• SPEAKERS

    for AI Healthcare Talk, 6 July 2018 @ NUHS Tower Block

  • Guest of Honour

    Prof Tan Chorh Chuan

    Executive Director,
    MOH Office for Healthcare Transformation

    Ministry of Health (MOH)

  • Speakers

    Dr Ngiam Kee Yuan

    Group Chief Technology Officer (CTO)

    National University Health System (NUHS)

    Asst Prof Mengling Feng

    Assistant Professor

    Saw Swee Hock School of Public Health (SSHSPH), National University of Singapore (NUS)

    Prof Ravishankar K. Iyer

    Professor

    Electrical and Computer Engineering,

    University of Illinois at Urbana-Champaign (UIUC)

    Asst Prof Alex Cook

    Vice Dean of Research

    Saw Swee Hock School of Public Health (SSHSPH), National University of Singapore (NUS)

    Mr Jason Widjaja

    Associate Director Data Science
    (AI & Data Products)

    Merck Sharp & Dohme (MSD) Singapore

    Prof Leong Tze Yun

    Director, AI Technology

    AI Singapore (AISG)

    Prof Ooi Beng Chin

    Chair Professor

    National University of Singapore (NUS)

    Marianne Slight

    Healthcare Analytics & Machine Learning
    Product Management Executive

    Google

    Prof Hidenobu Shigemitsu

    Chair of Department

    Department of Intensive Care Medicine,

    Tokyo Medical and Dental University (TMDU)

    Mr Steve Leonard

    Founding CEO

    SGInnovate

    Dr Xie Guotong

    Chief Healthcare Scientist

    PingAn Technology​

    Asst Prof Leo Anthony Celi

    Clinical Research Director 

    Laboratory of Computational Physiology​,
    Massachusetts Institute of Technology (MIT)

    Asst Prof Naoaki (Nao) Ichihara

    Assistant Professor

    Department of Healthcare Quality Assessment,

    University of Tokyo (UT)​

    Dr Qing Wang

    Research Staff Member

    IBM Research China (IBM)

    Hector Yee

    Staff Software Engineer

    Google

    Tian Cong

    Principal Data Scientist

    Philips Research and Development (Philips)

  • International Mentors

    Cátia Salgado

    Massachusetts Institute of Technology (MIT)

    Wei-Hung Weng

    Massachusetts Institute of Technology (MIT)

    Nikhil Shankar

    Massachusetts Institute of Technology (MIT)

    David Sasson

    Harvard T.H. Chan
    School of Public Health

    Ned McCague

    Massachusetts Institute of Technology (MIT)

    Louis Agha-Mir-Salim

    Imperial College Business School

    Dr Huang Chao-Hui

    Senior Scientist

    MSD

  • Speakers' and Mentors' Profile

    Dr Ngiam Kee Yuan (NUHS)

    is a Consultant General Surgeon specialising in Thyroid and Endocrine surgical disorders. Following the completion of his Advanced Specialist Training in General Surgery, he was awarded a fellowship from the Royal College of Surgeons of Edinburgh and was accredited as a surgical specialist by the Specialist Accreditation Board, Singapore. He is concurrently the Deputy Chief Medical Informatics Officer at the National University Health System and Director of Surgical Research and Development at the Department of Surgery, School of Medicine, National University of Singapore. Dr Ngiam’s special interests are in thyroid and endocrine surgery, robotic thyroid surgery, bariatric and metabolic surgery as well as machine learning in clinical informatics.

    Asst Prof Mengling Feng (NUS)

    is currently an Assistant Professor at National University of Singapore with School of Public Health, School of Medicine and School of Computing. He is also the Senior Assistant Director of National University Hospital championing the big data analytics efforts. Dr Feng is also an affiliated scientist with the Lab of Computational Physiology, Harvard-MIT Health Science Technology Division. His research is to develop effective Big Data management and analysis methods to extract actionable knowledge to improve the quality of care. His research brings together concepts and tools across machine learning, optimization, signal processing, statistical causal inference and big data management. In particular, he has been publishing on physiological signal forecasting, modeling of disease progress trajectory, dynamic patient phenotyping, statistical understanding of treatment effects and management of heterogeneous medical big data. Dr. Feng’s work was recognized by both well-established journals, such as Science Translational Medicine, and top international conferences, such as KDD, AAAI and AMIA.

