Collaborative Data Science for Healthcare

Louis Agha-Mir-Salim

MBBS, BSc, BMedSc

Charité - Universitätsmedizin Berlin

Louis Agha-Mir-Salim is a research fellow at the Institute of Medical Informatics at Charité - Universitätsmedizin Berlin. Before graduating from medical school at the University of Southampton, Louis completed a BSc in Medical Sciences with Management at Imperial College London while working for two digital health start-ups. As a former visiting student at the MIT Laboratory for Computational Physiology, he was involved in several projects on the analysis of critical care data. Before going into full-time research, Louis initially worked as a doctor in anaesthesiology and nephrology. Wanting to foster cross-disciplinary collaboration between data scientists and clinicians, he served as faculty member at numerous MIT Critical Data events worldwide.

Leo Anthony Celi

MD, MSc, MPH

MIT, Harvard Medical School, Harvard T.H. Chan School of Public Health

As clinical research director and principal research scientist at the MIT Laboratory for Computational Physiology (LCP), and as a practicing intensive care unit (ICU) physician at the Beth Israel Deaconess Medical Center (BIDMC), Leo Anthony Celi brings together clinicians and data scientists to support research using data routinely collected in the process of care. His group built and maintains the publicly-available Medical Information Mart for Intensive Care (MIMIC) database and the Philips-MIT eICU Collaborative Research Database, with more than 15,000 users from around the world. The MIMIC-III paper has been cited more than 1700 times since 2016. In addition, Leo is one of the course directors for HST.936 – global health informatics to improve quality of care, and HST.953 – collaborative data science in medicine, both at MIT. He is an editor of the textbook for each course, both released under an open access license. "Secondary Analysis of Electronic Health Records" has been downloaded more than 500,000 times, and has been translated to Mandarin, Spanish and Korean. Leo has spoken in more than 35 countries across 6 continents about the value of data and learning in health systems. His publications have been cited more than 6000 times since 2015.

Marie-Laure Charpignon

MSc, BSc

Massachusetts Institute of Technology

Marie Charpignon is a PhD student in the Interdisciplinary Doctoral Program in Statistics at MIT Institute for Data, Systems, and Society (IDSS). Her research focuses on causal inference methods for drug repurposing for Alzheimer's Disease using electronic health record data from the US and UK, in collaboration with MGH’s Biomedical Informatics, Harvard Medical School’s Systems Pharmacology Laboratory and Imperial College London. Since taking HST.953 and HST.956, Marie has had the opportunity to work with various health data science projects, honing her skills in data integration and harmonization. These include understanding the drivers of excess deaths from COVID-19, examining the effect of news media in disease outbreaks,and optimizing definitions of ventilator-associated conditions, among others. She is a veteran mentor of numerous health datathons organized by MIT Critical Data, including those held in Sao Paulo, Milan, Seoul, Boston, Singapore, New York and Orlando.

Kenneth Eugene Paik

MD, MBA, MMSc

Massachusetts Institute of Technology

Kenneth Paik is a clinical informatician focused on quality improvement in healthcare through technology innovation, combining a multidisciplinary background in medicine, machine learning, business management, and technology strategy. As a Research Scientist at the MIT Laboratory for Computational Physiology his work encompasses the secondary analysis of clinical health data, taking a collaborative (academic and industry) and multidisciplinary (clinicians and data scientists) approach to build high-resolution datasets for the practical application of machine learning in healthcare. His global health work through MIT Sana leverages mobile technology innovation and digital health to bridge immense gaps in resources or infrastructure, including for example, pilot projects for NCD management mHealth for refugee and displaced populations in Syria and Lebanon.

Julia Situ

Undergraduate

Massachusetts Institute of Technology

Julia Situ is an undergraduate student at MIT studying Computer Science and Molecular Biology. As an undergraduate student researcher at the MIT Laboratory for Computational Physiology, Julia has used the opportunity to further explore her interests in healthcare, especially the intersection with computation. She hopes that through her work involving the analysis of electronic health records, she will be able to contribute to improve patient care and experiences. Research aside, Julia is also actively involved in MIT Emergency Medical Services and MIT Hacking Medicine.

Wesley Yeung

MBBS

National University Hospital, Singapore

Wesley Yeung is an internal medicine resident at the National University Hospital in Singapore. He is an affiliate scientist with the MIT Laboratory for Computational Physiology and has mentored at MIT Critical Data events in Singapore, Beijing and Boston. His research interests include the use of machine learning to improve emergency medical services, secondary analysis of electronic health records and predictive modelling of patients with critical illness.