{"id":4337,"date":"2016-12-29T15:22:37","date_gmt":"2016-12-29T15:22:37","guid":{"rendered":"https:\/\/meetings.informs.org\/wordpress\/meetings2-2\/?page_id=4337"},"modified":"2022-11-30T15:53:57","modified_gmt":"2022-11-30T15:53:57","slug":"keynotes","status":"publish","type":"page","link":"https:\/\/meetings.informs.org\/wordpress\/wsc2022\/keynotes\/","title":{"rendered":"Keynotes"},"content":{"rendered":"

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2022 Keynote Panel
Reimagine Tomorrow<\/em><\/strong><\/span><\/h2>\n

In spite of a complete lack of natural resources, Singapore is a global economic powerhouse as the second-richest country in the world in terms of purchasing power parity. A hub for maritime, logistics, advanced manufacturing, and financial services, the secret to its success is its insatiable appetite for re-invention: \u201cSingapore Reimagined\u201d as part of the Smart Nation initiative is its latest re-invention project. In this panel, we will hear from the leaders of some of the key Singaporean industries about their contributions to this ambitious national project and the role played by simulation in enabling their contributions.<\/p> <\/div>\n<\/div>\n

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\n Kenneth Lim <\/h3>\n
\n Assistant Chief Executive (Industry & Transformation), Maritime and Port Authority of Singapore <\/div>\n \n <\/div>\n \n <\/div>\n <\/div>\n
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\n Ngien Hoon Ping <\/h3>\n
\n Group CEO, SMRT Corporation Ltd. <\/div>\n \n <\/div>\n \n <\/div>\n <\/div>\n
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\n Ong Kim Pong <\/h3>\n
\n Regional CEO, PSA International, Singapore <\/div>\n \n <\/div>\n \n <\/div>\n <\/div>\n
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2022 Titans of Simulation<\/strong><\/span><\/h2> <\/div>\n<\/div>\n
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Michael Fu<\/strong><\/h4>\n
Smith Chair of Management Science Decision, Operations and Information Technologies
<\/i>Robert H. Smith School of Business
University of Maryland<\/h5>\n

Stochastic Gradients: From Single Sample Paths to Conditional Monte Carlo to\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 Machine Learning

<\/strong>Dr. Michael Fu will make a humble attempt to convey one perspective of his journey through nearly four decades of simulation methodology research focused on stochastic gradient estimation and simulation optimization, highlighting technical advances and some real-world success stories (mainly of others) and illustrating several techniques using simple examples, sprinkled in with personal anecdotes, some historical context, and random ramblings. Perhaps by the end of the talk, with the guidance of the audience, potential future sample paths can be envisioned or reimagined.<\/p> <\/div>\n<\/div>\n\n

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