Core Faculty of the Training Program
The core faculty of the Biomedical Informatics Training Program includes faculty from the Department of Biomedical Indformatics, as well as faculty from other departments and schools within the University of Pittsburgh.
Ivet Bahar, MS, PhD, is a professor and the John K. Vries chair of the Department of Computational Biology. Bahar’s research expertise is in modeling and simulations of macromolecular dynamics, and developing new theories and computational tools for analyzing complex biological processes. She has extensive experience in analytical models and quantitative methods for determining the conformational dynamics of proteins and their complexes, as well as molecular dynamics (MD) simulations of biomolecules. She is the developer of the Gaussian Network Model (GNM) theory and software, which opened the way to a wealth of computational studies of protein dynamics and improved our understanding of the structural basis of biomolecular functional mechanisms. Bahar is part of the teaching faculty for Introduction to Computational Structural Biology (MSCBIO2030), a core course for the Joint CMU-Pitt PhD program in Computational Biology, and also cross-listed as a core course for the Molecular Biophysics Graduate Program.
Michael J. Becich, MD, PhD, is a professor of biomedical informatics, pathology and information sciences and telecommunications, and is the chair of the Department of Biomedical Informatics. Becich’s current research focuses on developing applications and databases to manage the analysis of expression data derived from high throughput genomics. This program focuses on creating data mining and data warehousing tools for data derived from DNA based microarrays, tissue microarrays, tissue bank information systems, clinical information systems and imaging repositories that currently exist in the Department of Pathology. His laboratories are well-funded with grants from the National Cancer Institute, National Center or Research Resources, and the National Institute for Diabetes, Digestive and Kidney Diseases as well as genomic/biotechnology company-sponsored research programs.
Panagiotis Benos, PhD, is an associate professor in the Department of Computational Biology. Benos’ main research areas include the study of the gene regulation with mathematical methods and computational techniques, and genome analysis with emphasis in the evolution of proteins and DNA regulatory regions. In particular, his laboratory focuses in the development of computational models for gene interactions, the identification of transcription factor binding sites, the study of the relation between protein sequence-structure-function, the study of biochemical and biophysical phenomena at the molecular level, and the analysis of heterogeneous data.
Brian E. Chapman, PhD, is an assistant professor of biomedical informatics, radiology, and bioengineering. Chapman’s primary research interest is the quantitative analysis of volumetric medical images. He is also involved with developing novel image acquisition techniques.
Wendy W. Chapman, PhD, is an assistant professor of biomedical informatics and intelligent systems, and she is an associate director of the Training Program. Chapman’s primary research interest is the application of natural language processing technology to textual clinical reports, with a current focus on classifying, extracting, and encoding clinical information that is useful for biosurveillance, including chief complaints, chest radiography reports, and emergency department reports.
Gregory F. Cooper, MD, PhD, is an associate professor of biomedical informatics, computational biology, computer science, information science, and intelligent systems. Cooper is the vice chair of the Department of Biomedical Informatics. He is the principal investigator of the NLM Training Program Grant. Cooper's general research interest is the application of decision theory, probability theory, and artificial intelligence to address medical informatics research questions. His primary research focus is causal modeling and discovery in medicine and biology. Other interests include data mining of medical databases, the application of Bayesian statistics in medicine, and computer-assisted information retrieval from electronic medical records.
Rebecca S. Crowley, MD, MSIS, is an assistant professor of biomedical informatics, intelligent systems, and pathology. Crowley, a graduate of the Training Program, is its current director. Her research interests include: development and evaluation of intelligent medical training systems (SlideTutor, ReportTutor), computational methods for medical knowledge representation and decision support, natural language processing and information extraction from medical free-text (caTIES), empirical studies of the development of visual diagnostic expertise, and the use of cognitive modeling and work process modeling to improve information systems.
Roger S. Day, ScD, is an associate professor of biomedical informatics. Day leads development of the Oncology Thinking Cap computer modeling facility, which uses stochastic models of tumor growth to help cancer researchers do thought experiments about cancer biology and treatment, and to help cancer educators develop their abilities to reason across the bridge from basic cancer science through implications for patients and clinical trials. New aspects of this work are integration with the Cancer Bioinformatics Grid (caBIG) and with knowledge acquisition tools. His work on breast cancer includes collaborations to shed light on contentious dosing issues in adjuvant breast cancer treatment through modeling of the population dynamics and genetic evolution of breast cancers, and through molecular studies of samples of individual cells from tumors. The long-range goal is to radically improve our ability to predict response of individual patients to a variety of cancer therapies and strategies. Day’s other areas of research include statistical model families (“weakest link” models; generalized additive effects models) that reflect the kinds of relationships that exist in the real world of biology and medicine.