    Prof Ravishankar K. Iyer​ (UIUC)

    is George and Ann Fisher Distinguished Professor of Engineering and holds appointments in the Coordinated Science Laboratory (CSL), the Information Trust Institute (ITI), Electrical and Computer Engineering (ECE), and Computer Science (CS). His research focuses on reliable and dependable computing, with application to varied fields such as system building, health monitoring, security and data analysis, cloud computing, and the power grid.

    Asst Prof Alex Cook (NUS)

    is an associate professor in the Saw Swee Hock School of Public Health of the National University of Singapore and National University Health System. He also have appointments at the Department of Statistics and Applied Probability and the Program in Health Services and Systems Research at the Duke-NUS Graduate Medical School Singapore and am a visiting scientific consultant at the Communicable Disease Centre at Tan Tock Seng Hospital. Dr Cook's research interests are in the area of Infectious disease modelling, statistical inference for infectious disease models, Bayesian statistics, computer simulations in health, statistical demography.

    Mr Jason Widjaja (MSD)

    leads a data science team within MSD's Global Data Science Competency specializing in machine learning, AI and open source product development. He is a hybrid business-technical leader with three scholarships in his MBA and Masters of Business Analytics, a first class hons in Information Systems with HR and a Bachelor of Computing. He works to meld the best of both the MNC and startup worlds to develop practical data science products in MSD, and is an advocate of the ethical deployment of AI at scale. Jason spent half his career overseas in Australia before relocating back to Singapore in 2016. He is passionate about developing people to thrive in an Industry 4.0 future and is currently Quora's top writer on Analytics.

     

    "The world’s most important data science work demands the world’s best data science team."

    Prof Leong Tze Yun​ (AISG)

    is Director of AI Technology at AI Singapore. She is Professor of Practice of Computer Science at the School of Computing, National University of Singapore. She also directs the Medical Computing Laboratory at the School. Tze Yun received her SB, SM, and PhD degrees in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology (MIT), USA. Her research interests include decision-theoretic artificial intelligence, cognitive modeling, machine learning, adaptive computing, and biomedical and health informatics. She has over 150 publications in international peer-reviewed journals and conferences. She has served on editorial boards and program committees of leading international journals and conferences in artificial intelligence and biomedical informatics. She is an elected Fellow of the American College of Medical Informatics (ACMI) and a founding Member of the International Academy of Health Sciences Informatics (IAHSI). Tze Yun is also a technopreneur and participates in the technology start-ups ecosystem. With both academic background and business experience, she has contributed to panels and committees that advise on R&D directions and education in Computer Science, Artificial Intelligence, and Health Informatics in both Singapore and abroad. She recently served as Member of the Working Committee on Research and Technology of the Information and Communication Technology and Media Master Plan 2025 in Singapore (2013-2015), Vice President overseeing the working groups and special interest groups of the International Medical Informatics Association (IMIA) (2013-2016), and Advisory Board Member of the United Nations University Institute for Computing and Society (UNU-CS) (2012-2016).

    Prof Ooi Beng Chin​ (NUS)

    is a Distinguished Professor of Computer Science, NGS faculty member and Director of Smart Systems Institute (SSI@NUS) at the National University of Singapore (NUS), an adjunct Chang Jiang Professor at Zhejiang University, China, and the director of NUS AI Innovation and Commercialization Centre at Suzhou, China. He obtained his BSc (1st Class Honors) and PhD from Monash University, Australia, in 1985 and 1989 respectively. Beng Chin's research interests include database systems, distributed and blockchain systems, machine learning and large scale analytics, in the aspects of system architectures, performance issues, security, accuracy and correctness. He works closely with the industry (eg. NUHS, Jurong Health and Tan Tok Seng Hospital on healthcare analytics and prediebetes prevention), and exploits IT for efficiency in various appplication domains, including healthcare, finance and smart city. He is a co-founder of yzBigData(2012) for Big Data Management and analytics, and Shentilium Technologies(2016) for AI- and data-driven Financial data analytics, MediLot Technologies(2018) for blockchain based healthcare data management and analytics. an advisory council member of a RegTech company, Cynopsis Solutions, and an advisor to blockchain based KYC traceto.io ICO. Beng Chin serves as a non-executive and independent director of ComfortDelgro and a member of Hangzhou Government AI Development Committee (AI TOP 30).

    Marianne Slight​ (Google)

    loves to solve buyer problems with new technology that users want to adopt: creating products that drive growth and margin. Her key strengths are product management, product marketing and leading teams to create, mature and market successful software products. Portfolio includes healthcare analytic cloud products and platforms with artificial intelligence (AI), machine learning (ML), and natural language processing (NLP).

