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.
Dr. Boyle is the Director of the Research Information Technology Unit (R2). Since 2006 Dr. Boyle has been researching, developing and implementing systems for the ethical acquisition of record-linkable data for audit, research and health surveillance. Consent management, security and privacy-protecting record linkage are key components and research areas. The software systems (GRHANITETM) are now responsible for the largest collections of record-linkable primary care data ever accumulated in Australia. Prior to emigrating from Scotland in 2006, Dr. Boyle worked in a similar capacity to develop and implement technologies for wide-scale data acquisition. His system SCI-DC Network is internationally recognized and is playing a continuing key role in the support of population-based diabetes health service provision across Scotland.
Dr. Cha is the head of data at the Cancer Big Data Center, National Cancer Center, Korea. He received his master’s and doctorate degrees from the Department of Electronic Computer Science, Chungbuk National University. He previously worked for the Korea Centers for Disease Control and Prevention and is currently working for the Cancer Big Data Center and AI Business Team at the National Cancer Center.
Dr. Cha’s research interests and activities include the use of clinical data governance, various analytic methods of clinical data, primarily specialized in cancer big data, and the use of artificial intelligence data. His activities establish contributions in various fields across the government using various data platforms along with EMR, EHR and PHR.
Jaehyeong Cho is a graduate student at Ajou University School of Medicine, South Korea. He received B.S. in Information Statistics from Andong University, Andong, South Korea in 2017. His research interests are applying statistical, epidemiological, and visualization methods to Common Data Model.
He joined OHDSI in 2017 and participated in several medical informatics related projects. He presented 1 software demonstration at the 2017 OHDSI Symposium: AEGIS: Application for Epidemiological Geographic Information System.
Frank is an Associate Director at IQVIA within the OMOP team. He manages a team of analysts and developers who perform OMOP conversions. He has worked on multiple OMOP conversions internally at IQVIA and externally across the globe ranging from project oversight to writing ETL code for the conversions on various source systems.
Frank’s technical experience is focused on ETL development, database design, database administration and performance tuning. Frank has strong expertise in business intelligence, reporting, analytics and process automation.
Frank attends the OHDSI collaborators and EHR working group meetings. He has also contributed an ETL poster to the OHDSI symposium and provided assistance for the OHDSI symposium training classes.
Dr. Feng is currently an Assistant Professor at the Institute for Data Science, National University of Singapore, and the Senior Assistant Director of National University Hospital championing the big data analytics efforts His research is to develop machine learning algorithms to extract actionable knowledge from a large amount of data to enable a better quality of healthcare. His research brings together concepts and tools across deep learning, optimization, signal processing, statistical causal inference and big data management. Dr. Feng’s work was recognized by both well-established journals, such as Science Translational Medicine, JAMA and top international conferences, such as KDD, AAAI and AMIA.
Dr. Hiramatsu is the professor and director of the Department of Medical Informatics at the International University of Health and Welfare (IUHW), Japan. He has been seeking a fusion of medical informatics and epidemiology, and he is working on an OMOP database network with other university hospitals in his research project. Before moving to IUHW, he was at the University of Tokyo Hospital and served as its site administrator of MID-NET (Sentinel-like project in Japan) conducted by PMDA (Pharmaceuticals and Medical Devices Agency) and the Ministry of Health, Labor and Welfare.
Various professional experiences represent the journey of his life. He was engaged in an epidemiological investigation of a resident-based cohort and received his PhD based on nutritional epidemiological research. However, before all that, he had had a lengthy experience of being a patient himself, longer than that of being a clinician, including 6 months of hospitalization with multiple complications and a decade of a restricted lifestyle. Dr. Hiramatsu has a wealth of experience in PC software development with several horizontal software packages as an R&D engineer, a team manager, or the senior executive director of a PC software company. Another one of his strengths has been the area of Internet connection and server construction/operation when in 1990 he started his Internet experience at the WIDE project (Widely Integrated Distributed Environment), which operated as Japan’s Internet backbone in the early days; it also aimed to coordinate academia and industry into an autonomous group that acts across organizational boundaries with new technologies in order to create a better society.
Jason C. Hsu Ph.D. is an Assistant Professor at International Ph.D. Program in Biotech and Healthcare Management at Taipei Medical University (TMU) in Taiwan, and he is also the Vice Dean in the Office of Data Science in TMU.
