Tutorial Workshops Faculty

We are pleased to announce the tutorial workshop faculty members for the 2019 OHDSI Symposium, listed in alphabetical order:

Hamed Abedtash, PharmD, PhD
Research Scientist – Real World Evidence
Global Patient Outcome Real World Evidence (GPORWE), Eli Lilly & Company

Dr. Abedtash is Informatics Research Scientist at Eli Lilly. He is a Doctor of Pharmacy, and holds PhD in biomedical and health informatics from Indiana University. Dr. Abedtash’s research interests are in the areas of semantic network, common data model (CDM), interoperability of CDMs, medical data analytics, visualization of health outcome data, and modeling big medical data for capturing new insights about patient outcome. He is currently involved in several OHDSI workgroups including Common Data Model and Pharmacovigilance Evidence Investigation.

Clair Blacketer, MPH, PMP
Manager, Epidemiology Analytics
Janssen Research & Development

Clair Blacketer is a Manager in the Epidemiology Analytics group within Epidemiology at Janssen Research & Development, a Johnson & Johnson company. She began her career at a regional health system in her home state of Virginia focused on health outcomes research, specifically in patients with sepsis. She then moved on to studying Medicare health care economics at a large payer and while there she was instrumental in implementing a novel way to track dual-enrolled Medicare retirees. Clair joined Janssen in 2015 where her main area of focus has been observational data management. This includes managing multiple ETL conversions to the OMOP Common Data Model as well as serving as project manager for the Common Data Model working group. She received her Bachelor of Science in Biology from James Madison University and her Master in Public Health from Eastern Virginia Medical School. Clair is also a certified Project Management Professional.

Eun Kyoung Ahn

Dmitry Dymshyts, MD
Lead Data Analyst
Odysseus Data Services

Dmitry Dymshyts, MD is a psychiatrist by training. He worked as a psychiatrist at his own private therapeutic practice and taught students in the University. He started contributing to OHDSI making manual mappings between ICDs and SNOMED in 2013. Since 2015 he as been an active collaborator and leading the team making OHDSI vocabularies architecture. Since 2016 he has been lead of the OHDSI vocabulary team.

Vojtech Huser, MD, PhD
Staff Scientist, Lister Hill National Center for Biomedical Communications, National Library of Medicine
National Institutes of Health

Dr. Huser was born in the Czech Republic. He received medical doctor degree (MD) from Palacky University (Olomouc, Czech Republic, EU) and PhD degree in Biomedical informatics from University of Utah (Salt Lake City, Utah, USA). He is currently affiliated with National Institutes of Health (NIH), Laboratory for Informatics Development at the NIH Clinical Center. His research interests are: clinical informatics, knowledge representation, clinical research informatics, data repositories and data analysis, workflow technology, executable clinical guidelines, medical decision support systems and quality improvement in healthcare. As an informatician, Dr. Huser worked with numerous informatics systems at Intermountain Healthcare in Utah, Marshfield Clinic in Wisconsin, and NIH in Maryland (intramural campus). He is a former Fulbright scholar (his PhD degree) and recipient of the Young Investigator Award from HMO Research Network. He is a member of American Medical Informatics Association.

Christopher Knoll

Christopher Knoll
Manager, Epidemiology Analytics
Janssen Research and Development

Christopher Knoll is a Manger of Epidemiology Analytics at Janssen Research and Development where he architects software solutions and data platforms for the analysis and application of observational data sources. Chris’ areas of expertise include web application development, service oriented architecture, data visualization, and software engineering. He is currently a collaborator of the open-source software working group in OHDSI. Contributions include: lead designer of Circe (cohort definitions), Achilles/AchillesWeb (database characterization), major contributor to Atlas (standardized platform for OHDSI analytics), lead developer of Atlas D3 visualization library, served as faculty for several OHDSI symposium classes and presentations, and mentor to many contributors in the OHDSI open source community.

Prior to joining Janssen Research and Development, Chris worked with several financial institutions assisting them in modeling credit risk applications for lenders, as well as leading large software development teams. Other industries Chris has experience in are finance, e-commerce, and consumer electronics. Chris received his undergraduate degrees in Computer Science and Philosophy at Rutgers University.


