision-making in artificial, biological, and social systems.
Associate Professor, Computational Biology, Pitt
The lab currently focuses on Epithelial-to-Mesenchymal Transition (EMT), characterized by loss of cell-cell adhesion and increased cell motility.
Assistant Professor, Computational Biology, CMU
We develop computational methods for modelling cell organization derived from electron cryotomography 3D images.
Professor, Anesthesiology Pharmacology & Chemical Biology, Physics & Astronomy, and Structural Biology, Pitt
High-Resolution Channel Protein Structure and Function; Molecular Mechanisms of General Anesthesia; MRI of Brain Protection after Cardiac Arrest and Resuscitation.
Associate Professor, Pharmaceutical Sciences,Pitt
The Yang lab focuses on computational and functional studies to identify mechanisms of cancer drug resistance, and to develop approaches/markers for personalized cancer medicine.
Associate Professor
The Zhang lab develops methods for automated causal discovery from various kinds of data, investigates learning problems including transfer learning, concept learning, and deep learning from a causal view, and studies philosophical foundations of causation and various machine learning tasks. On the application side, we are interested in neuroscience, computer vision, computational finance, and climate analysis.
Assistant Professor, Department of Medicine, Division of Endocrinology and Metabolism, Pitt
12h-clock, Hepatic Metabolic Homeostasis, Aging-associated Diseases