Jason specializes in smart biotech and healthcare management, and he is skilled in using multiple big data and scientific research methods such as statistics, economics, and artificial intelligence to carry out research on disease management (precision medicine, disease burden, epidemiology and health inequality), drug management (precision treatment, product value assessment, prescription behavior and drug utilization) and policy management (health insurance drug payment policy and budget impact analysis).
Prior to joining TMU, Jason was a Fulbright research fellow and a postdoctoral researcher focusing on Pharmaceutical Policy Research at the Department of Population Medicine at Harvard Medical School (HMS). He was also a faculty at the School of Pharmacy and Institute of Clinical Pharmacy and Pharmaceutical Sciences, College of Medicine in National Cheng Kung University (NCKU) in Taiwan.
Jason received his Bachelor’s degree in Pharmacy from Taipei Medical University (TMU), his Master of Science degree in Technology Management from National Tsing Hua University (NTHU) and his Doctor of Philosophy (PhD) in International Business from National Taiwan University (NTU).
Dr. Jonnagaddala is an early career researcher (Research Fellow) with the School of Population Health under the Faculty of Medicine at the UNSW Sydney, Australia. Jitendra’s research interests are in the secondary usage of routinely collected electronic health records data. His focus is on linking and harmonizing primary care data with hospital admissions data to undertake large scale observational research. Jitendra as part of his PhD investigated the methods to assess absolute risk assessment for Coronary artery Disease in Type 2 Diabetes patients using EHRs. He is also the main organizer and editor of the International Workshop on Digital Disease Detection using Social Media (DDDSM). Jitendra leads several research projects working with diverse stakeholders such as UNSW, NSW Health, NSW Pathology and Cancer Institute NSW. Prior to that, he worked in Singapore for Singapore Health Services in translational cancer research. He is also a WHO international consultant on eHealth and Health information systems. As part of his consulting assignments, he worked with various funding agencies, health ministries, and technical assistance agencies and not-for-profit organizations.
Dr. Kahn was the Founding Director of Health Data Compass, a multi-institutional research data warehouse within the Colorado Center for Personalized Medicine that combines clinical, administrative, financial, biological and external linked data on over 6.0M patients from Children’s Hospital Colorado (3 hospitals), University of Colorado Health System (7 hospitals), CU Medicine Inc. (physician practice plan), basic biological data from University investigators, environmental and external data sources from local, regional, state and national data sets. Health Data Compass has supported over 1000 data requests focused on data-driven personalized medicine discoveries. I was the informatics lead for the AHRQ-funded SAFTINet distributed clinical research network and the informatics co-PI for two Patient-Centered Outcomes Research Institute (PCORI) national clinical data research networks (PEDSnet; PORTAL). I have significant experience in database integration across multiple institutions.
My informatics research interests are focused on informatics tools to support EHR-based observational research, data quality assessment and data sharing. I have been the Principle Investigator and lead publication author in the field of Data Quality Assessment in large scale clinical data networks. I have established an international reputation in the design and implementation of data quality assessment oversight programs. My research interests focus on data quality assessment and reporting in large multi-institutional research networks.
Chungsoo Kim is a graduate student in the Department of Biomedical Informatics at the Ajou University School of Medicine. He holds his PharmD from Ajou University College of Pharmacy in 2019. His research interests include comparing drug effects and predicting individual drug effects through a common data model.
He joined OHDSI in 2019 and participated in several medical informatics-related projects. He presented posters in both the OHDSI European Symposium and the OHDSI U.S. Symposium in 2019, also he also participated and prepared a tutorial program in the 2019 OHDSI Korea International Symposium.
Kwangsoo Kim (Ph.D.) is an associate professor for Transdisciplinary Department of Medicine & Advanced Technology in Seoul National University Hospital, South Korea. He received his Ph.D. degree in Industrial Engineering from Korea University and worked as a postdoctoral research fellow at bioinformatics institute in Seoul National University. His research area focuses on developing translational biomedical informatics methodologies for analysing electronic health record (EHR) data, unstructured clinical data and next generation sequencing (NGS) data.