    Prof Hidenobu Shigemitsu (TMDU)

    is professor and chair of the department of Intensive Care Medicine at Tokyo Medical and Dental University. He also oversees the advancement of global initiatives and partnerships as the deputy chief of the Institute of Global Affairs at Tokyo Medical and Dental University. He completed his fellowship education in critical care medicine and pulmonary medicine at Stanford University School of Medicine. He held leadership positions at several institutions in the United States including professor and chief at University of Nevada School of Medicine prior to his current position. His research interests include patient care system implementation and development of database in ICU and was the chairman of the 1st Big Data Machine Learning in Healthcare Datathon in Japan in February 2018.

    Mr Steve Leonard​ (SGInnovate)

    is a technology-industry leader with a wide range of experience, having played key roles in building several global companies in areas such as Software, Hardware and Services. Although born in the US, Mr Leonard considers himself a member of the larger global community, having lived and worked outside the US for more than 25 years. In his current role as the Founding Chief Executive Officer of SGInnovate – a private limited company wholly owned by the Singapore Government – Mr Leonard has been chartered to lead an organisation that builds ‘deep-tech’ companies. Capitalising on the science and technology research for which Singapore has gained a global reputation, Mr Leonard’s team works with local and international partners, including universities, venture capitalists, and major corporations to help technical founders imagine, start and scale globally-relevant earlystage technology companies from Singapore. Prior to his role as the CEO of SGInnovate, Mr Leonard served three years as the Executive Deputy Chairman of the Infocomm Development Authority (IDA), a government statutory board under the purview of Singapore’s Ministry of Communications and Information. In that role, he had executive responsibility at the national level for various aspects of the information technology and telecommunications industries in Singapore. Mr Leonard serves on the advisory boards of a range of universities and organisations in Singapore. Mr Leonard also serves as an Independent Non-Executive Director at Singapore Post Ltd (SingPost), a global leader in e-commerce logistics; and AsiaSat, a Hong Kong Stock Exchange-listed commercial operator of communication spacecraft.

    Dr Xie Guotong (PingAn)

    joined IBM Research in 2003 as Lead Cognitive Health research in IBM China Research Lab, and co-lead Healthcare Informatics strategy for IBM global research. Mr Guotong Xie delivered research technologies to IBM Watson Health offerings and topped healthcare clients in China, including the most influential hospitals, pharmaceuticals, local government and healthcare IT providers. During his appointment at IBM, Mr Guotong Xie had published 50 research papers in international conferences/journals and 40 patents, awarded 3 IBM research accomplishment and Best of IBM award.  In 2017, Mr Guotong Xie started to Lead PingAn Healthcare AI Initiative to land AI solutions by leveraging its massive amount of medical data and access to patients, health providers and payers.

    Asst Prof Leo Anthony Celi​ (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.

    Asst Prof Naoaki (Nao) Ichihara (UT)

    is an Assistant Professor at Department of Healthcare Quality Assessment, University of Tokyo (UT). He practiced as an invasive/non-invasive cardiologist at Kameda Medical Center and Yokohama City University (YCU) Hospital. Received Ph.D. at YCU Graduate School of Medicine and Master of Public Health (MPH) at Harvard T. H. Chan School of Public Health. Worked for Harvard University Health Services as a Data Analysist/Project Manager. Participated in development of a smartphone app for engaging patients to improve safety of care at Brigham and Women’s Hospital. Worked for OpenClinica, LLC., a company that produces an open-source software for clinical trials, as a Senior Business Analyst. At UT, he is involved in clinical/health services research, application of advanced methods for data exploration/visualization/statistical analysis, management of clinical registries, development of software tools for analysis, along with educational activities. Strong focus on improving quality of care and improving effectiveness of the healthcare system.

    Dr Qing Wang (IBM)

    is a Research Staff Member of IBM Research China. She joined IBM in 2004 after obtaining Ph.D from School of EEE , Nanyang Technological University, Singapore in 2003. Her current research fields include computer vision with deep learning, machine learning, medical image processing, etc. Currently, she is one of the key contributors to build a deep learning platform named POWER AI Vision and also to develop algorithms on video classification and action recognition. She is skillful on deep neural network, statistical analysis, system acceleration for Power, X86 and Cell Broadband Engine. She has rich engineering experiences through projects with major enterprises. On GTC2018, she was chosen as the Featured Speakers to introduce her work on video summarization using multimodal learning. She has published over 30 papers, 2 book chapters, and about 20 patents filed. She is an IEEE Senior Member and severs for several conferences as technical member.

