Core Faculty of the Training Program
The core faculty of the Biomedical Informatics Training Program includes faculty from the Department of Biomedical Informatics, 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.
Christa E. Bartos, RN, MSIS, PhD, is an assistant professor of informatics. Dr. Bartos’ research involves socio-technical implications of the implementation of computerized provider order entry and electronic health records, specifically changes in personal power and clinicians’ resistance. Additional interests include evaluation of clinical systems and decision support.
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 for Research Resources, and the National Institute for Diabetes, Digestive and Kidney Diseases as well as genomic/biotechnology company-sponsored research programs.
Tanja Bekhuis, PhD, MS, MLIS, is an Assistant Professor in the Department of Biomedical Informatics. Her research belongs to the emerging field of clinical and translational research informatics. She is particularly interested in developing methods to support comparative effectiveness researchers, including systematic reviewers who synthesize medical evidence, and biomedical librarians and trials search coordinators who develop complex search strategies. She also studies the language scientists use to describe their own research in published literature. Her work involves natural language processing and machine learning.
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.
Richard Boyce, PhD, is an assistant professor of biomedical informatics. Dr. Boyce is interested in knowledge-based approaches to drug-drug interaction, computational methods, and belief maintenance systems to biomedical knowledge-representation.
Gregory F. Cooper, MD, PhD, is a professor of biomedical informatics, computational biology, computer science, information science, and intelligent systems. Cooper is the vice chair of the Department of Biomedical Informatics. 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, MS, 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.
Gerald Douglas, PhD, is an assistant professor of biomedical informatics. His research focuses on applying the principles of medical informatics to improve healthcare in low-resource settings, both within the United States as well as internationally. He has particular interest in user-interface design and user experience. His research builds on techniques developed through 10 years of experience building point-of-care electronic medical record systems in Malawi. These techniques are captured in the curriculum of the graduate-level Principles of Global Health Informatics course, and Global Health Informatics Summer Internship in Malawi, created and taught by Dr. Douglas.
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 healthcare enterprise, information seeking behavior of varied populations, and the impact of electronic information resources.
Madhavi Ganapathiraju, PhD, is an Assistant Professor in the Department of Biomedical Informatics, University of Pittsburgh. She holds an MEng degree in Electrical and Communications Engineering from Indian Institute of Science and PhD in Language and Information Technologies from School of Computer Science at Carnegie Mellon University. Her PhD thesis focus was on the application of signal processing and language processing methods to the study of protein and proteome sequences, which led to the development of a high accuracy algorithm for transmembrane helix prediction. Her current research focus is in the area of computational molecular and systems biology, translational bioinformatics and biomedical text mining, using signal processing and machine learning.
Vanathi Gopalakrishnan, PhD, is an associate 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.
Steven M. Handler, MD, PhD, CMD, is an assistant professor with a primary appointment in the Department of Biomedical Informatics and secondary appointments in Geriatric Medicine, Clinical and Translational Research, the Geriatric Research Education and Clinical Center (GRECC) at the VA Pittsburgh Healthcare System. Dr. Handler’s research interests include the application of clinical decision support systems to improve medication safety primarily in the nursing home setting.
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.
Harry Hochheiser, PhD, is an assistant professor of biomedical informatics, His research interests are focused on the design of usable systems for use in clinical and research settings. He is particularly interested in using user-centered design techniques to inform the design of highly-interactive information visualization systems for the interpretation of complex data sets in domains such as bioinformatics and electronic health records.
Xia Jiang, PhD, is an assistant professor in the Department of Biomedical Informatics. Dr. Jiang has over 13 years of teaching and research experience in Bayesian Network modeling, machine learning, and algorithm design. One of Dr. Jiang's specific areas of interests is developing advanced computational methods for high-dimensional data analysis. Dr. Jiang is also very interested in translational informatics, in particular, cancer bioinformatics. She will devote her efforts in developing advanced informatics tools that assist the translation of the findings in basic scientific research efficiently and effectively into patient medical care, atrendin research so called “basepairstobedside”. Dr. Jiang’s research collaborators include mathematicians, computer scientists, statisticians, physicians, pathologists, biologists, geneticist, and peer informaticians from Pitt, CMU, NU, and UCSD etc.
Xinghua Lu, MD, PhD, is an associate professor of biomedical informatics. His research interests include computational methods for identifying signaling pathways underlying biological processes and diseases, statistical methods for acquiring knowledge from biomedical literature, translational bioinformatics and systems/computational biology, natural language processing and text mining.
Ashok Panigrahy, MD, is an associate professor in the Department of Radiology at the University of Pittsburgh, and the Radiologist-In-Chief, Department of Pediatric Radiology, Children’s Hospital of Pittsburgh. His research interest are neonatal brain injury: evaluation with advanced MR techniques; advanced MR imagining of pediatric brain tumors; and fetal MR imaging.
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 codirector 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 healthcare, the use of clinical information systems in healthcare, and the measurement and inclusion of patient preferences in clinical decision making.
Melissa I. Saul, MS, is an adjunct assistant professor of health information management at the School of Health and Rehabilitation Sciences and 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.
Ervin Sejdić, PhD, is an assistant professor in Department of Electrical and Computer Engineering (Swanson School of Engineering), Department of Bioengineering (Swanson School of Engineering), Department of Biomedical Informatics (School of Medicine) and the Intelligent Systems Program (Kenneth P. Dietrich School of Arts and Sciences). He is also the director of the Innovative Medical Engineering Developments (iMED) Lab at the University of Pittsburgh and the associate director of the RFID Center of Excellence at the University of Pittsburgh. Dr. Sejdić and his lab aim to develop dynamical biomarkers indicative of age- and disease-related changes and their contributions to functional decline under normal and pathological conditions by fostering innovation in computational approaches and instrumentation that can be translated to bedside care. Our research areas include, but not limited to, advanced information systems in medicine, bioinformatics, anticipatory medical devices, rehabilitation engineering, assistive technologies, biomedical and theoretical signal processing, computational biomarkers, brain-computer interfaces, human-computer interfaces.
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.
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.
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