Eizen Kimura is a Professor at the Medical Informatics Department of the Medical School of Ehime University, managing the hospital information system of Ehime University Hospital. He has been working on standard medical information standards and is currently researching FHIR and Terminology/Ontology. As an OHDSI Japan member, he is developing the terminology mapping methodology between Japan terminologies and OHDSI standard vocabulary to promote clinical research using real-world data in Japan.
Director, Chief Health Scientist Office (CHSO)
Ministry of Health, Singapore
Mingshi’s experience in biomedical sciences sector spans across strategy development at national and institutional level, managing strategic funding initiatives, as well as overseeing research operations. She is currently Director in the Chief Health Scientist Office (CHSO), Ministry of Health. The Office was formed in 2019 to foster a supportive environment for R&D, strengthen the translation of research, and shape MOH’s S&T agenda.
Kenichi Kohno is a Director of Health Data Science at Translational Research Center for Medical Innovation in Foundation for Biomedical Research and Innovation at Kobe.
His aim is data sharing in clinical research and the goal to achieve medical innovation through the collaboration of researchers.
Kristin Kostka is an Associate Director at IQVIA running the OMOP Data Network and a perennial collaborator within the Observational Health Sciences and Informatics (OHDSI) community – a global, multi-disciplinary community of more than 200 organizations aimed at improving patient outcomes through large scale analytics. In her work, Kristin partners with hospitals, payers and healthcare providers to help organizations unlock the power of institutional data and connect with the world’s largest observational health data network.
Kristin has over 10 years of experience leading real-world evidence generation studies, designing and implementing enterprise patient data lakes, conducting large-scale multinational clinical trials and preparing regular submissions. She is considered a preeminent voice in observational health research and data science providing expertise across the US, Europe, Middle East and Asia to deliver presentations on open science methodologies – including at Johns Hopkins University, the University of Oxford, Tufts Clinical and Translational Science Institute, Northwestern University and Fudan University. Kristin co-authored three chapters for the world’s first observational health open science textbook, the Book of OHDSI and is one of the facilitators for the OHDSI COVID-19 Study-a-thon and follow-on research programs including Project CHARYBDIS (Characterizing Health Associated Risks, and Your Baseline Disease In SARS-COV-2). Kristin is also aiding the US National Institutes of Health in designing and implementing a centralized data repository, the National COVID Cohort Collaborative, for COVID-19 surveillance.
Kristin is a recipient of many industry awards including 2020 Elon University Young Alumni Council “Top 10 Under 10” Alumni Award, 2018 OHDSI Titan Award in Community Collaboration, a 3- time recipient of Deloitte Outstanding Performance Award and an 8-time recipient of the Deloitte Applause Award for exceptional client service. She holds a Bachelor’s degree in Exercise Science from Elon University and a Master’s in Public Health in Epidemiology from Boston University School of Public Health.
Her current research includes (1) real world data-based pharmacovigilance(PV), (2) develop and apply analysis methods to better detect the real-world effects of medical products. She has nearly 10 years of experience in medical informatics, focusing on real-world data analysis including electronic health records, and claims.
She received his undergraduate degrees in Computer Science at Gachon University, her Master and PhD of Medical informatics at Seoul National University. She has worked in research professor positions within the Medical informatics lab at Seoul National University Hospital.
Dr. Feng Lei is a leader of the project department of the National Clinical Research Center of Mental Disorder, Beijing Anding Hospital, Capital Medical University. Doctor Feng takes depressive disorder and bipolar disorder as the main professional direction, especially the innovation of diagnosis and treatment technology, attaches importance to the combination of clinical research and basic research, as well as the design and implementation of a clinical research program.
Jing is responsible for conducting China OMOP studies and introducing OHDSI analytical methods to the broader group in China. Her work includes performing real-world evidence research using OHDSI OMOP model, coordinating and leading multi-center, multi-country studies, and executing quality assurance checks on OMOP CDM databases around the world. She has been an active contributor to OHDSI China activities, such as the Book of OHDSI translation, and China vocabulary standardization.
Jing received her undergraduate degree from Shanghai Jiao Tong University in China, and a Master of Science degree from the University of Minnesota in the US. Prior to IQVIA, she worked for Travelers Insurance (MN, USA) and Ant Financial (Shanghai, China) on predictive modeling and statistical analysis.
