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World Scientific is a wealth of high quality of research and academic resource in sciences, social sciences, humanities, engineering, education, health science, Asian studies plus more. publishes about 600 new titles a year and 140 journals in various fields. World Scientific has published more than 12,000 titles. Many of its books are recommended texts adopted by renowned institutions such as Harvard University, California Institute of Technology, Stanford University and Princeton University. You can access the world scientific database at the VinUni library website.

Competing by customer experience is no longer enough, businesses need to compete by "personal transformation". Read the latest article written by the Harvard professors, published in Feb, 2022 to better understand why it is necessary to apply this model to excel.

People around the globe have been talking about a post-pandemic future since the pandemic first made headlines more than two years ago. But the wellness market emerging from coronavirus is anything but a return to 2019. The Future of Wellness 2022 trends report reveals that what consumers are demanding has profoundly changed—and that wellness is taking provocative new directions. Experts have identified 10 wellness trends: from a new soil-focused and survivalist wellness—to the men’s body image crisis and women’s health research gap finally getting addressed—to the rise of the wellness metaverse, certified wellness coaches, urban wellness playgrounds, and healthier senior living models.

What makes the relationship between leaders and their employees better? What has changed the interaction between people, not only in the business environment but also in society to become more positive? Find out more about the book summary that Professor David Harrison introduced to you this month.

Professor Laurent will share his new research in the field of AI - Implicit Deep Learning model. This implicit structure promises to simplify the notations in deep learning, and holds great promise in finding new algorithms and structures.

A new approach to modeling sequential data, called Deep Equilibrium Model (DEQ) is introduced. Motivated by the convergence of the hidden layers in existing deep sequence models, the DEQ can find these equilibrium points directly through root finding. The process is equivalent to running an infinite-depth feedforward network, with the added benefits that the equilibrium points can be backpropagated using implicit differentiation. This approach bypasses the depth of the network, and thus uses constant memory.