CPCB Faculty

Pitt, Computational Biology (Chair)
Program students ; Executive Committee
Biomolecular systems dynamics, multiscale modeling and simulations, computer-aided drug design, molecular and systems pharmacology, bridging sequence evolution, structure and function.
Ivet Bahar

CMU, Comp Bio and ML
Program students; Program Director, Executive and Curriculum Committees
Our group develops computational methods for understanding the interactions, dynamics and conservation of complex biological systems.
Ziv Bar-Joseph

Pitt, Computational Biology
Program students; Admissions Committee
We develop new computational methods to model biological processes and mine high-dimensional, multi-modal biomedical data.
Takis Benos

Pitt, Computational Biology
Executive Committee
Dr. Berg’s research focuses the relationships between the structures and functions of biological molecules.
Jeremy Berg

CMU, Bio. Sci. and Chemistry
Our work is focused on developing tools that couple the best of the synthetic dyes with the advantages of genetic targeting…
Marcel Bruchez

Pitt, Computational Biology
Program students; Executive & Admissions Committees
We develop new technologies to predict and model protein structures, their physical interactions, and substrates.
Carlos Camacho

Executive Committee
Machine Learning in Computational Proteomics; Active and Proactive Machine Learning; Transfer and Multitask Learning; Low-Resource Language Analysis; ML & LT for On-Line Education.
Jaime Carbonell

Pitt, Comp. Bio.
Admissions Committee
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.

Pitt, Pediatrics
Statistical and computational methods for high-throughput genetic/genomic and the genetic study of complex diseases, including age-related macular degeneration (AMD), childhood asthma, and chronic obstructive pulmonary disease (COPD).
Wei Chen

Pitt, Comp. Biology
We investigate the molecular and cellular origins of human epithelial malignancies through computational approaches.
Chakra Chennubhotla

Pitt, Computational Biology
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.
Maria Chikina

Pitt, Chemistry
Research in the Chong lab involves the development and application of molecular simulation approaches to model a variety of biophysical processes.
Lillian Chong

Pitt, Computer Science
Database Systems, Mobile and Pervasive Data Management, Distributed Computing, Operating Systems, Real-Time Systems.
Panos Chrysanthis
Pitt, Computational Biology
Program students; Program Assoc. Director, Seminar Series Committee
Our research focuses on the process of adaptive evolution in response to natural and sexual selection, and on co-evolutionary patterns within gene networks.
Nathan Clark

Pitt, Chemistry
Quantum Dynamics Theory, with Application to Condensed Phase Systems; Colloid Science: Structural and Dynamics of Charged Polystyrene Sphere Suspensions; Design of Dielectric Waveguides.
Rob Coalson

CMU, Machine Learning and LTI
Information integration and machine learning, particularly information extraction, text categorization and learning from large datasets.
William Cohen

CMU, Computational Biology
Advising Committee

Pitt, Biomedical Informatics
Application of decision theory, probability theory, Bayesian statistics, and artificial intelligence to biomedical informatics research problems.
Gregory Cooper

Pitt, Microbio & Mol. Genetics
New Faculty
We study evolution-in-action in the laboratory, in infections, and in cancers using genomics to identify and ultimately predict adaptations.
Vaughn Cooper

CMU, Chem. & Biomedical Engineering
Using rheological, biophysical and optical techniques to understand the structure and organization of the cell nucleus.
Kris Dahl

Pitt, Bioengineering
Reverse Engineering Morphogenesis – From Cell Motility & ECM to Tissue Mechanics.
Lance Davidson

CMU, Biological Sciences, CSD
Computational molecular biology and computational genomics; especially, the evolution of genomic organization and function.
Dannie Durand

Pitt, Biological Sciences
Develop broadly applicable, innovative computer-aided drug design (CADD) techniques and apply those techniques to further infectious-disease, neurological, and cancer drug discovery.
Dannie Durand

CMU, Statistics, MLD, BIO, CNBC
The statistical problems associated with Functional Magnetic Resonance Imaging (fMRI)
William Eddy

Pitt, Mathematics
Executive Committee
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.
Bard Ermentrout

Pitt, Computational Biology
Program students; Program Director, Executive Committee
Developing mathematical models of biological regulatory processes that integrate specific knowledge about protein-protein interactions.
James Faeder

Data Mining for graphs and streams. Fractals, self-similarity and power laws. Indexing and data mining for video, biological and medical databases.
Christos Faloutsos

Pitt, Public Health
Statistical methods for complex family-based datasets. Detecting identity-by-descent and testing relationships using dense (sequence or chip) data.