Prof Li is a pioneer of Al in Medicine, Medical Informatics Research and a practicing dermatologist. He has been the Principal Investigators of many national and international projects related to translational biomedical informatics, patient safety and artificial intelligence.
He has served as President-elect(2021~2023) of the International Medical Informatics Association (IMIA), as President of the Asia-Pacific Association for Medical Informatics (APAMI). Moreover, he has also been elected as a fellow of Australia College of Health Informatics (2009), of American College of Medical Informatics (2010), and of International Academy of Health Science Informatics (2017).
He has dedicated himself to evolving the next generation of medical Al for patient safety and prevention (“Earlier Medicine”). He has been involved deeply not only in biomedical informatics projects in Taiwan but also has developed international collaborations across several continents including Europe, America and Africa. His positions include Distinguished Professor, Taipei Medical University; dermatologist, Taipei Municipal Wanfang Hospital; and President-elect, International Medical Informatics Association.
Yunpeng Li is Director of Big Data and AI department at SmindU Medical Science & Technology Co., Ltd., managing the big data product line of big data platform R&D based on OMOP CDM、big data application R&D of medical research, AI-related model training and data mining. Yunpeng’s area of expertise including software research and development, data ETL, AI-related NLP, model setup and training, data mining, agile process, project management. The product line has been successfully experimenting to set up large patients database based on OMOP CDM in China, which implements a “one-stop solution for doctors via: data collection, data governance, data verification, data ETL, data application” and support them to more easily and efficiently deliver research paper, and eventually energize the entire medical industry.
Professor Teng Liaw is a clinician scientist and informatician at UNSW Sydney. He uses mixed methodologies for informatics research with a focus on digital health, data quality & interoperability and ethical, legal & social issues. As Director of the WHO Collaborating Centre on eHealth, he assists WHO member countries with assessing and improving digital health capability and capacity to implement and sustain digital health programs to achieve universal health coverage, safe and cost-effective integrated person-centred health services and community development. He is a Fellow, American College of Medical Informatics and Founding Fellow, Australasian College of Health Informatics and International Academy of Health Sciences Informatics. He is the current Chair of the IMIA Primary Care Informatics WG.
Lei Liu, PhD
Professor in Biomedical informatics
Shanghai Medical College, Fudan University
Lei Liu, PhD, is a professor at the Institutes of Biomedical Sciences at Fudan University. He directs medical information and medical imaging intelligent diagnosis Institute of Fudan University big data research institute. He was the Director of Bioinformatics at the University of Illinois at Urbana-Champaign from 1999 to 2007. He was the Faculty Fellow in the National Center for Supercomputing Application (NCSA) of the University of Illinois from 2000 to 2007. Prof. Liu received his Doctor of Philosophy from the University of Connecticut in 1997. In addition, he holds a Master of Science in biochemistry from Chinese Academy of Sciences, and a Bachelor Science from Peking University in China. He is in charge of the project of “knowledgebase construction of disease research precision medicine”, a National Key Research and Development Project of Precision medicine of China. Prof. Liu is an expert in bioinformatics and clinical informatics. His primary research interests include 1) Omics data analysis and mining; 2) Integration and mining of biomedical big data; 3) Biomedical knowledgebase and knowledge graph development; 4) Artificial intelligence medicine.
Dr. Hui Lu is the Head of the Department of Bioinformatics and Biostatistics, Shanghai Jiao Tong University, and the co-director of SJTU-Yale Joint Center for Biostatistics. He is also the Director of the Center for Biomedical Informatics in Shanghai Children’s Hospital. He got a Bachelor’s degree from Peking University and PhD from the University of Illinois at Urbana-Champaign. He currently leads a National Key R&D project “Big data analysis technology and pipeline development for precision medicine”. His research areas include big data analysis in biomedical research, bioinformatics, biostatistics, molecular network modeling, systems biology, and drug design. His current research interests are in translational medicine: integrating multi-omics data and disease phenotypes, constructing disease network, investigating self-adapting methods for a clinical trial, set up high-speed genomics data processing pipeline, large scale patient record analysis, building a phenotype-genotype based diagnosis system.
