• Schedule and Mentors


    Cultivate cross-disciplinary collaborations

    3-5 Dec 2021


    Over SGD 20,000 Total Cash Prizes for Top Teams

  • Mentors

    Assoc Prof Leo Anthony Celi​ (MIT)

    Clinical Director, LCP MIT

    has practiced medicine in three continents, giving him broad perspectives in healthcare delivery. As clinical research director and principal research scientist at the MIT Laboratory for Computational Physiology (LCP), and as an attending physician at the Beth Israel Deaconess Medical Center (BIDMC), he brings together clinicians and data scientists to support research using data routinely collected in the process of care. His group built and maintains the public-access Medical Information Mart for Intensive Care (MIMIC) database, which holds clinical data from over 60,000 stays in BIDMC intensive care units (ICU). It is an unparalleled research resource; over 5000 investigators from more than 70 countries have free access to the clinical data under a data use agreement. In 2016, LCP partnered with Philips eICU Research Institute to host the eICU database with more than 2 million ICU patients admitted across the United States.


    Leo also founded and co-directs Sana, a cross-disciplinary organization based at the Institute for Medical Engineering and Science at MIT, whose objective is to leverage information technology to improve health outcomes in low- and middle-income countries. He 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. The textbook “Secondary Analysis of Electronic Health Records” came out in October 2016 and was downloaded more the 100,000 times in the first year of publication. The massive open online course HST.936x “Global Health Informatics to Improve Quality of Care” was launched under edX in February 2017. Finally, Leo has spoken in 25 countries about the value of data in improving health outcomes.

    Dr. Eric Gifford (PhD)

    Director, MSD Research​

    founded the R&D IT team at the MSD Singapore IT Hub in 2016. He is an experienced pharmaceutical R&D IT professional with in-depth knowledge of computer-assisted drug discovery, business development and external collaborations. He remains focused on building teams employing emerging computational technologies to advance pharmaceutical research and development. He is a strong advocate of open science and precompetitive collaborations to leverage solutions across industries. Eric is also the founding team leader for the MSD Singapore IT Hub External Ecosystem Engagement Team which is responsible for identifying and delivering successful technology partnerships between MSD and Singapore based entities.

    Dr David Pilcher, MD​

    Director, ANZICS

    is an Intensive Care Specialist at The Alfred Hospital in Melbourne. He trained in respiratory and general medicine in the UK before moving to Australia in 2002 to undertake training in Intensive Care Medicine. His interests include organ donation, lung transplantation, ECMO, severity adjustment of ICU outcomes, ICU performance monitoring and the epidemiology of Intensive Care medicine. He is the Chairman of the Australian and New Zealand Intensive Care Society (ANZICS) Centre for Outcome and Resource Evaluation (CORE) which runs the bi-National critical care registries. He is a medical advisor to DonateLife in Victoria. He is also an Adjunct Clinical Professor with the Department of Epidemiology and Preventive Medicine at Monash University.

    Dr Finale Doshi-Velez, ​PhD

    Associate Professor, Computer Science, Harvard University

    is a John L. Loeb associate professor in Computer Science at the Harvard Paulson School of Engineering and Applied Sciences. She completed her MSc from the University of Cambridge as a Marshall Scholar, her PhD from MIT, and her postdoc at Harvard Medical School. Her interests lie at the intersection of machine learning, healthcare, and interpretability.

    Dr Omar Badawi, PharmD, MPH, FCCM

    Head of Health Data Science and AI , Philips

    is the Head of Health Data Science and AI in the Philips Patient Care Analytics business and leads the research for developing and validating product-related predictive algorithms and decision support tools. He is also an Adjunct Assistant Professor with the University of Maryland School of Pharmacy and Research Affiliate at the Massachusetts Institute of Technology. He earned a Master in Public Health degree with a focus in Epidemiology and Biostatistics from The Johns Hopkins Bloomberg School of Public Health and is currently the Program Manager for the Philips eICU Research Institute which supports collaborative research between industry, academia and clinicians using de-identified clinical data representing over 6 million ICU patients. Dr. Badawi is also a Fellow of the American College of Critical Care Medicine.

    Asst/Prof Judy Wawira Gichoya​

    Department of Radiology & Imaging Sciences, Emory University

    is a multidisciplinary researcher, trained as both an informatician and a clinically active radiologist. She is an assistant professor at Emory university, and works in Interventional Radiology and Informatics. She has been funded through the Grand Challenges Canada, NBIB and NSF ECCS. Her career focus is on validating machine learning models for health in real clinical settings, exploring explainability, fairness, and a specific focus on how algorithms fail. She has worked on the curation of datasets for the SIIM (Society for Imaging Informatics in Medicine) hackathon and ML committee. She volunteers on the ACR and RSNA machine learning committees to support the AI ecosystem to advance development and use of AI in medicine. She is currently working on the sociotechnical context for AI explainability for radiology, especially the dimensions of human factors that govern user perceptions and preferences of XAI systems.

    Dr Alistair Johnson, PhD

    Research Scientist, MIT

    a research scientist at the Massachusetts Institute of Technology working on data analysis in critical care. This includes retrospective observational studies to generate new knowledge, predictive modeling using machine learning to prognosticate outcome, and curation of data to support the research enterprise. You can check out some of my work below, and if you’re interested in collaboration or just want to chat, feel free to get in touch!

    Dr Tom Pollard, PhD

    Research Scientist, MIT

    a researcher in the Laboratory for Computational Physiology at MIT, with a particular interest in improving the way that clinical data is shared and reused for the benefit of patients. Previously I was a PhD student at University College London, where I carried out an interdisciplinary project between the Mullard Space Science Laboratory and University College Hospital, exploring how models of 'normal' health can be used to track the physiological status of critical care patients.

    Dr Fei Wang, PhD, FAMIA

    Associate Professor at Weill Cornell Medicine

    is an Associate Professor at Department of Population Health Sciences, Weill Cornell Medicine, Cornell University. His major research interest is data mining, machine learning and their applications in health data science. He has published on the top venues of related areas such as ICML, KDD, NeurIPS, AAAI, JAMA Internal Medicine, Annals of Internal Medicine, etc. His papers have received over 13,400 citations so far with an H-index 57. His (or his students’) papers have won 7 best paper (or nomination) awards at international academic conferences. His team won the championship of the NIPS/Kaggle Challenge on Classification of Clinically Actionable Genetic Mutations in 2017 and Parkinson’s Progression Markers Initiative data challenge organized by Michael J. Fox Foundation in 2016. Dr. Wang is the recipient of the NSF CAREER Award in 2018, as well as the inaugural research leadership award in IEEE International Conference on Health Informatics (ICHI) 2019. Dr. Wang is the chair of the Knowledge Discovery and Data Mining working group in American Medical Informatics Association (AMIA). Dr. Wang is a Fellow of AMIA.

    Dr Joel Park, MD MS FACEP​

    Director, Medical Informatics and Health Information Systems at BeiGene