Ellen G. Detlefsen, DLS, is an associate professor of library and information science in the School of Information Sciences (SIS). Detlefsen directs the health librarianship concentration at SIS. Her research interests are in information behavior and information dissemination, consumer informatics, and education for medical informatics. Detlefsen teaches a master’s level course for non-clinicians entitled “Applications in Medical Informatics” (LIS 2587), which incorporates face-to-face and online formats.
Barbara Epstein, MSLS, is director of the University’s Health Sciences Library System (HSLS). Epstein’s research interests include training for health sciences librarianship, information challenges in the decentralized health care enterprise, information seeking behavior of varied populations, and the impact of electronic information resources.
Vanathi Gopalakrishnan, PhD, is an assistant professor of biomedical informatics, intelligent systems and computational biology. Gopalakrishnan is interested in the development of intelligent computational aids for solving clinically relevant biological problems, such as biomarker discovery for neurodegenerative diseases from proteomic mass spectra, macromolecular crystallization, functional MRI data analysis and mapping of protein sequence-structure-function relationships. Her research encompasses the application of machine learning methods such as rule learning and Bayesian techniques, in addition to developing quantitative models of biological phenomena from first principles. Gopalakrishnan teaches a core course titled Introduction to Bioinformatics (BIOINF 2051) each fall term, oversees the Bioinformatics Journal Club, and each summer offers a directed study laboratory course (BIOINF 2053) in conjunction with educators from the Pittsburgh Supercomputing Center.
Milos Hauskrecht, PhD, is an associate professor of computer science. Hauskrecht regularly teaches graduate level artificial intelligence and machine learning courses at the University, as well as advanced Machine Learning and AI seminars. His primary research interests are in probabilistic modeling and the design of efficient optimization, inference and learning algorithms for such models. Hauskrecht applies the models and techniques to analysis of high-throughput proteomic and genomic datasets, data mining and discovery in clinical databases, and decision-making in patient management tasks.
William R. Hogan, MD, is an associate professor of biomedical informatics, senior data analyst of the Real-time Outbreak and Disease Surveillance (RODS) Laboratory, and director of Medical Vocabulary Services at the University of Pittsburgh Medical Center (UPMC). Hogan’s areas of expertise include ontology, medical vocabulary, knowledge representation, clinical decision support, public health surveillance, and standards for electronic data transmission and communication. His work at UPMC involves all aspects of harmonization of the meaning of data across two major electronic medical records and other systems. Hogan’s current research at the Department of Biomedical Informatics involves applying models of atmospheric diffusion to the problem of detecting disease patterns that are consistent with an airborne release of pathogens.
James Lyons-Weiler, PhD, is an adjunct assistant professor of biomedical informatics, and is director of the Bioinformatics Analysis Core at the University. Lyons-Weiler’s primary research interest is the development and evaluation of algorithms for the interpretive analysis of high-dimensional genomic, proteomic, genetic and clinical data centered on biomarker development for disease prediction modeling. His graduate students work on a range of analytical and methodological problems from integrative clinical study design via decision modeling to survivorship prediction modeling.
Claudia Mello-Thoms, MSEE, PhD, is a research assistant professor of biomedical informatics. Mello-Thoms’ research interests are in the areas of image perception and image interpretation, as well as visual search and modeling of the decision making process that radiologists undergo as they read a medical image.
Valerie Monaco, PhD, MHCI, is an assistant professor of biomedical informatics, and is faculty director of the University of Pittsburgh Cancer Institute and the UPMC Cancer Center Web sites. Monaco completed graduate training in the fields of psychology and human-computer interaction. Her research explores ways to enhance the delivery of health information to consumers. Monaco has focused primarily on two populations: patients considering participation in a cancer clinical trial, and low-literacy individuals searching for online health information.
Bambang Parmanto, PhD, is an associate professor of health information management at the School of Health and Rehabilitation Sciences. Parmanto’s primary research interests include data mining/warehousing, personal health record, Web transcoding, and telerehabilitation. He teaches two courses in the Training Program: Object-oriented and Web Programming (HRS-2422), and Database Systems in Healthcare (HRS-2423).
Mark S. Roberts, MD, MPP, is a professor of medicine, health policy and management, and industrial engineering. Roberts is chief of the Section of Decision Sciences and Clinical Systems Modeling in the Division of General Medicine. He also serves as the co-director of the master's program in Clinical Research and the new PhD program in Clinical and Translational Science. Roberts’ research interests include the development and application of clinically realistic mathematical models of disease to investigate and inform questions that cannot easily be examined by randomized controlled trials, such as the optimal timing of an intervention in a chronic disease. Roberts uses modeling techniques such as decision analysis, Monte Carlo Simulation, and discrete event simulation to create representations of disease processes and therapeutic interventions. In addition, he has substantial expertise in the conduct of cost-effectiveness analysis in health care, the use of clinical information systems in health care, and the measurement and inclusion of patient preferences in clinical decision making.