Dr. Yuan Lu was trained in epidemiology and global health, with a focus on cardiovascular diseases. She obtained both of her ScD and MSc Degrees in Global Health and Population at the Harvard School of Public Health. Her current research interests bridge population health, cardiovascular disease prevention, implementation science, and clinical informatics. She is particularly committed to harnessing the digital transformation of medical data and advanced analytics to generate high-quality, real-world evidence that provides actionable insights to improve patient outcomes. As a full-time Assistant Professor of Cardiovascular Medicine at Yale School of Medicine, she has more than 10 years of experience in conducting and analyzing large-scale observational studies in the field of cardiovascular epidemiology and global health. She has authored over 50 peer-reviewed publications, including first author articles in leading journals such as The Lancet and Circulation, and her work has been cited more than 40,000 times. She is currently an NHLBI K12 scholar in implementation science, where she is using electronic health record data from the Yale-New Haven Health System to identify patients with persistent hypertension and gaps in care.
In 2019, Dr. Lu joined the newly established OHDSI APAC research committee. She is leading the first OHDSI APAC collaborative effort focusing on the comparative effectiveness of dual combination therapy in treatment escalation of hypertension. She is also a member of the OHDSI LEGEND working group.
Eri Matsuki is a trained hematologist/oncologist with a research interest in the treatment of chronic myeloid leukemia and lymphoma. She is currently involved in the development of a real-world data collection platform from electronic health records through a collaborative effort among Core Clinical Research Hospitals under the initiative supported by the Japan Agency for Medical Research and Development (AMED).
Graduated from Peking Union Medical College with an M.D. degree, Dr. Gong Mengchun entered Peking Union Medical College Hospital and accomplished the internal residency training in 2014, after which time he worked at the University of California, San Francisco as a visiting scholar.
Dr. Gong joined the area of applied medical informatics in 2015 and now works as the Distinguished Professor in the Institute of Health Management, Southern Medical University, China. He is actively engaged with international academic societies and holds the positions including the Diagnostic Science Committee member of IRDiRC (www.irdirc.org), the Member-at-Large of the Global Health Informatics Workgroup of AMIA (www.amia.org), the Medical Informatics Consultant of the National Children’s Care Center/Fudan University Children’s Hospital and the member of the executive committee of the Chinese Association of Bioinformatics.
Dr. Gong took charge of the National Rare Diseases Registry System of China (www.nrdrs.org.cn) as the executive director from 2016 to 2019 and has been a pioneer in rare disease research and patient advocacy in China. His research focus covers medical terminology/ontology, precision medical informatics, rare diseases and orphan drugs development, and health technology assessment (HTA). He is also actively engaged with the bioinformatics society in China and is currently a member of the executive committee of the Chinese Association of Bioinformatics.
On the industrial side, as one of the co-founders, Dr. Gong holds the position of the Senior Vice President and Chief Medical Informatics Officer of DHC Technologies Co. which is the leading company in China in precision medicine IT solution, healthcare big data and real-world insights.
Assistant Professor Ngiam Kee Yuan is the Group Chief Technology Officer of the National University Health System (NUHS) Singapore overseeing technology deployment in the Western Healthcare Cluster of Singapore. In this role, he assists the Chief Executive to implement new technologies throughout NUHS and serves as the Chief Advisor to the Centre for Innovation in Healthcare in NUHS.
Prof Ngiam is concurrently the Deputy Chief Medical Informatics Officer at the National University Hospital of Singapore with a special focus on artificial intelligence research and implementation in healthcare. In addition, he co-chairs the OHDSI Singapore chapter along with Dr. Mengling Feng
Alex has 10+ years of experience in the field of Healthcare Informatics, has developed the HIT products and implemented the HIT projects for clients who are from enterprise to ministry. Project scope has been covered in different levels (from small to huge; from enterprise to national level), and it is defined in fields as ICT, Healthcare. Especial, Alex has a lot of lessons learned when he has faced the difficult matters of the project in several roles (engineering, researcher, manager, and so forth). It is a valued experience to help him to manage projects successfully.
Aki Nishimura is an Assistant Professor of Biostatistics at Johns Hopkins School of Public Health and is an active contributor to OHDSI analytic tools and study executions. Aki is a statistician/data scientist with expertise in Bayesian methods and statistical computing. In particular, he is currently working on developing software for fitting large-scale Bayesian hierarchical regression to aggregate information across the individual healthcare databases within the OHDSI community.