Cong Liu
Associate Research Scientist
Columbia University Department of Biomedical Informatics

I have a broad background in biomedical science, with specific training and expertise in bioinformatics and biomedical informatics. I am primarily trained in the methods of bioinformatics, statistical learning, machine learning, and their use for biomedical discovery using large-scale genomic data. I used these skills to develop a novel knowledge-guided feature selection method in machine learning related tasks for high-dimensional omics data. In addition to my training in bioinformatics, I am recently trained in clinical informatics, phenotyping, natural language processing, and observational data analysis. I have developed a novel system called Doc2Hpo for interactive and efficient phenotype concept curation from clinical text with automated concept normalization using the Human Phenotype Ontology (HPO). I also developed a user-center clinical trial searching application compatible with OHDSI to reduce the information overload.

Mary Boland

Ajit Londhe, MPH
Manager, Epidemiology Analytics
Janssen Research and Development

Ajit Londhe is a Manager of Epidemiology Analytics at Janssen Research and Development, a Johnson & Johnson company. His projects typically deal with comparative effectiveness and clinical characterization studies. Ajit leads the Metadata and Annotations Working Group, and has contributed to the development of the Achilles and CdmAtlasCutover R packages. He also has been leading efforts to convert multiple Optum claims data sets into the OMOP Common Data Model, gaining efficiencies in the CDM build process, and improving data set characterization. Ajit received his Bachelor of Science in Computer Science and Engineering from Pennsylvania State University and his Master’s in Public Health (Epidemiology) from Emory University’s Rollins School of Public Health. He previously worked in various roles in Johnson & Johnson’s IT department prior to joining the Epidemiology department.

Peter Rijnbeek

Melanie Philofsky, RN, MS
Senior Business & Data Analyst
Odysseus Data Services

Melanie Philofsky is a Senior Business & Data Analyst with Odysseus Data Services, Inc. She is responsible for the harmonization of various healthcare data sources into the OMOP Common Data Model to support research endeavors. Her areas of expertise include clinical informatics, data analysis, data quality, ETL conversions, EHR data, the OMOP CDM and data modeling of new domains. Prior to earning her MS in Healthcare Informatics, she was an ICU RN. She knows and understands the clinical workflow and UI of an EHR system to the backend where data is pulled for transformation to the OMOP CDM.

Melanie is the EHR working group lead and a collaborator in the CDM/Vocabulary working group, Symposium Planning Committee and Themis.

Christian Reich

Christian Reich, MD, PhD
VP Real World Analytics Solutions

At IQVIA, Christian is responsible for building open OHDSI study networks for RWE generation as a service, including the building of enabling technology solutions. Christian is also Principal Investigator of OHDSI, and also served as Program Manager and Principal Investigator at OMOP. He responsible for the design and construction of the OMOP Standardized Vocabularies and leads the Common Data Model Working Group.

Christian has more than 15 years of experience in life science research and medicine. He was a practicing physician in Berlin and Ulm, Germany before moving to the European Bioinformatics Institute to work on the Human Genome Project. He then joined the biotech industry in 1998, where he worked in various positions on typical challenges in drug research and development, such as gene sequence and expression analysis, clinical trial design and analysis, systems biology, and outcome research, applying computational methods to large scale biological data. He received his bachelor’s degree in preclinical training from Humboldt University in Berlin and holds his M.D. and doctorate from the Medical University of Lübeck, Germany where he focused his research on T-cell activation and regulation.

Jenna RepsPhD
Senior Epidemiology Informaticist
Janssen research and Development

Jenna Reps is a Senior Epidemiology Informaticist at Janssen research and Development where she is focusing on developing novel solutions to personalise risk prediction. Jenna’s areas of expertise include applying machine learning and data mining techniques to develop solutions for various healthcare problems. She is currently working within the patient level prediction OHDSI workgroup with the aim of developing open source and user friendly software for developing risk models using data sets in the OMOP Common Data Model format.

Prior to joining Janssen Research and Development, Jenna was a Senior Research Fellow at the University of Nottingham where she developed supervised learning techniques to signal adverse drug reactions using UK primary care data and acted as a data consultant to other researchers within the University. Jenna received her BSc in Mathematics and MSc in Mathematical Biology at the University of Bath and her PhD in Computer Science at the University of Nottingham.

Peter Rijnbeek, PhD
Associate Professor Health Data Science
Erasmus University Medical Center

Peter Rijnbeek, PhD, obtained his MSc (1996) in Electrical Engineering at the Technical University Delft. His PhD thesis, received from the Erasmus University Rotterdam, was on the development of a computer program to automatically interpret pediatric electrocardiograms. He is Assistant Professor at the Erasmus University Medical Center in Rotterdam where he is leading the health data science group at the Department of Medical Informatics (www.healthdatascience.nl).