Pitt, Biomed. Inform.
Pattern mining whole-genome and whole-proteome sequences, with application of suffix array data structures for preprocessing genome sequences.

NYU, Dept. of Biology
Evolutionary genomics of infectious agents; neglected tropical diseases; microbiome and virus metagenomic studies.

Pitt, Biomed. Inform.
The design and development of computational methods for solving clinically relevant biological problems.

CMU, Machine Learning, RI
Multi-agent planning, reinforcement learning, decision-theoretic planning, statistical models of difficult data (e.g. maps, video, text), computational learning and game theory.

Pitt, Structural Bio (Chair)
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.

Pitt, Ophthalmology (Chair)
We study eye development and disease. We’re particularly interested in the genomic and epigenomic regulation of retinal development and regeneration.

Pitt, Biology
Executive Committee
The molecular genetics of the mycobacteria and their mycobacteriophages.

Pitt, Computer Science
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.

CMU, Biological Sciences
Understanding the role of bacteria in both health and disease.

CMU, Bio Sci, Comp Bio
How genomes control cell fate decisions during embryonic development and also later regeneration.

Pitt, Biomedical Informatics
We apply artificial intelligence, machine learning, Bayesian, and other computational methods to problems in biology, medicine, and translational research.

Pitt, Chemistry
Theory and experimental studies of molecules and clusters, reaction at surfaces, electron and proton localization transfer in polyatomic molecules and waterclusters.

CMU, Computational Biology, MLD
Seminar Series Committee
Developing statistical machine learning techniques to address significant methodological problems in computational genomics.

CMU, Computational Biology
Program students; Program Assoc. Director, Admissions Committee
Designing graph and optimization algorithms to extract insight from biological data.

Pitt, Computational Biology
Past students; Curriculum Committee
We develop computational algorithms and full-scale systems to support rapid and inexpensive drug discovery and apply these methods to develop novel therapeutics.

Pitt, Developmental Biology
We model epigenomic marks during differentiation and development, and build methods to elucidate the role of transcriptional enhancer sequences in vertebrate left-right patterning.

CMU, ECE (Chair), Bio Eng
Providing signal representation tools to be used primarily in communication and biomedical systems.

CMU, Chemistry
Understanding the work of membrane proteins, such as receptors, signal transduction proteins, toxins and ion channels.

Pitt, Computer Science
Big data, user-centric data management, scientific data management, data stream management systems and data-intensive computing.

CMU, Comp Bio, Bio Sci
Program students; Curriculum Committee
Personalized Medicine and Computational Structural Biology using Machine Learning and Mechanistic Modeling. Modeling the evolution of drug resistance.

Pitt, Biology
Elucidating the evolution of bacterial genomes, including their size, composition, variability and organization.

CMU, Mech Eng, Bio, BME, CBD
To investigate biological systems with mechanical engineering approaches, which we enable by synthesizing novel technologies.

Pitt, Biological Sciences
My research addresses how gene expression programs change, leading to changes to cellular identity.

Pitt, Computational Biology
Program students; Admissions Committee
We use single cell experiments and mathematical models to understand how cells process information to make cell fate decisions.

Pitt, Computational Biology
Program students; Journal Club Committee
Using coarse-grained models and statistical physics techniques to elucidate the underlying physical rules that are applied to the elements of living systems.

CMU, Bio Sci, Comp Bio
The regulation of alternative pre-mRNA splicing, its contribution to cell function and development, and its disruption in disease.

Pitt, Biomedical Informatics
Computational methods to identify signaling pathways underlying biological processes and diseases as well as statistical methods for acquiring knowledge from biomedical literature.

CMU, Computational Biology
New Faculty, Admissions Committee
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.
Jian Ma web

CMU, BioSci, Comp Bio
Understanding the genetic causes of variation in gene expression.

CMU, Computer Science
Computational geometry, scientific computing, parallel algorithms and randomized algorithms.

Pitt, Bioengineering
Biological design automation and systems and synthetic biology.

CMU, Machine Learning, CBD
Machine learning to understand how the human brain uses neural activity to represent information, and statistical learning algorithms for natural language processing.

CMU, CBD (Chair), BIO, BME, ML
Program students, Executive Committee
Cell and computational biology. Experimental and computational methods to learn and represent how proteins are organized within eukaryotic cells.