Aki also serves as a Program-Chair of the junior researcher section of the International Society of Bayesian Analysis. His research has earned him the Laplace Award (2016) from Section on Bayesian Statistical Science of the American Statistical Association, as well as the Savage Award honorable mention (2018) from the International Society for Bayesian Analysis.
Nicole is a biostatistician and Deputy Director the Quality Use of Medicines and Pharmacy Research Centre, University of South Australia and a chief investigator on the Centre of Research Excellence on Post-market Surveillance of Medicines and Medical Devices. Nicole is responsible for evaluating the quality use of medicines program: Veterans’ Medicines Advice and Therapeutics Education Service (Veterans’ MATES). Veterans’ MATES uses administrative claims data to develop and evaluate interventions to improve the use of medicines in the veteran community in Australia. Nicole is also a member of the Drug Utilisation Sub-Committee (DUSC) of the Australian Government Department of Health Pharmaceutical Benefits Advisory Committee. She is a collaborator of the Asian Pharmacoepidemiology Network (AsPEN) (www.aspennet.asia).
Dani Prieto-Alhambra is the theme lead for observational research and chair for the big health data research group at the Centre for Statistics in Medicine, University of Oxford.Prieto-Alhambra leads database and pharmaco-epidemiological research within the Epidemiology research group in NDORMS and has experience designing, analysing and interpreting electronic medical records from around the world. He has worked on databases like the United Kingdom’s CPRD (formerly GPRD), Spain’s SIDIAP Database, Denmark’s Danish Health Registries, Italy’s HSD, and the Netherlands’ IPCI (Netherlands). Dani is the academic lead for EHDEN WP1 (www.ehden.eu).He studied Medical Sciences at the Autonomous University of Barcelona in Spain (1996-2002), qualified as a General Practitioner in 2006, and obtained an MSc in Primary Care Research from the Autonomous University of Barcelona in 2009. Prieto-Alhambra joined NDORMS in June 2009 to work on the epidemiology of musculoskeletal conditions, and he was awarded an “excellent cum laude, with a European mention” PhD in 2011 for his work on the potential role of bisphosphonates in knee osteoarthritis and fractures.Prieto-Alhambra also obtained an MSc in Musculoskeletal Sciences from NDORMS and a Certificate in Pharmaco-epidemiology and Pharmacovigilance from the London School of Hygiene and Tropical Medicine.
Selva received his master’s degree from Nanyang Technological University in Singapore. He is currently working as a data analyst under Dr. Mengling Feng in Saw Swee Hock School of Public Health. In addition, He is also one of the founding members of the OHDSI-SG regional chapter. Selva has experience in transforming raw EHR and survey data sources to OMOP CDM standards. He has already been part of OHDSI network studies and has been an instructor during OHDSI-US 2020 symposium.
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 research, 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 he is contributing to the OHDSI Methods Library. Martijn is heading the OHDSI Population-Level Methods workgroup together with Marc Suchard.
Sarah is the Associate Director of Data Science for IQVIA. She leads a team of data scientists who create and execute a number of studies using IQVIA’s converted OMOP data assets. It is also her mission to increase both her and her team’s presence within the OHDSI community, contributing both technical expertise as well as knowledge sharing.
Prior to joining IQVIA, Sarah has built her career over the last 20+ years within the UK health sector – conducting large scale Public Health analytics within the NHS, leading in data management both for the Department of Health and the General Medical Council, as well as designing and implementing data lakes and the creation of a new Data Science function for a UK Private Medical Insurance company.
Sarah joined the OHDSI community in 2018 and is an active member of various OHDSI working groups. She strives to extend her OHDSI collaboration further by offering further support in the community and to perform OMOP tutorial trainings. She also enjoys bringing her more creative side to the community.