Gilan El Saadawi, MD, PhD, is an assistant professor of health and community systems and biomedical informatics at the School of Nursing. El Saadawi’s primary research interests are in human computer interaction and standardized markup languages to develop an improved process for converting existing text-based files into a standard document format.
Melissa I. Saul, MS, is an adjunct assistant professor of health information management at the School of Health and Rehabilitation Sciences, and she is director of the Clinical Research Informatics Service (CRIS) at the Department of Biomedical Informatics and the Clinical and Translational Science Institute (CTSI). Saul also serves as informatics director at the Center for Pharmacoinformatics and Outcomes Research in the School of Pharmacy. She is a founding member of the Medical ARchival Systems (MARS) development team. MARS is the University of Pittsburgh Medical Center’s data repository for clinical and financial data. In her current role, Saul provides consultation services to clinicians and informatics trainees for collecting and analyzing large datasets. Saul teaches the summer term course Concepts in Software Engineering for Health Care (BIOINF 2110). In collaboration with Gregory Cooper and others, Saul developed De-ID™, which is a de-identification software tool licensed by the University for use by academic and commercial entities. Her research interests include the use of large data sets for outcomes management and cost-effectiveness studies, and the development of software tools to assist in the retrieval of data from electronic medical record systems.
Titus K. L. Schleyer, DMD, PhD, is an associate professor of dental medicine and biomedical informatics, and is director of the Center for Dental Informatics at the School of Dental Medicine. Schleyer is also the University of Pittsburgh Biomedical Informatics Training Program’s co-director for dental informatics. His research interests include clinical dental informatics, computer-based oral health records, distributed information resources, and computer-supported collaborative work and educational software. Schleyer’s main research interest is focused on the development of a novel computing environment for clinical dentistry, which will include a three-dimensional dental record, a natural language processing interface, and an embedded context-aware computing infrastructure.
Heiko Spallek, DMD, PhD, is an assistant professor of dental medicine and biomedical informatics at the School of Dental Medicine. Spallek’s research is oriented towards the use of information technology in dental practice, research, and education—including the quality of online learning resources, adaptive hypermedia systems for dental education, clinical use of computers in dentistry, and the development of online research communities.
Nancy H. Tannery, MLS, is the associate director for information services at the Health Sciences Library System. Tannery’s research interests include training for health sciences librarianship, user education, and how users find and use information.
Thankam P. Thyvalikakath, BDS, MDS, MS, is an assistant professor of dental medicine and biomedical informatics at the School of Dental Medicine. Thyvalikakath’s research interests include developing a novel human-computer interface for computer-based patient records in dentistry, implementing and evaluating informatics-based interventions for patient care outcomes, and developing a standard information model for electronic dental records.
Fu-Chiang (Rich) Tsui, PhD, is a research assistant professor of biomedical informatics and intelligent systems, and is associate director of the Real-time Outbreak and Disease Surveillance (RODS) Laboratory. Tsui’s research interests include time series analysis, neural networks, digital signal processing, wavelet transforms, and database management as they apply to electronic medical records, medical decision support systems, notification systems, Web design and real-time analysis of clinical signals. He mentors students in master’s and PhD programs, and is also a guest lecturer in the courses Knowledge Representation and Modeling, and Real-time Outbreak and Disease Surveillance.
Shyam Visweswaran, MD, PhD, is an assistant professor of biomedical informatics. Visweswaran’s research interests include the application of artificial intelligence and machine learning to problems in clinical medicine and bioinformatics with a specific focus on data mining of biomedical data, patient-specific predictive modeling, medical anomaly detection, and decision support systems.
Michael M. Wagner, MD, PhD, is an associate professor of biomedical informatics and intelligent systems, and is director of the Real-time Outbreak and Disease Surveillance (RODS) Laboratory. Wagner has developed reminder and alerting systems that are based on probabilistic and decision-theoretic formalisms. His current research in biosurveillance involves collaborations with researchers at Carnegie Mellon University, and many health departments, to develop and evaluate algorithms, decision models, and fielded production systems for biosurveillance. Wagner’s areas of expertise include knowledge representation, intelligent systems, and clinical decision support.
Garrick Wallstrom, PhD, is an assistant professor of biomedical informatics, and is senior statistician at the Real-time Outbreak and Disease Surveillance (RODS) Laboratory. In collaboration with other researchers, Wallstrom has developed a desktop application for evaluating biosurveillance systems and a software package for performing Bayesian nonparametric regression. His research involves the development of computational statistical methods for biomedical applications. Wallstrom’s current research in the field of biosurveillance is focused on the development of outbreak detection algorithms and the evaluation of biosurveillance systems. His areas of expertise include statistical computation, biosurveillance system evaluation, and Bayesian methodology.