His research interests include computerized analysis of the electrocardiogram, pattern recognition, machine learning and predictive modeling using clinical data. He had a leading role in several large European projects related to secondary use of health care database. He is co-leading the European Health Data and Evidence Network project funded by the European Commission that aims to standardize a large amount of databases to the OMOP-CDM in the upcoming 5 years and create a high quality European data network. Peter is the coordinator of the European OHDSI chapter that organizes a yearly symposium (www.ohdsi-europe.org) that supports the adoption of the OMOP-CDM.

In OHDSI he is co-leading the Patient-Level Prediction working group together with Jenna Reps that built a framework on top of the OMOP-CDM for large-scale development and validation of prediction models across the world (www.github.com/ohdsi/PatientLevelPrediction).

Patrick Ryan, PhD
Sr. Director and Head, Epidemiology Analytics
Janssen Research and Development
Assistant Professor, Adjunct; Department of Biomedical Informatics
Columbia University Medical Center

Patrick Ryan, PhD is Senior Director of Epidemiology and the Head of Epidemiology Analytics at Janssen Research and Development, where he is leading efforts to develop and apply analysis methods to better understand the real-world effects of medical products. He is currently a collaborator in Observational Health Data Sciences and Informatics (OHDSI), a multi-stakeholder, interdisciplinary collaborative to create open-source solutions that bring out the value of observational health data through large-scale analytics. He served as a principal investigator of the Observational Medical Outcomes Partnership (OMOP), a public-private partnership chaired by the Food and Drug Administration, where he led methodological research to assess the appropriate use of observational health care data to identify and evaluate drug safety issues.

Patrick received his undergraduate degrees in Computer Science and Operations Research at Cornell University, his Master of Engineering in Operations Research and Industrial Engineering at Cornell, and his PhD in Pharmaceutical Outcomes and Policy from University of North Carolina at Chapel Hill. Patrick has worked in various positions within the pharmaceutical industry at Pfizer and GlaxoSmithKline, and also in academia at the University of Arizona Arthritis Center.

Martijn Schuemie, PhD
Director, Epidemiology Analytics
Janssen Research and Development

Dr. Martijn Schuemie received his Master’s degree in Economics with a major in Information Management. He completed his PhD in Computer Science on the topic of human-computer interaction in virtual reality systems for phobia treatment. In the past, he was employed as an assistant professor at the Erasmus University Medical Center of Rotterdam, where he started by researching the application of text-mining the scientific literature in support of molecular biology. He later moved to pharmacoepidemiology, and was one of the lead investigators in the EU-ADR project tasked with building a prototype drug safety signal detection system using population-level observational data. In 2012 he received a one-year fellowship of the FDA and became an active OMOP investigator.

In 2013 Martijn joined Janssen Research and Development, where he continued his research in OMOP and later in OHDSI. He is working on methods for estimating average effect sizes in observational, calibration of effect size estimates, and patient level prediction, as well as supporting the conversion of databases to the OMOP CDM. Within OHDSI, Martijn has developed the White Rabbit and Rabbit in a Hat tools, and is contributing to the OHDSI Methods Library. Martijn is heading the OHDSI Population-Level Methods workgroup together with Marc Suchard.

Eun Kyoung Ahn

Joel N. Swerdel, PhD MS MPH
Associate Director, Epidemiology Analytics
Janssen Research and Development, LLC

Joel Swerdel is an Associate Director of Epidemiology Analytics at Janssen Research and Development, a Johnson and Johnson company. He is involved in many epidemiological research projects where he designs novel approaches for the use of standard OHDSI methods. He has recently completed a project using predictive modeling to determine patients in end-of-life care. He is currently working on designing a standard approach for developing and evaluating diagnostic phenotypes.

Prior to joining Janssen Research and Development, Joel was at the Rutgers School of Public Health where he conducted epidemiology research in the areas of cardiovascular disease and cancer. Prior to Rutgers, Joel was at Bristol-Myers Squibb in drug development research. Joel received a BA from Rutgers, an MS from the Medical College of Wisconsin, and an MPH from the Rutgers School of Public Health. He received his doctorate in epidemiology from the Rutgers School of Public Health where he used patient-level prediction to develop models for predicting incident heart failure in subjects previously diagnosed with atrial fibrillation.