Dr. Suchard is at the forefront of high-performance statistical computing. He is a leading Bayesian statistician who focuses on inference of stochastic processes in biomedical research and in the clinical application of statistics. His training in both Medicine and Applied Probability help bridge the gap of understanding between statistical theory and clinical practicality. He has been awarded several prestigious statistical awards such as the Savage Award (2003), the Mitchell Prize (2006 and 2011), as well as an Alfred P. Sloan Research Fellowship (2007) in computational and molecular evolutionary biology and a Guggenheim Fellowship (2008) to further computational statistics. He received the Raymond J. Carroll Young Investigator Award (2011) for a leading statistician within 10 years post-Ph.D., and in 2013 he was honored with the Committee of Presidents of Statistical Societies (COPSS) Presidents’ Award for outstanding contributions to the statistics profession by a person aged 40 or under. He is an elected Fellow of the American Statistical Association and of the Institute of Mathematical Statistics.
Lingyi is an OMOP Project Administrator at IQVIA. He is also Secretary for OHDSI China. Lingyi coordinates and teaches at OHDSI events in China, such as the OHDSI China Annual Symposium and OHDSI tutorials in China. He also promotes OHDSI various sources such as online media, website, online forums and WeChat in China. He contributed a lot to the translation of Book of OHDSI and Atlas in Chinese.
Lingyi received his undergraduate degree in Applied Mathematics at East China University of Science and Technology, his Master of Science in Applied Mathematics at the University of Houston, and another Master of Science in Biomedical Informatics at The University of Texas Health Science Center at Houston. He also did part of the MBA at Rice University, focusing on Corporate Finance and Entrepreneurship. Lingyi is also serving as Healthcare Information and Management Systems Society (HIMSS) Innovation Committee member starting from Aug 1st, 2018.
Desmond is a Data Analyst at the Vigilance and Compliance Branch at the Health Sciences Authority of Singapore (HSA). He is involved in the EMRALD (Electronic Medical Records for Active Surveillance of Adverse Drug Reactions) program to develop text mining and analytics techniques to enhance HSA’s active drug safety surveillance activities. He is also a pharmacist by training and his interest areas include drug safety outcomes and healthcare analytics.
Tan Hui Xing is a Data Analyst at the Vigilance and Compliance Branch of the Health Sciences Authority of Singapore (HSA). She is involved in the EMRALD (Electronic Medical Records for Active Surveillance of Adverse Drug Reactions) program to develop data mining, text mining and machine learning techniques to enhance HSA’s active drug safety surveillance activities. Her day-to-day job includes analyzing electronic health records to investigate the relationships between the drugs and adverse drug reactions of interest.
Mui is a Senior Director of OMOP Data Networks and Product Development at IQVIA, managing the OMOP Development Team. She has over 20 years of experience in software development, data conversions, agile process, and project management. Mui is an expert in large patient databases in the OMOP model and the standard vocabularies that are needed to support these conversions. She helped pioneer the curriculum for the OHDSI tutorials delivered around the world. Under Mui’s leadership, the OMOP Development Team has performed OMOP ETL conversions on over 20 different datasets in 9 different countries.
Mui is a leader within the OHDSI Community – serving on the OHDSI Steering Committee, leading the THEMIS quality group, co-leading the China OMOP CDM/Vocabulary working group, serving as a reviewer on the OHDSI Symposium Scientific Committee and mentors fellow collaborators in the Women of OHDSI group. She is regularly invited to speak about the OHDSI community at conferences across the globe. Her speaking engagements include the OHDSI Symposiums (US, Europe, China and Korea), the China Hackathons, numerous individual universities, notably the University of Oxford, and a variety of pharmaceutical companies. In 2018 Mui was awarded the OHDSI Titan Award for Community Collaboration recognizing her extensive contributions to foster the OHDSI community globally.
Xialin is a data scientist at OMOP Studies team at IQVIA. She focused on conducting analysis for OHDSI studies, presenting at OHDSI China tutorials, collaborating with doctors and researchers, and sharing results that use the OMOP common data model.
Xialin Wang has finished her undergraduate degree in Statistics and Economics from the University of Washington and her graduate degree in Biostatistics from Columbia University. Her area of expertise includes data mining, data quality assurance, statistical modeling and clinical trials. She participated in several OHDSI activities in China and helped to translate the Book of OHDSI and ATLAS to Chinese.
Prior to joining IQVIA, she worked as a biostatistician at The Medicines Company (NJ, USA) and Synyi AI (Shanghai, China).