    Hector Yee​ (Google)

    leads a team at Google AI: Healthcare researching the applications of machine learning on Medical Waveforms. His other Google projects include image search ranking, perception for the self-driving car, video content analysis and Youtube’s Emmy award winning personalized video recommendation system. He has also worked on Airbnb's smart pricing system, movies such as Shrek 2 and video games such as Star Wars: Empire at War.

    Cong Tian​ (Philips)

    is a Senior Scientist in Philips Research China, working on the data analytics and clinical decision support in critical care medicine as well as non-communicable diseases. Her research interests include machine learning for clinical application, clinical decision support for critical care diseases and non-communicable diseases.

    Cátia Salgado​ (MIT)

    is a PhD student in Bioengineering Systems from MIT Portugal, at the Department of Mechanical Engineering, Instituto Superior Técnico, University of Lisbon, Portugal. She received the MSc degree in Biomedical Engineering from University of Minho, Portugal, in 2012. Her PhD thesis is titled “Data-based modeling for personalized medicine in the ICU”, and it is focused on the use of machine learning techniques to predict patient adverse events following admission to intensive care units. More specifically, she works in fuzzy modeling and fuzzy clustering applied to health care systems.

    Wei-Hung Weng​ ​(MIT)

    is a PhD graduate at MIT EECS and Computer Science and Artificial Intelligence Laboratory. Prior to joining MIT, he received the MMSc in Biomedical Informatics from Harvard Medical School in 2017, earned his MD degree from Chang Gung University in 2011, and worked as a physician and pathologist in Taiwan for years. His research interests are multimodal representation learning and reinforcement learning for clinical decision making.

    Nikhil Shankar​​ (MIT)

    was born in southern Florida, studied chemical and biomolecular engineering in Philadelphia for college, medicine in New York, and then moved to Boston for residency in Emergency Medicine at Beth Israel Deaconess Medical Center. He is currently in his final year of residency and plans to stay in Boston after graduation to work both as a clinician and researcher with appointments with both Harvard medical faculty and the MIT Laboratory for Computational Physiology. He has spent almost all of his academic career searching for ways to fuse medicine and engineering, and deeply enjoys working with data scientists to interrogate large databases with unique clinically meaningful queries. In his spare time, he enjoys rock climbing, attending concerts, learning foreign languages, and hiking.

    David Sasson ​(Harvard T.H. Chan)

    is a graduate student at the Harvard T.H. Chan School of Public Health studying Health Data Science. Prior to joining MIT Critical Data he completed his undergraduate degree in Biochemistry and held research appointments in private, government, and academic sectors. In addition to working in research, David has volunteered in medically underserved areas spanning the greater New York City area, rural Appalachia, and central Bolivia. His current interests include the microbiome, democratized AI, and the diminishing separations between biology and technology.​

    Ned McCague​ (MIT)

    is data scientist in Boston and has worked in the data space for over a decade. He currently works at Kyruus, a Boston-based startup focused on patient access and provider data management. Additionally, he holds a faculty appointment at MIT where he lectures on Global Health Informatics and Data Science in Healthcare.

    Louis Agha-Mir-Salim​ (Imperial College)

    is currently studying Management at Imperial College Business School, pausing his medical degree at the University of Southampton for one year to explore healthcare beyond the aspects of clinical medicine. Prior to attending Imperial College London, Louis completed a Bachelor of Medical Sciences in the third year of his medical degree. Believing an interdisciplinary approach is key to tackling complex problems, he has a special interest in health informatics and digital health innovation for improving the quality healthcare delivery.

    Dr Huang Chao-Hui, Senior Scientist (MSD)

    Dr. HUANG is currently a senior scientist of bioimaging informatics in MSD/Merck International GmbH (Singapore Branch). Before he joined MSD, he was a postdoctoral researcher in Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), Singapore. He has been working in the fields of medical/biomedical imaging informatics, bioinformatics, biostatistics and pathology informatics, including immunohistochemistry (IHC), whole slide image (WSI) analysis and automated microscopy, based on his capabilities of applied mathematics, statistical analysis, and information technology, such as statistical/predictive modelling, machine learning, computer vision, knowledge reasoning/representation, massively parallel programming and cluster/cloud computing.