Don TorokDon Torok, MS
Ephir Inc

I have been working as a consultant with Ephir Inc. since January 2010. During that time, I have: specified ETLs for a number of EHR and Claims datasets into OMOP, Mini-Sentinal and PCORnet common data models; Installed the OHDSI Web API and Atlas tool set; Developed ETLs to OMOP CDM using AWS RedShift, Oracle, SQL-Server and Postgres for both claims and EHR datasets; QC’ed ETL implementations and OHDIS vocabularies; and implemented code to create Drug and Condition Era tables.

Prior to joining Ephir I worked as a programmer/analyst at IMS Health from June 2004 through Nov 2009. There I developed custom analytic reports, using health care data, for most major drug and other health care related companies.

Mui Van Zandt

Mui Van Zandt
Director Product Development
Mui is a Director of Product Development at IQVIA, managing the OMOP Factory. Mui’s area of expertise include software development, data conversions, agile process, and project management. The OMOP Factory has been performing OMOP ETL conversions on over 12 different datasets in 6 different countries. Mui has gained extensive knowledge working on large patient databases in the OMOP model and the standard vocabularies that are needed to support these conversions.

Mui is an active contributor to the community through various OHDSI working groups. She is one of the co-leaders of the China OMOP CDM/Vocabulary working group. She leads two of the sub-working groups within the THEMIS working group. She has and continues to perform OMOP tutorial trainings to many different organizations and conference, such as the OHDSI Symposiums, the China Hackathons, and individual universities.

Erica VossErica Voss, MPH
Associate Director, Epidemiology Analytics
Janssen Research and Development

Erica Voss is currently a Associate Director in the Epidemiology Analytics group within Epidemiology at Janssen Research & Development, a Johnson & Johnson company. Starting in the IT department, she focused on data warehousing and working with large datasets. In 2007, she started working with observational datasets and later joined the Epidemiology department in 2011. Her projects typically include studying patient populations across different therapeutic areas as well as implementing OHDSI tools, such as converting the Truven MarketScan and Optum Clinformatics claims datasets into the OMOP Common Data Model.  Erica received her Bachelor of Science in Information Sciences and Technology at the Pennsylvania State University, her Master in Public Health from Johns Hopkins Bloomberg School of Public Health, and is currently pursuing her PhD in Medical Informatics at Erasmus MC. She is also a certified Project Management Professional.

jwJames Weaver, MPH, MS
Manager, Epidemiology Analytics
Janssen Research and Development

I’m a Manager of Epidemiology Analytics at Janssen Research & Development, a Johnson & Johnson company. In the Epidemiology Analytics group within the Epidemiology department, my role is to design and execute observational research studies with a focus population-level effect estimation evidence generation and methodological development.

My background is in epidemiology, statistics, and data science and I have 10 years of experience in academia working with diverse teams in comparative effectiveness research, methods for causal inference, and applied predictive analytics. I have 3 years of experience working in the pharmaceutical industry. I have a BA from McGill University, an MPH from the Dalla Lana School of Public Health at University of Toronto, and an MS in business analytics from the Stern School of Business at New York University. I live in Toronto, Ontario.

Andrew WilliamsAndrew Williams, PhD, Special and Scientific Staff

Tufts Medical Center CTSI and Institute for Clinical Research and Health Policy Studies

Dr. Williams is a psychologist by training, a health services researcher, clinical informatician and data scientist. The areas his work has focused on include the conduct of pragmatic trials, on relating EHR-based performance measures to disease incidence, on interventions that promote individual health behavior change and on the measure of health literacy and health communication. He was a member of AcademyHealth’s Electronic Data Methods forum and the Data Quality Collaboratory. He oversees the Data Quality program of the Tufts CTSI.

Nigam ShahRoss D. Williams MSc.
PhD Student
Erasmus University Medical Centre

Ross Williams is a PhD student working in the group of Dr. Peter Rijnbeek at Erasmus MC, where he is part of the Health Data Science group (www.healthdatascience.nl). His main focus is creating tools and analysis methods to develop personalised medical risk prediction. His specific areas of interest are on the external validation of prediction models, net benefit assessment and techniques for temporal health data analysis. He contributes to the Patient Level Prediction OHDSI working group.

Ross obtained his MSc (2017) in Data Science from King’s College London having previously obtained his BSc in Physics and Philosophy from the same institution. Before starting work at Erasmus MC he spent time working on a Marie Curie scholarship on the TRANSACT project under the EU FP7 initiative.