Professor Wong is Co-Director of the Centre for Safe Medication Practice and Research, Department of Pharmacology & Pharmacy, and holder of the Lo Shiu Kwan Kan Po Ling Professorship in Pharmacy at the University of Hong Kong. He is Co-Director of Centre for Medication Optimisation Research and Education (CMORE) at the University College London Hospital and UCL School of Pharmacy. His expertise is in using big data research to investigate the optimum use of medications. He has over 300 peer-reviewed papers published in prominent journals including JAMA, JAMA Internal Medicine, JAMA Psychiatry, Lancet Psychiatry, Lancet Infectious Disease, BMJ, Annals of Internal Medicine, PLOS Medicine, Journal of the American College of Cardiology, Gastroenterology and Guts. Professor Wong was cited among the top 1% of scholars in the Clarivate Analytics’ Essential Science Indicators from 2015 to 2020. In recognition of his research, Professor Wong has received different awards and fellowships for his work as an academic pharmacist.
He was awarded the Chemist and Druggist Pharmacy Practice Research Conference Medal from the Royal Pharmaceutical Society of Great Britain in 2004. He is the only pharmacist to date to have received a UK Department of Health Public Health Career Scientist Award in 2002. He was awarded an Honorary Fellowship from the Royal College of Paediatrics and Child Health in the UK in 2011, an Honorary Fellowship from the College of Pharmacy Practice in Hong Kong in 2013, and a Fellowship from the Royal Pharmaceutical Society of Great Britain in 2013, British Pharmacological Society 2019 and International Society of Pharmacovigilance in 2019.
Clinical Associate Professor Yeo Khung Keong is a Senior Consultant with the Department of Cardiology at the National Heart Centre Singapore. He is the Academic Vice-Chair of Training and Education, and the Research EXCO in the SingHealth Duke-NUS Cardiovascular Sciences Academic Clinical Programme. Clin Assoc Prof Yeo is also the Deputy Group Chief Medical Informatics Officer (Research) of SingHealth.
Sooyoung Yoo (Ph.D.) is Associate Professor of Office of eHealth Research and Businesses in Seoul National University Bundang Hospital (SNUBH), South Korea. She is also the director of Healthcare ICT Research Center and oversees OMOP CDM Conversion in SNUBH. After graduating from a Graduated School of College of Medicine, Seoul National University in 2008, she has been working as a medical informatics specialist in SNUBH since 2009. She has participated in various health IT researches ranging from medical information sharing to electronic health record (EHR) data analytics. Her major interests are the EHR technology, medical information standards, health information exchange, smart hospital solutions, and health data analytics.
Dr. You is a medical doctor who majored in internal medicine from Severance hospital, Korea. He received his Master of Medical Science at the same university. Currently, he is a PhD candidate in the Department of Biomedical Informatics, Ajou University, and he studies primarily OHDSI network research. He received the best community contribution award for clinical evidence generation at the 2017 OHDSI symposium. He works as a member of several OHDSI working group: Genomic WG, Population-Level Estimation WG, and Patient-Level-Prediction Oncology WG.
Xinwei Zhang is a senior medical consultant of the medical big data department at SmindU Medical Science & Technology Co., Ltd. He has experience working with OMOP CDM database in the areas of psychiatric research. His research interests are in the areas of modeling big medical data for prediction about patient outcome, medical data analytics, visualization of clinical data, data quality assessment.
Huijuan is currently a senior assistant director in the division of analytics and information management in Ministry of Health Singapore. She started her career in software development and later specialized in data analytics. She has experiences in data analytics in different industries like telecommunication, investment and healthcare. Her current areas of focus include data architecture, data engineering and data management.
Yi Zhou, PhD, is a professor at Sun Yat-Sen University. He is the Vice President of the National Institute of Health and Medical Big Data and the Director of Zhongshan Medical School Medical Informatics Teaching and Research Department at Sun Yat-Sen University. Dr. Zhou received his Doctor of Philosophy in medical informatics at Sun Yat-Sen University.
Dr. Zhou has conducted much research on health and medical Informatics, big data and medical artificial intelligence. A lot of pioneering work has been done on the analysis and model research of clinical disease big data in the aspects of medical informatics and health care big data standards, the convergence and fusion of diverse heterogeneous data in health care, nonlinear dynamics and artificial intelligence methods (natural language processing, deep learning, etc.).