Pitt, Pathology and Comp Bio
Curriculum Committee
My research uses system biology approaches to understand disease pathologies, and develop improved diagnostic and therapeutic approaches.
CMU, Computational Biology
New Faculty
The neurogenomics laboratory studies how genome sequence differences influence behavior and neurological disorder predispositio
CMU, Business, CSD
Models, methods and applications of discrete optimization.

Pitt, Biology
We study the evolution of gene regulatory networks that control differences in morphology.

CMU, Statistics, Comp Bio
The use of statistical tools to understand the workings of the human genome and the nature of inherited diseases.

Pitt, Biology
My research philosophy is to bring a physical, problem-ori­ented ap­proach to the acquisition and interpretation of biomolecular structural information.

The long term vision of our DELPHI research group is to make epidemiological forecasting as universally accepted and useful as weather forecasting is today.

Pitt, Mathematics
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.

CMU, Biological Sciences
My research is directed at understanding inter-molecular interactions in biological systems.

CMU, Disruptive Health Tech Inst.
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.

CMU, Chem Eng, Comp Bio
Curriculum Committee
We advance areas of optimization theory, algorithms, and software, and develop comprehensive solutions to problems involving biological, chemical, and engineering systems.

Pitt, Physics
Curriculum Committee
Our research aims to understand mechanisms of collective behavior and variability in bacterial cultures and their effect on responses to changing environments.

CMU, Computer Science, ML
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.

PGH Development Center
The molecular biology of cell function in gametes, embryos, stem cells, maternal/fetal efficacy of assisted reproduction technologies, the origins of developmental diseases, and…

CMU, Bio Sci & Comp Bio
Program students; Exec. & Student Advising Committees
Computational genomics, population genetics and phylogenetics, cancer heterogeneity and progression, computational biophysics, simulation and model inference of complex reaction networks.

Joel Stiles
Pittsburgh Supercomputing Center
In Memoriam

Pitt, Mathematics
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.

Pitt, Computational Biology
Program students; Student Advising Committee
We are interested in the action of low-affinity drugs, such as general anesthetics and alcohols, on the neurotransmitter-gated receptor channels.

Pitt, Drug Discovery Inst.
I am focusing my efforts in Quantitative Systems Pharmacology in order to change the paradigm in drug discovery and development.

Pitt, Biostatistics
We develop rigorous, timely and useful statistical and computational methodologies to understand disease mechanisms and improve disease diagnosis and treatment.

Dr. Urban’s research interests seek to understand the physiological mechanisms underlying functional and computational properties of brain neuronal networks.

Pitt, Biomed. Informatics
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.

Pitt, Surgery
Our group’s research focuses on studying mechanisms of inflammation and gaining a systems-level perspective into this central physiological and pathological process.

Pitt, Pathology
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.

CMU, Biomedical Engineering (Chair)
Executive Committee
Mechanics represent a key aspect of live cells. Our lab seeks a cellular-level understanding of the mechanisms of actuating and sensing mechanical events.

CMU, Statistics
We are group of faculty and students in Statistics and Machine Learning broadly interested in theoretical work at the intersection of these two disciplines.

CMU, Computational Biology
Admissions Committee
My research uses integrative approaches to study complex human diseases by combining biology, computational and statistical learning, bioinformatics, and genomics.

Pitt, Pharmacy
Dr. Xie’s research group designs and discovers GPCRs chemical genomics-based drugs for osteoporosis, multiple myeloma and breast cancer research.

CMU, Machine Learning
We develop machine learning, statistical methodology, and computational systems for solving problems of learning, reasoning, and decision-making in artificial, biological, and social systems.

Pitt, Computational Biology
Program students; Admissions Committee
The lab currently focuses on Epithelial-to-Mesenchymal Transition (EMT), characterized by loss of cell-cell adhesion and increased cell motility.

CMU, Computational Biology
We develop computational methods for modelling cell organization derived from electron cryotomography 3D images.

Pitt, Anesthesiology
High-Resolution Channel Protein Structure and Function; Molecular Mechanisms of General Anesthesia; MRI of Brain Protection after Cardiac Arrest and Resuscitation.

Pitt, Pharmacy
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.

CMU, Biomedical Engineering, CBD
My research interests are in computational cell biology, bioimage informatics, molecular cell mechanics, and fluorescence imaging.

CMU, Computer Science
Designing programming models, language implementation strategies, and tools to make it easier to create software. Security and privacy of medical data and modeling protein interactions.
Jean Yang